Overview

Dataset statistics

Number of variables79
Number of observations100
Missing cells2067
Missing cells (%)26.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory64.5 KiB
Average record size in memory660.3 B

Variable types

Text31
Categorical23
Numeric21
Boolean3
Unsupported1

Alerts

lclas has constant value ""Constant
mlsfc has constant value ""Constant
lst_updt_dt has constant value ""Constant
data_orgn has constant value ""Constant
file_name has constant value ""Constant
base_ymd has constant value ""Constant
regist_yn is highly imbalanced (75.8%)Imbalance
regist_stts is highly imbalanced (75.8%)Imbalance
osvc_av_gud_fee is highly imbalanced (58.8%)Imbalance
pre_schl_gnrl_fee is highly imbalanced (82.1%)Imbalance
grp_spc_fee_dcrate is highly imbalanced (56.6%)Imbalance
hr_pbl_curatr_tot is highly imbalanced (57.7%)Imbalance
hr_pbl_pbsvnt_curatr_crqfc_pos_cnt is highly imbalanced (73.5%)Imbalance
hr_pbl_irgllbr_curatr_crqfc_pos_cnt is highly imbalanced (61.2%)Imbalance
hr_pbl_intern is highly imbalanced (79.3%)Imbalance
hr_prv_curatr_crqfc_pos_cnt is highly imbalanced (73.5%)Imbalance
hr_prv_curatr_crqfc_non_pos_cnt is highly imbalanced (56.8%)Imbalance
hr_prv_intern is highly imbalanced (52.6%)Imbalance
osvc_addr has 7 (7.0%) missing valuesMissing
osvc_av_gud_prvd_yn has 6 (6.0%) missing valuesMissing
osvc_mssys_prvd_yn has 6 (6.0%) missing valuesMissing
plot_aea has 2 (2.0%) missing valuesMissing
buld_totar has 4 (4.0%) missing valuesMissing
ehbll_aea has 2 (2.0%) missing valuesMissing
shlf_aea has 6 (6.0%) missing valuesMissing
edu_plce_aea has 35 (35.0%) missing valuesMissing
ofce_aea has 7 (7.0%) missing valuesMissing
data_lbr_booth_aea has 46 (46.0%) missing valuesMissing
data_lbr_cnt has 53 (53.0%) missing valuesMissing
fyer_opn_dt_tot has 6 (6.0%) missing valuesMissing
fyer_usemem_tot has 3 (3.0%) missing valuesMissing
dyrg_usemem_cnt has 5 (5.0%) missing valuesMissing
gnrl_fee has 81 (81.0%) missing valuesMissing
ele_schl_gnrl_fee has 82 (82.0%) missing valuesMissing
mid_hi_gnrl_fee has 82 (82.0%) missing valuesMissing
age_19_25_gnrl_fee has 83 (83.0%) missing valuesMissing
grp_gnrl_fee_dcrate has 86 (86.0%) missing valuesMissing
etc_gnrl_fee_dcrate has 90 (90.0%) missing valuesMissing
gnrl_fee_dc_policy has 85 (85.0%) missing valuesMissing
spc_fee has 63 (63.0%) missing valuesMissing
pre_schl_spc_fee has 88 (88.0%) missing valuesMissing
pre_ele_schl_spc_fee has 68 (68.0%) missing valuesMissing
mid_hi_spc_fee has 67 (67.0%) missing valuesMissing
age_19_25_spc_fee has 71 (71.0%) missing valuesMissing
etc_spc_fee_dcrate has 76 (76.0%) missing valuesMissing
spc_fee_dc_policy has 61 (61.0%) missing valuesMissing
spc_fee_free_trgt has 32 (32.0%) missing valuesMissing
hr_pbl_pbsvnt_subtot has 87 (87.0%) missing valuesMissing
hr_pbl_irgllbr_subtot has 77 (77.0%) missing valuesMissing
hr_pbl_poigs has 75 (75.0%) missing valuesMissing
hr_pbl_irgllbr has 77 (77.0%) missing valuesMissing
hr_pbl_volun has 82 (82.0%) missing valuesMissing
hr_prv_curatr_tot has 40 (40.0%) missing valuesMissing
hr_prv_non_curatr_exp_cnt has 74 (74.0%) missing valuesMissing
hr_prv_rgllbr has 66 (66.0%) missing valuesMissing
hr_prv_volun has 85 (85.0%) missing valuesMissing
rm has 100 (100.0%) missing valuesMissing
id has unique valuesUnique
fclt_name has unique valuesUnique
rm is an unsupported type, check if it needs cleaning or further analysisUnsupported
ehbll_aea has 3 (3.0%) zerosZeros

Reproduction

Analysis started2023-12-10 09:39:04.307095
Analysis finished2023-12-10 09:39:08.408111
Duration4.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

id
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:08.603937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowKCDMART21N000000001
2nd rowKCDMART21N000000268
3rd rowKCDMART21N000000003
4th rowKCDMART21N000000004
5th rowKCDMART21N000000005
ValueCountFrequency (%)
kcdmart21n000000001 1
 
1.0%
kcdmart21n000000063 1
 
1.0%
kcdmart21n000000074 1
 
1.0%
kcdmart21n000000073 1
 
1.0%
kcdmart21n000000072 1
 
1.0%
kcdmart21n000000071 1
 
1.0%
kcdmart21n000000070 1
 
1.0%
kcdmart21n000000069 1
 
1.0%
kcdmart21n000000068 1
 
1.0%
kcdmart21n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:39:09.115891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 715
37.6%
1 121
 
6.4%
2 121
 
6.4%
K 100
 
5.3%
T 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
R 100
 
5.3%
A 100
 
5.3%
M 100
 
5.3%
Other values (8) 243
 
12.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
57.9%
Uppercase Letter 800
42.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 715
65.0%
1 121
 
11.0%
2 121
 
11.0%
6 22
 
2.0%
7 21
 
1.9%
9 21
 
1.9%
4 20
 
1.8%
5 20
 
1.8%
8 20
 
1.8%
3 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
K 100
12.5%
T 100
12.5%
C 100
12.5%
N 100
12.5%
R 100
12.5%
A 100
12.5%
M 100
12.5%
D 100
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
57.9%
Latin 800
42.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 715
65.0%
1 121
 
11.0%
2 121
 
11.0%
6 22
 
2.0%
7 21
 
1.9%
9 21
 
1.9%
4 20
 
1.8%
5 20
 
1.8%
8 20
 
1.8%
3 19
 
1.7%
Latin
ValueCountFrequency (%)
K 100
12.5%
T 100
12.5%
C 100
12.5%
N 100
12.5%
R 100
12.5%
A 100
12.5%
M 100
12.5%
D 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 715
37.6%
1 121
 
6.4%
2 121
 
6.4%
K 100
 
5.3%
T 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
R 100
 
5.3%
A 100
 
5.3%
M 100
 
5.3%
Other values (8) 243
 
12.8%

lclas
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
문화시설
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row문화시설
2nd row문화시설
3rd row문화시설
4th row문화시설
5th row문화시설

Common Values

ValueCountFrequency (%)
문화시설 100
100.0%

Length

2023-12-10T18:39:09.324184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:09.436942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화시설 100
100.0%

mlsfc
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
미술관
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미술관
2nd row미술관
3rd row미술관
4th row미술관
5th row미술관

Common Values

ValueCountFrequency (%)
미술관 100
100.0%

Length

2023-12-10T18:39:09.564945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:09.683718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미술관 100
100.0%

fclt_name
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:09.910201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length7.95
Min length4

Characters and Unicode

Total characters795
Distinct characters184
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row국립현대미술관(과천)
2nd row제주조각공원
3rd row국립현대미술관(덕수궁)
4th row국립현대미술관 미술품수장센터(청주)
5th row겸재정선미술관
ValueCountFrequency (%)
미술관 10
 
7.6%
종로구립 2
 
1.5%
예술의전당 2
 
1.5%
국립현대미술관(과천 1
 
0.8%
경북대학교 1
 
0.8%
금봉미술관 1
 
0.8%
시화문화마을 1
 
0.8%
광주시립미술관 1
 
0.8%
해든뮤지움 1
 
0.8%
전원미술관 1
 
0.8%
Other values (111) 111
84.1%
2023-12-10T18:39:10.460808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
94
 
11.8%
91
 
11.4%
89
 
11.2%
32
 
4.0%
22
 
2.8%
16
 
2.0%
14
 
1.8%
13
 
1.6%
12
 
1.5%
12
 
1.5%
Other values (174) 400
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 717
90.2%
Space Separator 33
 
4.2%
Uppercase Letter 21
 
2.6%
Close Punctuation 9
 
1.1%
Open Punctuation 9
 
1.1%
Lowercase Letter 4
 
0.5%
Decimal Number 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
94
 
13.1%
91
 
12.7%
89
 
12.4%
22
 
3.1%
16
 
2.2%
14
 
2.0%
13
 
1.8%
12
 
1.7%
12
 
1.7%
8
 
1.1%
Other values (153) 346
48.3%
Uppercase Letter
ValueCountFrequency (%)
C 6
28.6%
I 3
14.3%
A 2
 
9.5%
O 2
 
9.5%
T 1
 
4.8%
D 1
 
4.8%
X 1
 
4.8%
L 1
 
4.8%
J 1
 
4.8%
M 1
 
4.8%
Other values (2) 2
 
9.5%
Lowercase Letter
ValueCountFrequency (%)
e 2
50.0%
m 1
25.0%
u 1
25.0%
Space Separator
ValueCountFrequency (%)
32
97.0%
  1
 
3.0%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
6 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 717
90.2%
Common 53
 
6.7%
Latin 25
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
94
 
13.1%
91
 
12.7%
89
 
12.4%
22
 
3.1%
16
 
2.2%
14
 
2.0%
13
 
1.8%
12
 
1.7%
12
 
1.7%
8
 
1.1%
Other values (153) 346
48.3%
Latin
ValueCountFrequency (%)
C 6
24.0%
I 3
12.0%
A 2
 
8.0%
e 2
 
8.0%
O 2
 
8.0%
T 1
 
4.0%
D 1
 
4.0%
X 1
 
4.0%
m 1
 
4.0%
u 1
 
4.0%
Other values (5) 5
20.0%
Common
ValueCountFrequency (%)
32
60.4%
) 9
 
17.0%
( 9
 
17.0%
3 1
 
1.9%
6 1
 
1.9%
  1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 717
90.2%
ASCII 77
 
9.7%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
94
 
13.1%
91
 
12.7%
89
 
12.4%
22
 
3.1%
16
 
2.2%
14
 
2.0%
13
 
1.8%
12
 
1.7%
12
 
1.7%
8
 
1.1%
Other values (153) 346
48.3%
ASCII
ValueCountFrequency (%)
32
41.6%
) 9
 
11.7%
( 9
 
11.7%
C 6
 
7.8%
I 3
 
3.9%
A 2
 
2.6%
e 2
 
2.6%
O 2
 
2.6%
T 1
 
1.3%
D 1
 
1.3%
Other values (10) 10
 
13.0%
None
ValueCountFrequency (%)
  1
100.0%

ctprvn_nm
Categorical

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
45 
경기도
15 
광주광역시
14 
부산광역시
인천광역시
Other values (4)
13 

Length

Max length7
Median length5
Mean length4.75
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row경기도
2nd row제주특별자치도
3rd row서울특별시
4th row충청북도
5th row서울특별시

Common Values

ValueCountFrequency (%)
서울특별시 45
45.0%
경기도 15
 
15.0%
광주광역시 14
 
14.0%
부산광역시 8
 
8.0%
인천광역시 5
 
5.0%
대전광역시 5
 
5.0%
대구광역시 4
 
4.0%
제주특별자치도 3
 
3.0%
충청북도 1
 
1.0%

Length

2023-12-10T18:39:10.779012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:11.538279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 45
45.0%
경기도 15
 
15.0%
광주광역시 14
 
14.0%
부산광역시 8
 
8.0%
인천광역시 5
 
5.0%
대전광역시 5
 
5.0%
대구광역시 4
 
4.0%
제주특별자치도 3
 
3.0%
충청북도 1
 
1.0%

sgnr_nm
Categorical

Distinct40
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로구
18 
동구
남구
용산구
 
5
서구
 
4
Other values (35)
59 

Length

Max length4
Median length3
Mean length2.81
Min length2

Unique

Unique20 ?
Unique (%)20.0%

Sample

1st row과천시
2nd row서귀포시
3rd row중구
4th row청주시
5th row강서구

Common Values

ValueCountFrequency (%)
종로구 18
18.0%
동구 8
 
8.0%
남구 6
 
6.0%
용산구 5
 
5.0%
서구 4
 
4.0%
중구 4
 
4.0%
강남구 4
 
4.0%
서초구 4
 
4.0%
강화군 3
 
3.0%
북구 3
 
3.0%
Other values (30) 41
41.0%

Length

2023-12-10T18:39:12.183219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종로구 18
18.0%
동구 8
 
8.0%
남구 6
 
6.0%
용산구 5
 
5.0%
서구 4
 
4.0%
중구 4
 
4.0%
강남구 4
 
4.0%
서초구 4
 
4.0%
강화군 3
 
3.0%
북구 3
 
3.0%
Other values (30) 41
41.0%

legaldong_cd
Real number (ℝ)

Distinct85
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.345477 × 109
Minimum1.1110106 × 109
Maximum5.013031 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:13.076750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110106 × 109
5-th percentile1.1110121 × 109
Q11.1192612 × 109
median2.6365104 × 109
Q32.917011 × 109
95-th percentile4.1830257 × 109
Maximum5.013031 × 109
Range3.9020204 × 109
Interquartile range (IQR)1.7977498 × 109

Descriptive statistics

Standard deviation1.2287238 × 109
Coefficient of variation (CV)0.52386948
Kurtosis-1.0889583
Mean2.345477 × 109
Median Absolute Deviation (MAD)1.4760014 × 109
Skewness0.42700442
Sum2.345477 × 1011
Variance1.5097622 × 1018
MonotonicityNot monotonic
2023-12-10T18:39:13.624866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2911012100 4
 
4.0%
1165010800 3
 
3.0%
3017012800 2
 
2.0%
1171011100 2
 
2.0%
1111011900 2
 
2.0%
2635010500 2
 
2.0%
1111018300 2
 
2.0%
1111014900 2
 
2.0%
1111018400 2
 
2.0%
1168010700 2
 
2.0%
Other values (75) 77
77.0%
ValueCountFrequency (%)
1111010600 1
1.0%
1111011100 1
1.0%
1111011900 2
2.0%
1111012000 1
1.0%
1111012100 1
1.0%
1111012300 1
1.0%
1111012400 1
1.0%
1111014200 1
1.0%
1111014400 1
1.0%
1111014900 2
2.0%
ValueCountFrequency (%)
5013031026 1
1.0%
5013025924 1
1.0%
5011025925 1
1.0%
4311410200 1
1.0%
4183038028 1
1.0%
4183025021 1
1.0%
4182032527 1
1.0%
4167012000 1
1.0%
4163034024 1
1.0%
4157025626 1
1.0%
Distinct85
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:14.186450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.58
Min length2

Characters and Unicode

Total characters358
Distinct characters109
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)73.0%

Sample

1st row막계동
2nd row안덕면 덕수리
3rd row정동
4th row내덕동
5th row가양동
ValueCountFrequency (%)
운림동 4
 
3.6%
서초동 3
 
2.7%
평창동 2
 
1.8%
세종로 2
 
1.8%
신사동 2
 
1.8%
양림동 2
 
1.8%
방이동 2
 
1.8%
만년동 2
 
1.8%
우동 2
 
1.8%
한남동 2
 
1.8%
Other values (86) 88
79.3%
2023-12-10T18:39:14.868326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
24.0%
11
 
3.1%
11
 
3.1%
9
 
2.5%
9
 
2.5%
9
 
2.5%
8
 
2.2%
7
 
2.0%
7
 
2.0%
6
 
1.7%
Other values (99) 195
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 339
94.7%
Space Separator 11
 
3.1%
Decimal Number 8
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
86
25.4%
11
 
3.2%
9
 
2.7%
9
 
2.7%
9
 
2.7%
8
 
2.4%
7
 
2.1%
7
 
2.1%
6
 
1.8%
6
 
1.8%
Other values (95) 181
53.4%
Decimal Number
ValueCountFrequency (%)
2 5
62.5%
1 2
 
25.0%
4 1
 
12.5%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 339
94.7%
Common 19
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
86
25.4%
11
 
3.2%
9
 
2.7%
9
 
2.7%
9
 
2.7%
8
 
2.4%
7
 
2.1%
7
 
2.1%
6
 
1.8%
6
 
1.8%
Other values (95) 181
53.4%
Common
ValueCountFrequency (%)
11
57.9%
2 5
26.3%
1 2
 
10.5%
4 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 339
94.7%
ASCII 19
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
86
25.4%
11
 
3.2%
9
 
2.7%
9
 
2.7%
9
 
2.7%
8
 
2.4%
7
 
2.1%
7
 
2.1%
6
 
1.8%
6
 
1.8%
Other values (95) 181
53.4%
ASCII
ValueCountFrequency (%)
11
57.9%
2 5
26.3%
1 2
 
10.5%
4 1
 
5.3%

adstrd_cd
Real number (ℝ)

Distinct79
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3455191 × 109
Minimum1.1110515 × 109
Maximum5.013031 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:15.086680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110515 × 109
5-th percentile1.111054 × 109
Q11.1193084 × 109
median2.6365541 × 109
Q32.9170614 × 109
95-th percentile4.1830256 × 109
Maximum5.013031 × 109
Range3.9019795 × 109
Interquartile range (IQR)1.797753 × 109

Descriptive statistics

Standard deviation1.2287171 × 109
Coefficient of variation (CV)0.5238572
Kurtosis-1.0889847
Mean2.3455191 × 109
Median Absolute Deviation (MAD)1.4760149 × 109
Skewness0.42699221
Sum2.3455191 × 1011
Variance1.5097456 × 1018
MonotonicityNot monotonic
2023-12-10T18:39:15.325129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2911071000 4
 
4.0%
1111053000 4
 
4.0%
1165053000 3
 
3.0%
1111061500 3
 
3.0%
1111054000 2
 
2.0%
1168054500 2
 
2.0%
3017065000 2
 
2.0%
2911052500 2
 
2.0%
1111056000 2
 
2.0%
1117068500 2
 
2.0%
Other values (69) 74
74.0%
ValueCountFrequency (%)
1111051500 1
 
1.0%
1111053000 4
4.0%
1111054000 2
2.0%
1111055000 2
2.0%
1111056000 2
2.0%
1111060000 2
2.0%
1111061500 3
3.0%
1111064000 1
 
1.0%
1111065000 1
 
1.0%
1114052000 2
2.0%
ValueCountFrequency (%)
5013031000 1
1.0%
5013025900 1
1.0%
5011025900 1
1.0%
4311453000 1
1.0%
4183038000 1
1.0%
4183025000 1
1.0%
4182032500 1
1.0%
4167053000 1
1.0%
4163034000 1
1.0%
4157025600 1
1.0%
Distinct77
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:15.741891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.56
Min length3

Characters and Unicode

Total characters356
Distinct characters107
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)61.0%

Sample

1st row문원동
2nd row안덕면
3rd row소공동
4th row내덕2동
5th row가양1동
ValueCountFrequency (%)
사직동 5
 
5.0%
학운동 4
 
4.0%
서초3동 3
 
3.0%
종로1.2.3.4가동 3
 
3.0%
한남동 2
 
2.0%
압구정동 2
 
2.0%
충장동 2
 
2.0%
평창동 2
 
2.0%
삼청동 2
 
2.0%
양림동 2
 
2.0%
Other values (67) 73
73.0%
2023-12-10T18:39:16.511896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90
25.3%
2 14
 
3.9%
3 11
 
3.1%
1 9
 
2.5%
. 9
 
2.5%
7
 
2.0%
7
 
2.0%
7
 
2.0%
7
 
2.0%
6
 
1.7%
Other values (97) 189
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 308
86.5%
Decimal Number 39
 
11.0%
Other Punctuation 9
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
90
29.2%
7
 
2.3%
7
 
2.3%
7
 
2.3%
7
 
2.3%
6
 
1.9%
6
 
1.9%
5
 
1.6%
5
 
1.6%
5
 
1.6%
Other values (91) 163
52.9%
Decimal Number
ValueCountFrequency (%)
2 14
35.9%
3 11
28.2%
1 9
23.1%
4 4
 
10.3%
6 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 308
86.5%
Common 48
 
13.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
90
29.2%
7
 
2.3%
7
 
2.3%
7
 
2.3%
7
 
2.3%
6
 
1.9%
6
 
1.9%
5
 
1.6%
5
 
1.6%
5
 
1.6%
Other values (91) 163
52.9%
Common
ValueCountFrequency (%)
2 14
29.2%
3 11
22.9%
1 9
18.8%
. 9
18.8%
4 4
 
8.3%
6 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 308
86.5%
ASCII 48
 
13.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
90
29.2%
7
 
2.3%
7
 
2.3%
7
 
2.3%
7
 
2.3%
6
 
1.9%
6
 
1.9%
5
 
1.6%
5
 
1.6%
5
 
1.6%
Other values (91) 163
52.9%
ASCII
ValueCountFrequency (%)
2 14
29.2%
3 11
22.9%
1 9
18.8%
. 9
18.8%
4 4
 
8.3%
6 1
 
2.1%

rdnmaddr_cd
Real number (ℝ)

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3311565 × 1011
Minimum1.1110201 × 1011
Maximum5.0130485 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:16.860517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110201 × 1011
5-th percentile1.111031 × 1011
Q11.1290328 × 1011
median2.636536 × 1011
Q32.9159125 × 1011
95-th percentile4.1830445 × 1011
Maximum5.0130485 × 1011
Range3.9020285 × 1011
Interquartile range (IQR)1.7868798 × 1011

Descriptive statistics

Standard deviation1.2154597 × 1011
Coefficient of variation (CV)0.52139774
Kurtosis-1.030227
Mean2.3311565 × 1011
Median Absolute Deviation (MAD)1.474516 × 1011
Skewness0.44592365
Sum2.3311565 × 1013
Variance1.4773423 × 1022
MonotonicityNot monotonic
2023-12-10T18:39:17.143594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
116502000003 3
 
3.0%
113203000004 2
 
2.0%
291104277206 2
 
2.0%
117103123023 2
 
2.0%
116202000003 2
 
2.0%
111102005001 2
 
2.0%
301702166001 2
 
2.0%
291103159010 2
 
2.0%
291703162082 1
 
1.0%
291104277145 1
 
1.0%
Other values (81) 81
81.0%
ValueCountFrequency (%)
111102005001 2
2.0%
111103005004 1
1.0%
111103100007 1
1.0%
111103100009 1
1.0%
111103100010 1
1.0%
111103100013 1
1.0%
111104100010 1
1.0%
111104100075 1
1.0%
111104100205 1
1.0%
111104100236 1
1.0%
ValueCountFrequency (%)
501304850416 1
1.0%
501303349236 1
1.0%
501103349123 1
1.0%
431143236027 1
1.0%
418304451442 1
1.0%
418304451226 1
1.0%
418203216053 1
1.0%
416704442277 1
1.0%
416303212007 1
1.0%
415703209064 1
1.0%
Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:17.671731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length22
Mean length15.91
Min length11

Characters and Unicode

Total characters1591
Distinct characters172
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row경기 과천시 광명로 313
2nd row제주특별자치도 서귀포시 안덕면 일주서로 1836
3rd row서울 중구 세종대로 99
4th row충북 청주시 청원구 상당로 314
5th row서울 강서구 양천로47길 36
ValueCountFrequency (%)
서울 45
 
10.8%
종로구 18
 
4.3%
경기 15
 
3.6%
광주 14
 
3.3%
부산 8
 
1.9%
동구 8
 
1.9%
남구 6
 
1.4%
용산구 5
 
1.2%
대전 5
 
1.2%
인천 4
 
1.0%
Other values (233) 290
69.4%
2023-12-10T18:39:18.502164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
318
20.0%
102
 
6.4%
90
 
5.7%
62
 
3.9%
1 57
 
3.6%
45
 
2.8%
2 39
 
2.5%
37
 
2.3%
0 36
 
2.3%
3 32
 
2.0%
Other values (162) 773
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 943
59.3%
Space Separator 318
 
20.0%
Decimal Number 314
 
19.7%
Dash Punctuation 11
 
0.7%
Uppercase Letter 4
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
102
 
10.8%
90
 
9.5%
62
 
6.6%
45
 
4.8%
37
 
3.9%
27
 
2.9%
23
 
2.4%
22
 
2.3%
22
 
2.3%
18
 
1.9%
Other values (145) 495
52.5%
Decimal Number
ValueCountFrequency (%)
1 57
18.2%
2 39
12.4%
0 36
11.5%
3 32
10.2%
5 31
9.9%
4 29
9.2%
6 26
8.3%
8 24
7.6%
7 21
 
6.7%
9 19
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
E 1
25.0%
P 1
25.0%
A 1
25.0%
Space Separator
ValueCountFrequency (%)
318
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 943
59.3%
Common 644
40.5%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
102
 
10.8%
90
 
9.5%
62
 
6.6%
45
 
4.8%
37
 
3.9%
27
 
2.9%
23
 
2.4%
22
 
2.3%
22
 
2.3%
18
 
1.9%
Other values (145) 495
52.5%
Common
ValueCountFrequency (%)
318
49.4%
1 57
 
8.9%
2 39
 
6.1%
0 36
 
5.6%
3 32
 
5.0%
5 31
 
4.8%
4 29
 
4.5%
6 26
 
4.0%
8 24
 
3.7%
7 21
 
3.3%
Other values (3) 31
 
4.8%
Latin
ValueCountFrequency (%)
C 1
25.0%
E 1
25.0%
P 1
25.0%
A 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 943
59.3%
ASCII 648
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
318
49.1%
1 57
 
8.8%
2 39
 
6.0%
0 36
 
5.6%
3 32
 
4.9%
5 31
 
4.8%
4 29
 
4.5%
6 26
 
4.0%
8 24
 
3.7%
7 21
 
3.2%
Other values (7) 35
 
5.4%
Hangul
ValueCountFrequency (%)
102
 
10.8%
90
 
9.5%
62
 
6.6%
45
 
4.8%
37
 
3.9%
27
 
2.9%
23
 
2.4%
22
 
2.3%
22
 
2.3%
18
 
1.9%
Other values (145) 495
52.5%

zip_cd
Real number (ℝ)

Distinct94
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23334.38
Minimum1811
Maximum63641
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:19.085365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1811
5-th percentile3021.9
Q14410.75
median12542
Q343563.25
95-th percentile61641.15
Maximum63641
Range61830
Interquartile range (IQR)39152.5

Descriptive statistics

Standard deviation22408.3
Coefficient of variation (CV)0.96031264
Kurtosis-1.0847559
Mean23334.38
Median Absolute Deviation (MAD)9482
Skewness0.7385039
Sum2333438
Variance5.0213191 × 108
MonotonicityNot monotonic
2023-12-10T18:39:19.355697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
61493 3
 
3.0%
3004 2
 
2.0%
35204 2
 
2.0%
6757 2
 
2.0%
3062 2
 
2.0%
13829 1
 
1.0%
61494 1
 
1.0%
61496 1
 
1.0%
61663 1
 
1.0%
61640 1
 
1.0%
Other values (84) 84
84.0%
ValueCountFrequency (%)
1811 1
1.0%
1878 1
1.0%
3004 2
2.0%
3020 1
1.0%
3022 1
1.0%
3034 1
1.0%
3044 1
1.0%
3051 1
1.0%
3058 1
1.0%
3062 2
2.0%
ValueCountFrequency (%)
63641 1
 
1.0%
63527 1
 
1.0%
63332 1
 
1.0%
61743 1
 
1.0%
61663 1
 
1.0%
61640 1
 
1.0%
61637 1
 
1.0%
61496 1
 
1.0%
61494 1
 
1.0%
61493 3
3.0%
Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:19.845197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters800
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)96.0%

Sample

1st row다사575369
2nd row나나903746
3rd row다사536519
4th row다바993509
5th row다사415527
ValueCountFrequency (%)
다라502822 2
 
2.0%
다사570424 2
 
2.0%
다라467843 1
 
1.0%
다사126698 1
 
1.0%
다사575369 1
 
1.0%
다라492819 1
 
1.0%
다라486820 1
 
1.0%
다라467825 1
 
1.0%
다라465829 1
 
1.0%
다라490872 1
 
1.0%
Other values (88) 88
88.0%
2023-12-10T18:39:20.493493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 101
12.6%
86
10.8%
4 82
10.2%
65
8.1%
3 64
8.0%
2 63
7.9%
8 58
7.2%
6 55
6.9%
9 48
 
6.0%
0 46
 
5.8%
Other values (6) 132
16.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 600
75.0%
Other Letter 200
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 101
16.8%
4 82
13.7%
3 64
10.7%
2 63
10.5%
8 58
9.7%
6 55
9.2%
9 48
8.0%
0 46
7.7%
7 45
7.5%
1 38
 
6.3%
Other Letter
ValueCountFrequency (%)
86
43.0%
65
32.5%
26
 
13.0%
14
 
7.0%
6
 
3.0%
3
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 600
75.0%
Hangul 200
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 101
16.8%
4 82
13.7%
3 64
10.7%
2 63
10.5%
8 58
9.7%
6 55
9.2%
9 48
8.0%
0 46
7.7%
7 45
7.5%
1 38
 
6.3%
Hangul
ValueCountFrequency (%)
86
43.0%
65
32.5%
26
 
13.0%
14
 
7.0%
6
 
3.0%
3
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 600
75.0%
Hangul 200
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 101
16.8%
4 82
13.7%
3 64
10.7%
2 63
10.5%
8 58
9.7%
6 55
9.2%
9 48
8.0%
0 46
7.7%
7 45
7.5%
1 38
 
6.3%
Hangul
ValueCountFrequency (%)
86
43.0%
65
32.5%
26
 
13.0%
14
 
7.0%
6
 
3.0%
3
 
1.5%

x_cd
Real number (ℝ)

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.74583
Minimum33.257451
Maximum37.766283
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:20.728535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.257451
5-th percentile35.108833
Q135.683375
median37.478147
Q337.571942
95-th percentile37.634446
Maximum37.766283
Range4.5088317
Interquartile range (IQR)1.8885666

Descriptive statistics

Standard deviation1.1622808
Coefficient of variation (CV)0.031630277
Kurtosis0.11596528
Mean36.74583
Median Absolute Deviation (MAD)0.142986
Skewness-1.1268263
Sum3674.583
Variance1.3508966
MonotonicityNot monotonic
2023-12-10T18:39:20.914345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4802402 2
 
2.0%
37.4310034 1
 
1.0%
37.7662826 1
 
1.0%
35.1437838 1
 
1.0%
35.134182 1
 
1.0%
35.1342979 1
 
1.0%
35.1318924 1
 
1.0%
35.1369073 1
 
1.0%
35.1405537 1
 
1.0%
35.1795643 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
33.2574509 1
1.0%
33.4396448 1
1.0%
33.5437575 1
1.0%
35.103741 1
1.0%
35.1059037 1
1.0%
35.1089872 1
1.0%
35.1093319 1
1.0%
35.1293706 1
1.0%
35.1318076 1
1.0%
35.1318924 1
1.0%
ValueCountFrequency (%)
37.7662826 1
1.0%
37.7328163 1
1.0%
37.723755 1
1.0%
37.6614856 1
1.0%
37.6604165 1
1.0%
37.6330789 1
1.0%
37.6303439 1
1.0%
37.6301286 1
1.0%
37.6121371 1
1.0%
37.6121218 1
1.0%

y_cd
Real number (ℝ)

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.22904
Minimum126.32252
Maximum129.14121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:21.146484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.32252
5-th percentile126.61945
Q1126.94238
median126.98198
Q3127.11435
95-th percentile129.03826
Maximum129.14121
Range2.8186933
Interquartile range (IQR)0.17196255

Descriptive statistics

Standard deviation0.66535243
Coefficient of variation (CV)0.0052295644
Kurtosis2.8386998
Mean127.22904
Median Absolute Deviation (MAD)0.0701416
Skewness1.9659219
Sum12722.904
Variance0.44269386
MonotonicityNot monotonic
2023-12-10T18:39:21.350413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0142152 2
 
2.0%
127.0199299 1
 
1.0%
126.4587597 1
 
1.0%
126.9070168 1
 
1.0%
126.9537242 1
 
1.0%
126.9534815 1
 
1.0%
126.9365211 1
 
1.0%
126.9156646 1
 
1.0%
126.9129673 1
 
1.0%
126.9404082 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
126.3225174 1
1.0%
126.4587597 1
1.0%
126.5084261 1
1.0%
126.5088507 1
1.0%
126.5977739 1
1.0%
126.6205946 1
1.0%
126.6422184 1
1.0%
126.6531786 1
1.0%
126.7744583 1
1.0%
126.8099898 1
1.0%
ValueCountFrequency (%)
129.1412107 1
1.0%
129.1370273 1
1.0%
129.100099 1
1.0%
129.0767727 1
1.0%
129.0542017 1
1.0%
129.0374232 1
1.0%
129.0194146 1
1.0%
128.9426936 1
1.0%
128.6743408 1
1.0%
128.6143223 1
1.0%

sdiv
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
사립
58 
공립
28 
대학
11 
국립
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국립
2nd row사립
3rd row국립
4th row국립
5th row공립

Common Values

ValueCountFrequency (%)
사립 58
58.0%
공립 28
28.0%
대학 11
 
11.0%
국립 3
 
3.0%

Length

2023-12-10T18:39:21.674421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:21.816479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 58
58.0%
공립 28
28.0%
대학 11
 
11.0%
국립 3
 
3.0%

regist_yn
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
등록
96 
미등록
 
4

Length

Max length3
Median length2
Mean length2.04
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row등록
2nd row등록
3rd row등록
4th row미등록
5th row등록

Common Values

ValueCountFrequency (%)
등록 96
96.0%
미등록 4
 
4.0%

Length

2023-12-10T18:39:22.018416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:22.409206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록 96
96.0%
미등록 4
 
4.0%

cttpc
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:22.742726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length11.79
Min length9

Characters and Unicode

Total characters1179
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row02-2188-6114
2nd row010-8875-8174
3rd row02-2022-0600
4th row043-261-1400
5th row02-2659-2206
ValueCountFrequency (%)
02-580-1300 2
 
2.0%
062-224-6601 1
 
1.0%
032-933-9297 1
 
1.0%
062-223-6677 1
 
1.0%
062-223-6515 1
 
1.0%
062-232-7335 1
 
1.0%
062-674-8515 1
 
1.0%
062-607-2315 1
 
1.0%
062-269-9883 1
 
1.0%
062-613-7113 1
 
1.0%
Other values (89) 89
89.0%
2023-12-10T18:39:23.429507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 209
17.7%
- 198
16.8%
2 159
13.5%
1 98
8.3%
3 89
7.5%
7 88
7.5%
6 86
7.3%
5 69
 
5.9%
4 68
 
5.8%
8 64
 
5.4%
Other values (4) 51
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 977
82.9%
Dash Punctuation 198
 
16.8%
Math Symbol 2
 
0.2%
Other Punctuation 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 209
21.4%
2 159
16.3%
1 98
10.0%
3 89
9.1%
7 88
9.0%
6 86
8.8%
5 69
 
7.1%
4 68
 
7.0%
8 64
 
6.6%
9 47
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
/ 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 198
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1179
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 209
17.7%
- 198
16.8%
2 159
13.5%
1 98
8.3%
3 89
7.5%
7 88
7.5%
6 86
7.3%
5 69
 
5.9%
4 68
 
5.8%
8 64
 
5.4%
Other values (4) 51
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1179
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 209
17.7%
- 198
16.8%
2 159
13.5%
1 98
8.3%
3 89
7.5%
7 88
7.5%
6 86
7.3%
5 69
 
5.9%
4 68
 
5.8%
8 64
 
5.4%
Other values (4) 51
 
4.3%
Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:23.802876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length10
Mean length10.55
Min length8

Characters and Unicode

Total characters1055
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row1986.08.25.
2nd row1987.10.01.
3rd row1998.12.01.
4th row2018.12.27
5th row2009.04.23.
ValueCountFrequency (%)
1995.08.06 2
 
2.0%
1992.10.31 1
 
1.0%
1999.09.01 1
 
1.0%
2007.07.26 1
 
1.0%
2018.05.01 1
 
1.0%
2008.07.21 1
 
1.0%
2018.02.09 1
 
1.0%
2012.12.27 1
 
1.0%
2015.06.04 1
 
1.0%
1992.08.01 1
 
1.0%
Other values (90) 90
89.1%
2023-12-10T18:39:24.600271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 238
22.6%
0 224
21.2%
1 182
17.3%
2 123
11.7%
9 79
 
7.5%
8 42
 
4.0%
6 32
 
3.0%
7 32
 
3.0%
5 30
 
2.8%
3 28
 
2.7%
Other values (18) 45
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 796
75.5%
Other Punctuation 239
 
22.7%
Other Letter 15
 
1.4%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
13.3%
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (3) 3
20.0%
Decimal Number
ValueCountFrequency (%)
0 224
28.1%
1 182
22.9%
2 123
15.5%
9 79
 
9.9%
8 42
 
5.3%
6 32
 
4.0%
7 32
 
4.0%
5 30
 
3.8%
3 28
 
3.5%
4 24
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 238
99.6%
, 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1040
98.6%
Hangul 15
 
1.4%

Most frequent character per script

Common
ValueCountFrequency (%)
. 238
22.9%
0 224
21.5%
1 182
17.5%
2 123
11.8%
9 79
 
7.6%
8 42
 
4.0%
6 32
 
3.1%
7 32
 
3.1%
5 30
 
2.9%
3 28
 
2.7%
Other values (5) 30
 
2.9%
Hangul
ValueCountFrequency (%)
2
13.3%
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (3) 3
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1040
98.6%
Hangul 15
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 238
22.9%
0 224
21.5%
1 182
17.5%
2 123
11.8%
9 79
 
7.6%
8 42
 
4.0%
6 32
 
3.1%
7 32
 
3.1%
5 30
 
2.9%
3 28
 
2.7%
Other values (5) 30
 
2.9%
Hangul
ValueCountFrequency (%)
2
13.3%
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (3) 3
20.0%

regist_stts
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
96 
False
 
4
ValueCountFrequency (%)
True 96
96.0%
False 4
 
4.0%
2023-12-10T18:39:24.832178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Distinct93
Distinct (%)93.9%
Missing1
Missing (%)1.0%
Memory size932.0 B
2023-12-10T18:39:25.186819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length10
Mean length10.242424
Min length3

Characters and Unicode

Total characters1014
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)89.9%

Sample

1st row2017.12.14.
2nd row2007.08.30.
3rd row2017.12.14.
4th row미등록
5th row2014.02.14.
ValueCountFrequency (%)
미등록 4
 
4.0%
2017.12.14 2
 
2.0%
2002.05.20 2
 
2.0%
2005.03.11 2
 
2.0%
1996.11.22 2
 
2.0%
2018.05.30 2
 
2.0%
2018.07.02 1
 
1.0%
2015.03.25 1
 
1.0%
1993.02.11 1
 
1.0%
2001.04.13 1
 
1.0%
Other values (83) 83
82.2%
2023-12-10T18:39:25.872635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 229
22.6%
0 200
19.7%
1 170
16.8%
2 159
15.7%
9 61
 
6.0%
7 35
 
3.5%
3 33
 
3.3%
5 29
 
2.9%
6 29
 
2.9%
8 26
 
2.6%
Other values (13) 43
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 759
74.9%
Other Punctuation 230
 
22.7%
Other Letter 22
 
2.2%
Space Separator 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 200
26.4%
1 170
22.4%
2 159
20.9%
9 61
 
8.0%
7 35
 
4.6%
3 33
 
4.3%
5 29
 
3.8%
6 29
 
3.8%
8 26
 
3.4%
4 17
 
2.2%
Other Letter
ValueCountFrequency (%)
6
27.3%
6
27.3%
4
18.2%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 229
99.6%
, 1
 
0.4%
Space Separator
ValueCountFrequency (%)
2
66.7%
  1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 992
97.8%
Hangul 22
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 229
23.1%
0 200
20.2%
1 170
17.1%
2 159
16.0%
9 61
 
6.1%
7 35
 
3.5%
3 33
 
3.3%
5 29
 
2.9%
6 29
 
2.9%
8 26
 
2.6%
Other values (4) 21
 
2.1%
Hangul
ValueCountFrequency (%)
6
27.3%
6
27.3%
4
18.2%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 991
97.7%
Hangul 22
 
2.2%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 229
23.1%
0 200
20.2%
1 170
17.2%
2 159
16.0%
9 61
 
6.2%
7 35
 
3.5%
3 33
 
3.3%
5 29
 
2.9%
6 29
 
2.9%
8 26
 
2.6%
Other values (3) 20
 
2.0%
Hangul
ValueCountFrequency (%)
6
27.3%
6
27.3%
4
18.2%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
None
ValueCountFrequency (%)
  1
100.0%
Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:26.214508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length15.41
Min length3

Characters and Unicode

Total characters1541
Distinct characters34
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)94.0%

Sample

1st row국립13-2017-07호
2nd row제주-사립13-2007-10호
3rd row국립13-2017-09호
4th row미등록
5th row서울-공립13-2014-03호
ValueCountFrequency (%)
미등록 4
 
4.0%
서울-사립13-1996-03호 2
 
2.0%
국립13-2017-07호 1
 
1.0%
인천-사립13-1996-01호 1
 
1.0%
광주-사립13-2017-02호 1
 
1.0%
광주-사립13-2007-01호 1
 
1.0%
광주-사립13-2018-01호 1
 
1.0%
광주-사립13-2008-01호 1
 
1.0%
광주-공립13-2018-02호 1
 
1.0%
광주-공립13-2015-01호 1
 
1.0%
Other values (86) 86
86.0%
2023-12-10T18:39:27.179252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 286
18.6%
1 208
13.5%
0 201
13.0%
2 116
 
7.5%
3 100
 
6.5%
96
 
6.2%
85
 
5.5%
57
 
3.7%
9 51
 
3.3%
43
 
2.8%
Other values (24) 298
19.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 767
49.8%
Other Letter 488
31.7%
Dash Punctuation 286
 
18.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
96
19.7%
85
17.4%
57
11.7%
43
8.8%
43
8.8%
26
 
5.3%
20
 
4.1%
15
 
3.1%
14
 
2.9%
14
 
2.9%
Other values (13) 75
15.4%
Decimal Number
ValueCountFrequency (%)
1 208
27.1%
0 201
26.2%
2 116
15.1%
3 100
13.0%
9 51
 
6.6%
7 24
 
3.1%
8 19
 
2.5%
5 18
 
2.3%
6 17
 
2.2%
4 13
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 286
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1053
68.3%
Hangul 488
31.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
96
19.7%
85
17.4%
57
11.7%
43
8.8%
43
8.8%
26
 
5.3%
20
 
4.1%
15
 
3.1%
14
 
2.9%
14
 
2.9%
Other values (13) 75
15.4%
Common
ValueCountFrequency (%)
- 286
27.2%
1 208
19.8%
0 201
19.1%
2 116
11.0%
3 100
 
9.5%
9 51
 
4.8%
7 24
 
2.3%
8 19
 
1.8%
5 18
 
1.7%
6 17
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1053
68.3%
Hangul 488
31.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 286
27.2%
1 208
19.8%
0 201
19.1%
2 116
11.0%
3 100
 
9.5%
9 51
 
4.8%
7 24
 
2.3%
8 19
 
1.8%
5 18
 
1.7%
6 17
 
1.6%
Hangul
ValueCountFrequency (%)
96
19.7%
85
17.4%
57
11.7%
43
8.8%
43
8.8%
26
 
5.3%
20
 
4.1%
15
 
3.1%
14
 
2.9%
14
 
2.9%
Other values (13) 75
15.4%

osvc_addr
Text

MISSING 

Distinct89
Distinct (%)95.7%
Missing7
Missing (%)7.0%
Memory size932.0 B
2023-12-10T18:39:27.795395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length146
Median length36
Mean length27.591398
Min length13

Characters and Unicode

Total characters2566
Distinct characters57
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)91.4%

Sample

1st rowwww.mmca.go.kr, ,www.facebook.com/MMCAKorea, www.instagram.com/MMCAKorea, ,www.twitter.com/MMCAKOREA, www.youtube.com/MMCAKorea, tv.naver.com/mmca
2nd rowwww.jejuartpark.com
3rd rowwww.mmca.go.kr, www.facebook.com/MMCAKorea, ,www.instagram.com/MMCAKorea, www.twitter.com/MMCAKOREA,, www.youtube.com/MMCAKorea, tv.naver.com/mmca
4th rowwww.mmca.go.kr, www.facebook.com/MMCAKorea, ,www.instagram.com/MMCAKorea, www.twitter.com/MMCAKOREA,, www.youtube.com/MMCAKorea, tv.naver.com/mmca
5th rowwww.gjjs.or.kr
ValueCountFrequency (%)
www.mmca.go.kr 3
 
2.8%
www.instagram.com/mmcakorea 3
 
2.8%
www.twitter.com/mmcakorea 3
 
2.8%
www.youtube.com/mmcakorea 3
 
2.8%
tv.naver.com/mmca 3
 
2.8%
www.facebook.com/mmcakorea 3
 
2.8%
http://sema.seoul.go.kr 2
 
1.9%
www.sac.or.kr 2
 
1.9%
http://www.daelimmuseum.org/index.do 2
 
1.9%
http://artmuse.gwangju.go.kr 1
 
0.9%
Other values (83) 83
76.9%
2023-12-10T18:39:28.442462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 273
 
10.6%
w 255
 
9.9%
o 180
 
7.0%
m 172
 
6.7%
r 143
 
5.6%
/ 142
 
5.5%
a 134
 
5.2%
t 134
 
5.2%
u 120
 
4.7%
e 119
 
4.6%
Other values (47) 894
34.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1953
76.1%
Other Punctuation 480
 
18.7%
Uppercase Letter 82
 
3.2%
Decimal Number 24
 
0.9%
Space Separator 15
 
0.6%
Other Letter 7
 
0.3%
Connector Punctuation 3
 
0.1%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 255
13.1%
o 180
 
9.2%
m 172
 
8.8%
r 143
 
7.3%
a 134
 
6.9%
t 134
 
6.9%
u 120
 
6.1%
e 119
 
6.1%
c 101
 
5.2%
s 92
 
4.7%
Other values (15) 503
25.8%
Uppercase Letter
ValueCountFrequency (%)
M 24
29.3%
A 16
19.5%
K 13
15.9%
C 13
15.9%
R 5
 
6.1%
O 4
 
4.9%
E 3
 
3.7%
W 3
 
3.7%
T 1
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 7
29.2%
0 4
16.7%
3 3
12.5%
2 3
12.5%
8 2
 
8.3%
5 2
 
8.3%
6 1
 
4.2%
4 1
 
4.2%
7 1
 
4.2%
Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 273
56.9%
/ 142
29.6%
: 39
 
8.1%
, 26
 
5.4%
Space Separator
ValueCountFrequency (%)
15
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2035
79.3%
Common 524
 
20.4%
Hangul 7
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 255
12.5%
o 180
 
8.8%
m 172
 
8.5%
r 143
 
7.0%
a 134
 
6.6%
t 134
 
6.6%
u 120
 
5.9%
e 119
 
5.8%
c 101
 
5.0%
s 92
 
4.5%
Other values (24) 585
28.7%
Common
ValueCountFrequency (%)
. 273
52.1%
/ 142
27.1%
: 39
 
7.4%
, 26
 
5.0%
15
 
2.9%
1 7
 
1.3%
0 4
 
0.8%
3 3
 
0.6%
_ 3
 
0.6%
2 3
 
0.6%
Other values (6) 9
 
1.7%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2559
99.7%
Hangul 7
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 273
 
10.7%
w 255
 
10.0%
o 180
 
7.0%
m 172
 
6.7%
r 143
 
5.6%
/ 142
 
5.5%
a 134
 
5.2%
t 134
 
5.2%
u 120
 
4.7%
e 119
 
4.7%
Other values (40) 887
34.7%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

osvc_av_gud_prvd_yn
Boolean

MISSING 

Distinct2
Distinct (%)2.1%
Missing6
Missing (%)6.0%
Memory size332.0 B
False
77 
True
17 
(Missing)
 
6
ValueCountFrequency (%)
False 77
77.0%
True 17
 
17.0%
(Missing) 6
 
6.0%
2023-12-10T18:39:28.687804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

osvc_av_gud_fee
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
83 
무료
13 
1000
 
3
O
 
1

Length

Max length4
Median length4
Mean length3.71
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row1000
2nd row<NA>
3rd row1000
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 83
83.0%
무료 13
 
13.0%
1000 3
 
3.0%
O 1
 
1.0%

Length

2023-12-10T18:39:28.856588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:29.054199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 83
83.0%
무료 13
 
13.0%
1000 3
 
3.0%
o 1
 
1.0%

osvc_mssys_prvd_yn
Boolean

MISSING 

Distinct2
Distinct (%)2.1%
Missing6
Missing (%)6.0%
Memory size332.0 B
False
72 
True
22 
(Missing)
 
6
ValueCountFrequency (%)
False 72
72.0%
True 22
 
22.0%
(Missing) 6
 
6.0%
2023-12-10T18:39:29.223406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

plot_aea
Text

MISSING 

Distinct98
Distinct (%)100.0%
Missing2
Missing (%)2.0%
Memory size932.0 B
2023-12-10T18:39:29.643715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.4081633
Min length3

Characters and Unicode

Total characters432
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)100.0%

Sample

1st row66916
2nd row412286
3rd row1181
4th row12077
5th row3561
ValueCountFrequency (%)
4815 1
 
1.0%
441 1
 
1.0%
1388.42 1
 
1.0%
1405 1
 
1.0%
248 1
 
1.0%
373 1
 
1.0%
158 1
 
1.0%
8898 1
 
1.0%
143293 1
 
1.0%
2980 1
 
1.0%
Other values (88) 88
89.8%
2023-12-10T18:39:30.300179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 62
14.4%
2 49
11.3%
4 47
10.9%
9 41
9.5%
0 40
9.3%
8 38
8.8%
6 38
8.8%
5 36
8.3%
7 30
6.9%
3 30
6.9%
Other values (6) 21
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 411
95.1%
Other Punctuation 16
 
3.7%
Other Letter 5
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 62
15.1%
2 49
11.9%
4 47
11.4%
9 41
10.0%
0 40
9.7%
8 38
9.2%
6 38
9.2%
5 36
8.8%
7 30
7.3%
3 30
7.3%
Other Letter
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 427
98.8%
Hangul 5
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 62
14.5%
2 49
11.5%
4 47
11.0%
9 41
9.6%
0 40
9.4%
8 38
8.9%
6 38
8.9%
5 36
8.4%
7 30
7.0%
3 30
7.0%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 427
98.8%
Hangul 5
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 62
14.5%
2 49
11.5%
4 47
11.0%
9 41
9.6%
0 40
9.4%
8 38
8.9%
6 38
8.9%
5 36
8.4%
7 30
7.0%
3 30
7.0%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

buld_totar
Text

MISSING 

Distinct96
Distinct (%)100.0%
Missing4
Missing (%)4.0%
Memory size932.0 B
2023-12-10T18:39:30.818474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.40625
Min length3

Characters and Unicode

Total characters423
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)100.0%

Sample

1st row37796.8
2nd row1688.12
3rd row3428
4th row19865
5th row3305
ValueCountFrequency (%)
22826 1
 
1.0%
3428 1
 
1.0%
604.95 1
 
1.0%
769 1
 
1.0%
569 1
 
1.0%
489.4 1
 
1.0%
318 1
 
1.0%
945 1
 
1.0%
13330 1
 
1.0%
1986 1
 
1.0%
Other values (86) 86
89.6%
2023-12-10T18:39:31.632462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 70
16.5%
3 47
11.1%
8 42
9.9%
5 40
9.5%
2 38
9.0%
6 37
8.7%
0 35
8.3%
4 33
7.8%
9 30
7.1%
7 29
6.9%
Other values (6) 22
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 401
94.8%
Other Punctuation 17
 
4.0%
Other Letter 5
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 70
17.5%
3 47
11.7%
8 42
10.5%
5 40
10.0%
2 38
9.5%
6 37
9.2%
0 35
8.7%
4 33
8.2%
9 30
7.5%
7 29
7.2%
Other Letter
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 418
98.8%
Hangul 5
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 70
16.7%
3 47
11.2%
8 42
10.0%
5 40
9.6%
2 38
9.1%
6 37
8.9%
0 35
8.4%
4 33
7.9%
9 30
7.2%
7 29
6.9%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 418
98.8%
Hangul 5
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 70
16.7%
3 47
11.2%
8 42
10.0%
5 40
9.6%
2 38
9.1%
6 37
8.9%
0 35
8.4%
4 33
7.9%
9 30
7.2%
7 29
6.9%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

ehbll_aea
Real number (ℝ)

MISSING  ZEROS 

Distinct92
Distinct (%)93.9%
Missing2
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean1330.6429
Minimum0
Maximum13941
Zeros3
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:31.942972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile113.35
Q1355.75
median639
Q31439
95-th percentile4430.95
Maximum13941
Range13941
Interquartile range (IQR)1083.25

Descriptive statistics

Standard deviation1910.9334
Coefficient of variation (CV)1.4360979
Kurtosis20.131177
Mean1330.6429
Median Absolute Deviation (MAD)424.5
Skewness3.838606
Sum130403
Variance3651666.5
MonotonicityNot monotonic
2023-12-10T18:39:32.310209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
3.0%
330 2
 
2.0%
561 2
 
2.0%
398 2
 
2.0%
606 2
 
2.0%
664 1
 
1.0%
460 1
 
1.0%
242 1
 
1.0%
200 1
 
1.0%
318 1
 
1.0%
Other values (82) 82
82.0%
(Missing) 2
 
2.0%
ValueCountFrequency (%)
0 3
3.0%
83 1
 
1.0%
104 1
 
1.0%
115 1
 
1.0%
121 1
 
1.0%
159 1
 
1.0%
160 1
 
1.0%
165 1
 
1.0%
191 1
 
1.0%
200 1
 
1.0%
ValueCountFrequency (%)
13941 1
1.0%
7565 1
1.0%
5911 1
1.0%
5787 1
1.0%
5649 1
1.0%
4216 1
1.0%
3930 1
1.0%
3511 1
1.0%
3448 1
1.0%
3256 1
1.0%

shlf_aea
Real number (ℝ)

MISSING 

Distinct83
Distinct (%)88.3%
Missing6
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean365.20545
Minimum3
Maximum7361
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:32.580804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile15.702
Q150
median106.87
Q3226.5
95-th percentile1504.95
Maximum7361
Range7358
Interquartile range (IQR)176.5

Descriptive statistics

Standard deviation939.69219
Coefficient of variation (CV)2.5730509
Kurtosis35.494416
Mean365.20545
Median Absolute Deviation (MAD)65.87
Skewness5.5037597
Sum34329.312
Variance883021.42
MonotonicityNot monotonic
2023-12-10T18:39:32.776998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80.0 3
 
3.0%
50.0 3
 
3.0%
132.0 2
 
2.0%
106.0 2
 
2.0%
225.0 2
 
2.0%
42.0 2
 
2.0%
99.0 2
 
2.0%
127.0 2
 
2.0%
41.0 2
 
2.0%
463.32 1
 
1.0%
Other values (73) 73
73.0%
(Missing) 6
 
6.0%
ValueCountFrequency (%)
3.0 1
1.0%
10.8 1
1.0%
11.0 1
1.0%
13.0 1
1.0%
15.0 1
1.0%
16.08 1
1.0%
17.0 1
1.0%
20.0 1
1.0%
22.0 1
1.0%
25.0 1
1.0%
ValueCountFrequency (%)
7361.0 1
1.0%
3899.0 1
1.0%
3067.0 1
1.0%
2312.0 1
1.0%
1685.0 1
1.0%
1408.0 1
1.0%
870.0 1
1.0%
790.0 1
1.0%
753.66 1
1.0%
726.0 1
1.0%

edu_plce_aea
Text

MISSING 

Distinct61
Distinct (%)93.8%
Missing35
Missing (%)35.0%
Memory size932.0 B
2023-12-10T18:39:33.129725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters195
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)89.2%

Sample

1st row1286
2nd row78
3rd row295
4th row343
5th row157
ValueCountFrequency (%)
70 3
 
4.6%
100 2
 
3.1%
78 2
 
3.1%
332 1
 
1.5%
80 1
 
1.5%
129 1
 
1.5%
192 1
 
1.5%
37 1
 
1.5%
680 1
 
1.5%
213 1
 
1.5%
Other values (51) 51
78.5%
2023-12-10T18:39:33.749749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 30
15.4%
2 24
12.3%
0 20
10.3%
8 17
8.7%
5 17
8.7%
7 16
8.2%
4 16
8.2%
9 15
7.7%
6 15
7.7%
3 12
 
6.2%
Other values (6) 13
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 182
93.3%
Other Punctuation 8
 
4.1%
Other Letter 5
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 30
16.5%
2 24
13.2%
0 20
11.0%
8 17
9.3%
5 17
9.3%
7 16
8.8%
4 16
8.8%
9 15
8.2%
6 15
8.2%
3 12
 
6.6%
Other Letter
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 190
97.4%
Hangul 5
 
2.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 30
15.8%
2 24
12.6%
0 20
10.5%
8 17
8.9%
5 17
8.9%
7 16
8.4%
4 16
8.4%
9 15
7.9%
6 15
7.9%
3 12
 
6.3%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 190
97.4%
Hangul 5
 
2.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 30
15.8%
2 24
12.6%
0 20
10.5%
8 17
8.9%
5 17
8.9%
7 16
8.4%
4 16
8.4%
9 15
7.9%
6 15
7.9%
3 12
 
6.3%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

ofce_aea
Real number (ℝ)

MISSING 

Distinct77
Distinct (%)82.8%
Missing7
Missing (%)7.0%
Infinite0
Infinite (%)0.0%
Mean440.93032
Minimum3
Maximum20213
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:34.074874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile11.2
Q130
median74
Q3170
95-th percentile816.03
Maximum20213
Range20210
Interquartile range (IQR)140

Descriptive statistics

Standard deviation2158.0679
Coefficient of variation (CV)4.8943513
Kurtosis78.848873
Mean440.93032
Median Absolute Deviation (MAD)58
Skewness8.6472175
Sum41006.52
Variance4657257.1
MonotonicityNot monotonic
2023-12-10T18:39:34.288910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60.0 4
 
4.0%
16.0 3
 
3.0%
145.0 2
 
2.0%
64.0 2
 
2.0%
18.0 2
 
2.0%
39.0 2
 
2.0%
9.0 2
 
2.0%
66.0 2
 
2.0%
85.0 2
 
2.0%
149.0 2
 
2.0%
Other values (67) 70
70.0%
(Missing) 7
 
7.0%
ValueCountFrequency (%)
3.0 1
 
1.0%
5.0 1
 
1.0%
9.0 2
2.0%
10.0 1
 
1.0%
12.0 1
 
1.0%
12.53 1
 
1.0%
13.0 2
2.0%
14.0 1
 
1.0%
15.0 1
 
1.0%
16.0 3
3.0%
ValueCountFrequency (%)
20213.0 1
1.0%
4530.0 1
1.0%
3533.0 1
1.0%
976.0 1
1.0%
888.0 1
1.0%
768.05 1
1.0%
652.0 1
1.0%
639.0 1
1.0%
476.0 1
1.0%
457.0 1
1.0%

data_lbr_booth_aea
Real number (ℝ)

MISSING 

Distinct49
Distinct (%)90.7%
Missing46
Missing (%)46.0%
Infinite0
Infinite (%)0.0%
Mean112.07315
Minimum10
Maximum1172
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:34.523599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile11.65
Q130.25
median52.5
Q3114.5
95-th percentile313.95
Maximum1172
Range1162
Interquartile range (IQR)84.25

Descriptive statistics

Standard deviation177.64694
Coefficient of variation (CV)1.5850982
Kurtosis24.402689
Mean112.07315
Median Absolute Deviation (MAD)32
Skewness4.4641849
Sum6051.95
Variance31558.437
MonotonicityNot monotonic
2023-12-10T18:39:34.778491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
50.0 3
 
3.0%
100.0 2
 
2.0%
45.0 2
 
2.0%
10.0 2
 
2.0%
37.0 1
 
1.0%
59.0 1
 
1.0%
189.0 1
 
1.0%
14.0 1
 
1.0%
104.94 1
 
1.0%
12.0 1
 
1.0%
Other values (39) 39
39.0%
(Missing) 46
46.0%
ValueCountFrequency (%)
10.0 2
2.0%
11.0 1
1.0%
12.0 1
1.0%
14.0 1
1.0%
14.2 1
1.0%
19.0 1
1.0%
20.0 1
1.0%
21.0 1
1.0%
24.0 1
1.0%
25.0 1
1.0%
ValueCountFrequency (%)
1172.0 1
1.0%
524.3 1
1.0%
390.0 1
1.0%
273.0 1
1.0%
246.0 1
1.0%
235.0 1
1.0%
208.0 1
1.0%
205.0 1
1.0%
200.0 1
1.0%
196.0 1
1.0%

data_lbr_cnt
Text

MISSING 

Distinct41
Distinct (%)87.2%
Missing53
Missing (%)53.0%
Memory size932.0 B
2023-12-10T18:39:35.087292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.0212766
Min length2

Characters and Unicode

Total characters189
Distinct characters22
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)80.9%

Sample

1st row40510
2nd row744
3rd row2691
4th row38686
5th row5000
ValueCountFrequency (%)
300 4
 
8.3%
2000 3
 
6.2%
1000 2
 
4.2%
9609 1
 
2.1%
20000 1
 
2.1%
2100 1
 
2.1%
11889 1
 
2.1%
15093 1
 
2.1%
4287 1
 
2.1%
400 1
 
2.1%
Other values (32) 32
66.7%
2023-12-10T18:39:35.655622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 68
36.0%
1 25
 
13.2%
2 14
 
7.4%
5 14
 
7.4%
8 12
 
6.3%
3 10
 
5.3%
6 10
 
5.3%
9 10
 
5.3%
4 9
 
4.8%
7 5
 
2.6%
Other values (12) 12
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 177
93.7%
Other Letter 11
 
5.8%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
Decimal Number
ValueCountFrequency (%)
0 68
38.4%
1 25
 
14.1%
2 14
 
7.9%
5 14
 
7.9%
8 12
 
6.8%
3 10
 
5.6%
6 10
 
5.6%
9 10
 
5.6%
4 9
 
5.1%
7 5
 
2.8%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 178
94.2%
Hangul 11
 
5.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 68
38.2%
1 25
 
14.0%
2 14
 
7.9%
5 14
 
7.9%
8 12
 
6.7%
3 10
 
5.6%
6 10
 
5.6%
9 10
 
5.6%
4 9
 
5.1%
7 5
 
2.8%
Hangul
ValueCountFrequency (%)
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 178
94.2%
Hangul 11
 
5.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 68
38.2%
1 25
 
14.0%
2 14
 
7.9%
5 14
 
7.9%
8 12
 
6.7%
3 10
 
5.6%
6 10
 
5.6%
9 10
 
5.6%
4 9
 
5.1%
7 5
 
2.8%
Hangul
ValueCountFrequency (%)
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
16 
연5회
11 
연3회
10 
연4회
연2회
Other values (19)
45 

Length

Max length5
Median length3
Mean length3.38
Min length3

Unique

Unique9 ?
Unique (%)9.0%

Sample

1st row연 9회
2nd row<NA>
3rd row연 3회
4th row연1회
5th row연10회

Common Values

ValueCountFrequency (%)
<NA> 16
16.0%
연5회 11
11.0%
연3회 10
10.0%
연4회 9
9.0%
연2회 9
9.0%
연6회 8
 
8.0%
연1회 5
 
5.0%
연10회 4
 
4.0%
연8회 4
 
4.0%
연9회 4
 
4.0%
Other values (14) 20
20.0%

Length

2023-12-10T18:39:36.409962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 16
15.5%
연5회 11
10.7%
연3회 10
9.7%
연4회 9
 
8.7%
연2회 9
 
8.7%
연6회 8
 
7.8%
연1회 5
 
4.9%
연10회 4
 
3.9%
연8회 4
 
3.9%
연9회 4
 
3.9%
Other values (15) 23
22.3%

prgrm_tot
Categorical

Distinct34
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
17 
5
3
1
16
 
5
Other values (29)
58 

Length

Max length9
Median length4
Mean length2.13
Min length1

Unique

Unique14 ?
Unique (%)14.0%

Sample

1st row61(3관 전체)
2nd row<NA>
3rd row61(3관 전체)
4th row36
5th row32

Common Values

ValueCountFrequency (%)
<NA> 17
17.0%
5 8
 
8.0%
3 6
 
6.0%
1 6
 
6.0%
16 5
 
5.0%
12 5
 
5.0%
10 4
 
4.0%
2 4
 
4.0%
4 4
 
4.0%
15 4
 
4.0%
Other values (24) 37
37.0%

Length

2023-12-10T18:39:36.646475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 17
16.7%
5 8
 
7.8%
3 6
 
5.9%
1 6
 
5.9%
16 5
 
4.9%
12 5
 
4.9%
10 4
 
3.9%
2 4
 
3.9%
4 4
 
3.9%
15 4
 
3.9%
Other values (25) 39
38.2%

fyer_opn_dt_tot
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)66.0%
Missing6
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean274.19149
Minimum80
Maximum365
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:36.860365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum80
5-th percentile144.3
Q1247.25
median296
Q3310
95-th percentile360
Maximum365
Range285
Interquartile range (IQR)62.75

Descriptive statistics

Standard deviation60.622625
Coefficient of variation (CV)0.22109594
Kurtosis1.002658
Mean274.19149
Median Absolute Deviation (MAD)26
Skewness-1.0766788
Sum25774
Variance3675.1027
MonotonicityNot monotonic
2023-12-10T18:39:37.076986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 8
 
8.0%
300 7
 
7.0%
365 3
 
3.0%
307 3
 
3.0%
280 3
 
3.0%
312 3
 
3.0%
270 2
 
2.0%
278 2
 
2.0%
311 2
 
2.0%
262 2
 
2.0%
Other values (52) 59
59.0%
(Missing) 6
 
6.0%
ValueCountFrequency (%)
80 1
1.0%
120 1
1.0%
122 1
1.0%
136 1
1.0%
143 1
1.0%
145 1
1.0%
150 2
2.0%
169 1
1.0%
177 1
1.0%
200 1
1.0%
ValueCountFrequency (%)
365 3
3.0%
363 1
 
1.0%
360 2
2.0%
358 1
 
1.0%
348 1
 
1.0%
344 1
 
1.0%
340 1
 
1.0%
330 1
 
1.0%
326 1
 
1.0%
320 1
 
1.0%

fyer_usemem_tot
Real number (ℝ)

MISSING 

Distinct88
Distinct (%)90.7%
Missing3
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean118311.58
Minimum400
Maximum1423500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:37.314069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum400
5-th percentile1460
Q17000
median20530
Q3112113
95-th percentile508777.6
Maximum1423500
Range1423100
Interquartile range (IQR)105113

Descriptive statistics

Standard deviation237995.64
Coefficient of variation (CV)2.0116006
Kurtosis13.822162
Mean118311.58
Median Absolute Deviation (MAD)17480
Skewness3.4826316
Sum11476223
Variance5.6641925 × 1010
MonotonicityNot monotonic
2023-12-10T18:39:37.549522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000 4
 
4.0%
6000 3
 
3.0%
7000 2
 
2.0%
3500 2
 
2.0%
12000 2
 
2.0%
27000 2
 
2.0%
3170 1
 
1.0%
16460 1
 
1.0%
9863 1
 
1.0%
16586 1
 
1.0%
Other values (78) 78
78.0%
(Missing) 3
 
3.0%
ValueCountFrequency (%)
400 1
1.0%
649 1
1.0%
800 1
1.0%
875 1
1.0%
1300 1
1.0%
1500 1
1.0%
1600 1
1.0%
1670 1
1.0%
1862 1
1.0%
2200 1
1.0%
ValueCountFrequency (%)
1423500 1
1.0%
1147826 1
1.0%
1023738 1
1.0%
647805 1
1.0%
623888 1
1.0%
480000 1
1.0%
452024 1
1.0%
384032 1
1.0%
379910 1
1.0%
337930 1
1.0%

dyrg_usemem_cnt
Real number (ℝ)

MISSING 

Distinct78
Distinct (%)82.1%
Missing5
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean414.84295
Minimum4
Maximum4723
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:37.852952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile9.7
Q131
median85
Q3415
95-th percentile1793.6
Maximum4723
Range4719
Interquartile range (IQR)384

Descriptive statistics

Standard deviation798.17581
Coefficient of variation (CV)1.9240433
Kurtosis13.990545
Mean414.84295
Median Absolute Deviation (MAD)70
Skewness3.4768483
Sum39410.08
Variance637084.62
MonotonicityNot monotonic
2023-12-10T18:39:38.104309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.0 5
 
5.0%
50.0 4
 
4.0%
10.0 3
 
3.0%
15.0 3
 
3.0%
5.0 3
 
3.0%
83.0 2
 
2.0%
32.0 2
 
2.0%
600.0 2
 
2.0%
25.0 2
 
2.0%
213.0 1
 
1.0%
Other values (68) 68
68.0%
(Missing) 5
 
5.0%
ValueCountFrequency (%)
4.0 1
 
1.0%
5.0 3
3.0%
9.0 1
 
1.0%
10.0 3
3.0%
12.0 1
 
1.0%
15.0 3
3.0%
19.0 1
 
1.0%
20.0 5
5.0%
22.0 1
 
1.0%
25.0 2
 
2.0%
ValueCountFrequency (%)
4723.0 1
1.0%
4187.0 1
1.0%
2975.982558 1
1.0%
2076.298077 1
1.0%
1900.0 1
1.0%
1748.0 1
1.0%
1644.0 1
1.0%
1414.0 1
1.0%
1259.0 1
1.0%
1250.0 1
1.0%

gnrl_fee
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)63.2%
Missing81
Missing (%)81.0%
Infinite0
Infinite (%)0.0%
Mean5632.1053
Minimum10
Maximum20000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:38.292765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile451
Q12000
median4000
Q38500
95-th percentile13700
Maximum20000
Range19990
Interquartile range (IQR)6500

Descriptive statistics

Standard deviation5087.067
Coefficient of variation (CV)0.90322655
Kurtosis2.162223
Mean5632.1053
Median Absolute Deviation (MAD)3000
Skewness1.4170482
Sum107010
Variance25878251
MonotonicityNot monotonic
2023-12-10T18:39:38.503441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
3000 3
 
3.0%
10000 3
 
3.0%
2000 3
 
3.0%
7000 2
 
2.0%
1000 1
 
1.0%
20000 1
 
1.0%
4500 1
 
1.0%
10 1
 
1.0%
4000 1
 
1.0%
13000 1
 
1.0%
Other values (2) 2
 
2.0%
(Missing) 81
81.0%
ValueCountFrequency (%)
10 1
 
1.0%
500 1
 
1.0%
1000 1
 
1.0%
2000 3
3.0%
3000 3
3.0%
4000 1
 
1.0%
4500 1
 
1.0%
5000 1
 
1.0%
7000 2
2.0%
10000 3
3.0%
ValueCountFrequency (%)
20000 1
 
1.0%
13000 1
 
1.0%
10000 3
3.0%
7000 2
2.0%
5000 1
 
1.0%
4500 1
 
1.0%
4000 1
 
1.0%
3000 3
3.0%
2000 3
3.0%
1000 1
 
1.0%

pre_schl_gnrl_fee
Categorical

IMBALANCE 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
94 
5000
 
2
16000
 
1
500
 
1
3000
 
1

Length

Max length5
Median length4
Mean length3.99
Min length3

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 94
94.0%
5000 2
 
2.0%
16000 1
 
1.0%
500 1
 
1.0%
3000 1
 
1.0%
300 1
 
1.0%

Length

2023-12-10T18:39:38.923032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:39.137351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 94
94.0%
5000 2
 
2.0%
16000 1
 
1.0%
500 1
 
1.0%
3000 1
 
1.0%
300 1
 
1.0%

ele_schl_gnrl_fee
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)77.8%
Missing82
Missing (%)82.0%
Infinite0
Infinite (%)0.0%
Mean3494.4444
Minimum300
Maximum16000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:39.318121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile470
Q11000
median2500
Q35000
95-th percentile8350
Maximum16000
Range15700
Interquartile range (IQR)4000

Descriptive statistics

Standard deviation3766.9573
Coefficient of variation (CV)1.0779846
Kurtosis6.8352646
Mean3494.4444
Median Absolute Deviation (MAD)1800
Skewness2.3114205
Sum62900
Variance14189967
MonotonicityNot monotonic
2023-12-10T18:39:39.529963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
5000 3
 
3.0%
3000 2
 
2.0%
1000 2
 
2.0%
500 1
 
1.0%
1200 1
 
1.0%
16000 1
 
1.0%
6000 1
 
1.0%
4000 1
 
1.0%
1500 1
 
1.0%
800 1
 
1.0%
Other values (4) 4
 
4.0%
(Missing) 82
82.0%
ValueCountFrequency (%)
300 1
1.0%
500 1
1.0%
600 1
1.0%
800 1
1.0%
1000 2
2.0%
1200 1
1.0%
1500 1
1.0%
2000 1
1.0%
3000 2
2.0%
4000 1
1.0%
ValueCountFrequency (%)
16000 1
 
1.0%
7000 1
 
1.0%
6000 1
 
1.0%
5000 3
3.0%
4000 1
 
1.0%
3000 2
2.0%
2000 1
 
1.0%
1500 1
 
1.0%
1200 1
 
1.0%
1000 2
2.0%

mid_hi_gnrl_fee
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)61.1%
Missing82
Missing (%)82.0%
Infinite0
Infinite (%)0.0%
Mean4188.8889
Minimum300
Maximum18000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:39.724288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile470
Q11000
median3000
Q36000
95-th percentile9500
Maximum18000
Range17700
Interquartile range (IQR)5000

Descriptive statistics

Standard deviation4272.8815
Coefficient of variation (CV)1.0200513
Kurtosis5.8524299
Mean4188.8889
Median Absolute Deviation (MAD)2100
Skewness2.1046373
Sum75400
Variance18257516
MonotonicityNot monotonic
2023-12-10T18:39:39.910996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
3000 4
 
4.0%
1000 3
 
3.0%
6000 2
 
2.0%
7000 2
 
2.0%
500 1
 
1.0%
1800 1
 
1.0%
18000 1
 
1.0%
5000 1
 
1.0%
8000 1
 
1.0%
800 1
 
1.0%
(Missing) 82
82.0%
ValueCountFrequency (%)
300 1
 
1.0%
500 1
 
1.0%
800 1
 
1.0%
1000 3
3.0%
1800 1
 
1.0%
3000 4
4.0%
5000 1
 
1.0%
6000 2
2.0%
7000 2
2.0%
8000 1
 
1.0%
ValueCountFrequency (%)
18000 1
 
1.0%
8000 1
 
1.0%
7000 2
2.0%
6000 2
2.0%
5000 1
 
1.0%
3000 4
4.0%
1800 1
 
1.0%
1000 3
3.0%
800 1
 
1.0%
500 1
 
1.0%

age_19_25_gnrl_fee
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)70.6%
Missing83
Missing (%)83.0%
Infinite0
Infinite (%)0.0%
Mean5100
Minimum100
Maximum20000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:40.174146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile260
Q11800
median3000
Q37000
95-th percentile14400
Maximum20000
Range19900
Interquartile range (IQR)5200

Descriptive statistics

Standard deviation5192.6631
Coefficient of variation (CV)1.0181692
Kurtosis3.3295569
Mean5100
Median Absolute Deviation (MAD)2000
Skewness1.753051
Sum86700
Variance26963750
MonotonicityNot monotonic
2023-12-10T18:39:40.340794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
3000 3
 
3.0%
1000 2
 
2.0%
5000 2
 
2.0%
7000 2
 
2.0%
1800 1
 
1.0%
20000 1
 
1.0%
10000 1
 
1.0%
4500 1
 
1.0%
100 1
 
1.0%
13000 1
 
1.0%
Other values (2) 2
 
2.0%
(Missing) 83
83.0%
ValueCountFrequency (%)
100 1
 
1.0%
300 1
 
1.0%
1000 2
2.0%
1800 1
 
1.0%
2000 1
 
1.0%
3000 3
3.0%
4500 1
 
1.0%
5000 2
2.0%
7000 2
2.0%
10000 1
 
1.0%
ValueCountFrequency (%)
20000 1
 
1.0%
13000 1
 
1.0%
10000 1
 
1.0%
7000 2
2.0%
5000 2
2.0%
4500 1
 
1.0%
3000 3
3.0%
2000 1
 
1.0%
1800 1
 
1.0%
1000 2
2.0%

grp_gnrl_fee_dcrate
Text

MISSING 

Distinct8
Distinct (%)57.1%
Missing86
Missing (%)86.0%
Memory size932.0 B
2023-12-10T18:39:40.564079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length2
Mean length4.4285714
Min length2

Characters and Unicode

Total characters62
Distinct characters21
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)35.7%

Sample

1st row30~40
2nd row40 (어른 40, 청소년 33, 어린이 50)
3rd row30
4th row30
5th row20
ValueCountFrequency (%)
20 4
19.0%
30 3
14.3%
10 2
9.5%
40 2
9.5%
50 2
9.5%
30~40 1
 
4.8%
어른 1
 
4.8%
청소년 1
 
4.8%
33 1
 
4.8%
어린이 1
 
4.8%
Other values (3) 3
14.3%
2023-12-10T18:39:41.041273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18
29.0%
7
 
11.3%
3 7
 
11.3%
2 5
 
8.1%
5 3
 
4.8%
, 3
 
4.8%
4 3
 
4.8%
2
 
3.2%
1 2
 
3.2%
( 1
 
1.6%
Other values (11) 11
17.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38
61.3%
Other Letter 11
 
17.7%
Space Separator 7
 
11.3%
Other Punctuation 3
 
4.8%
Open Punctuation 1
 
1.6%
Math Symbol 1
 
1.6%
Close Punctuation 1
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
Decimal Number
ValueCountFrequency (%)
0 18
47.4%
3 7
 
18.4%
2 5
 
13.2%
5 3
 
7.9%
4 3
 
7.9%
1 2
 
5.3%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51
82.3%
Hangul 11
 
17.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18
35.3%
7
 
13.7%
3 7
 
13.7%
2 5
 
9.8%
5 3
 
5.9%
, 3
 
5.9%
4 3
 
5.9%
1 2
 
3.9%
( 1
 
2.0%
~ 1
 
2.0%
Hangul
ValueCountFrequency (%)
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51
82.3%
Hangul 11
 
17.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18
35.3%
7
 
13.7%
3 7
 
13.7%
2 5
 
9.8%
5 3
 
5.9%
, 3
 
5.9%
4 3
 
5.9%
1 2
 
3.9%
( 1
 
2.0%
~ 1
 
2.0%
Hangul
ValueCountFrequency (%)
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%

etc_gnrl_fee_dcrate
Text

MISSING 

Distinct7
Distinct (%)70.0%
Missing90
Missing (%)90.0%
Memory size932.0 B
2023-12-10T18:39:41.263092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length2
Mean length3.4
Min length2

Characters and Unicode

Total characters34
Distinct characters12
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)60.0%

Sample

1st row35
2nd row50
3rd row50
4th row20
5th row50
ValueCountFrequency (%)
50 4
36.4%
35 1
 
9.1%
20 1
 
9.1%
초,중,고 1
 
9.1%
2,000원 1
 
9.1%
45 1
 
9.1%
30~50 1
 
9.1%
30 1
 
9.1%
2023-12-10T18:39:41.774685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
32.4%
5 7
20.6%
, 4
 
11.8%
3 3
 
8.8%
2 2
 
5.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (2) 2
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24
70.6%
Other Punctuation 4
 
11.8%
Other Letter 4
 
11.8%
Space Separator 1
 
2.9%
Math Symbol 1
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
45.8%
5 7
29.2%
3 3
 
12.5%
2 2
 
8.3%
4 1
 
4.2%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30
88.2%
Hangul 4
 
11.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
36.7%
5 7
23.3%
, 4
 
13.3%
3 3
 
10.0%
2 2
 
6.7%
1
 
3.3%
4 1
 
3.3%
~ 1
 
3.3%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30
88.2%
Hangul 4
 
11.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
36.7%
5 7
23.3%
, 4
 
13.3%
3 3
 
10.0%
2 2
 
6.7%
1
 
3.3%
4 1
 
3.3%
~ 1
 
3.3%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

gnrl_fee_dc_policy
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing85
Missing (%)85.0%
Memory size932.0 B
2023-12-10T18:39:42.214132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length142
Median length20
Mean length32.533333
Min length4

Characters and Unicode

Total characters488
Distinct characters122
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)100.0%

Sample

1st row허준박물관-겸재정선미술관 통합관람권(35%), 제로페이 성인 입장객(2019. 8. 1 ~ 12. 31까지 30%할인), 문화가 있는 날 야간 무료입장 등
2nd row종로구민(50% 할인), 한복착용(50% 할인), 문화가 있는 날(50% 할인)
3rd row국가 유공자 및 장애인, 65세 이상
4th row경로, 장애인, 유공자 할인(20%), 문화가 있는날 무료 또는 일반 기준20%할인
5th row• 65세 이상 경로자, 장애인 50% 할인,• 삼성카드 10% 할인, 프리미엄카드 월1회 무료입장(본인적용),• 현대카드 20% M포인트 사용 (현장결제 시 적용),• 20인 이상 단체 10%, 40인 이상 단체 20%, 100인 이상 단체 40% 할인
ValueCountFrequency (%)
할인 7
 
6.6%
단체 6
 
5.7%
이상 5
 
4.7%
장애인 4
 
3.8%
무료 3
 
2.8%
문화가 3
 
2.8%
유공자 2
 
1.9%
30%할인 2
 
1.9%
20 2
 
1.9%
있는 2
 
1.9%
Other values (66) 70
66.0%
2023-12-10T18:39:42.907438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
 
18.6%
25
 
5.1%
0 24
 
4.9%
% 18
 
3.7%
, 18
 
3.7%
12
 
2.5%
5 10
 
2.0%
( 10
 
2.0%
) 10
 
2.0%
9
 
1.8%
Other values (112) 261
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 263
53.9%
Space Separator 91
 
18.6%
Decimal Number 66
 
13.5%
Other Punctuation 45
 
9.2%
Open Punctuation 10
 
2.0%
Close Punctuation 10
 
2.0%
Uppercase Letter 1
 
0.2%
Dash Punctuation 1
 
0.2%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
25
 
9.5%
12
 
4.6%
9
 
3.4%
9
 
3.4%
8
 
3.0%
7
 
2.7%
7
 
2.7%
6
 
2.3%
6
 
2.3%
6
 
2.3%
Other values (92) 168
63.9%
Decimal Number
ValueCountFrequency (%)
0 24
36.4%
5 10
15.2%
3 9
 
13.6%
2 8
 
12.1%
1 8
 
12.1%
6 3
 
4.5%
4 2
 
3.0%
8 1
 
1.5%
9 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
% 18
40.0%
, 18
40.0%
. 4
 
8.9%
4
 
8.9%
/ 1
 
2.2%
Space Separator
ValueCountFrequency (%)
91
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 263
53.9%
Common 224
45.9%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
25
 
9.5%
12
 
4.6%
9
 
3.4%
9
 
3.4%
8
 
3.0%
7
 
2.7%
7
 
2.7%
6
 
2.3%
6
 
2.3%
6
 
2.3%
Other values (92) 168
63.9%
Common
ValueCountFrequency (%)
91
40.6%
0 24
 
10.7%
% 18
 
8.0%
, 18
 
8.0%
5 10
 
4.5%
( 10
 
4.5%
) 10
 
4.5%
3 9
 
4.0%
2 8
 
3.6%
1 8
 
3.6%
Other values (9) 18
 
8.0%
Latin
ValueCountFrequency (%)
M 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 263
53.9%
ASCII 221
45.3%
Punctuation 4
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
41.2%
0 24
 
10.9%
% 18
 
8.1%
, 18
 
8.1%
5 10
 
4.5%
( 10
 
4.5%
) 10
 
4.5%
3 9
 
4.1%
2 8
 
3.6%
1 8
 
3.6%
Other values (9) 15
 
6.8%
Hangul
ValueCountFrequency (%)
25
 
9.5%
12
 
4.6%
9
 
3.4%
9
 
3.4%
8
 
3.0%
7
 
2.7%
7
 
2.7%
6
 
2.3%
6
 
2.3%
6
 
2.3%
Other values (92) 168
63.9%
Punctuation
ValueCountFrequency (%)
4
100.0%
Distinct19
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
전체
53 
<NA>
29 
해당없음
 
2
유치원, 65세이상, 장애인
 
1
만65세이상, 만6세이하, 국가유공자및유족, 독립유공자및유족, 518민주유공자및유족, 장애인
 
1
Other values (14)
14 

Length

Max length262
Median length2
Mean length9.14
Min length2

Unique

Unique16 ?
Unique (%)16.0%

Sample

1st row<NA>
2nd row전체
3rd row<NA>
4th row<NA>
5th row미취학 6세이하, 65세이상 어르신,,장애인, 국가유공자, 독립유공자, 장애인, 다둥이행복카드 소지자, 투표확인증 제출자 등

Common Values

ValueCountFrequency (%)
전체 53
53.0%
<NA> 29
29.0%
해당없음 2
 
2.0%
유치원, 65세이상, 장애인 1
 
1.0%
만65세이상, 만6세이하, 국가유공자및유족, 독립유공자및유족, 518민주유공자및유족, 장애인 1
 
1.0%
영유아, 노인 1
 
1.0%
65세 이상 노인, 6세 이하 어린이,장애인등록증 소지자(1~3급 장애인 동반 1인 포함),국가유공자증, 국가유공자유족증 소지자,독립유공자증, 독립유공자유족증 소지자,5.18민주유공자증, 5.18민주유공자유족증 소지자 ,참전유공자, 고엽제후유의증환자증 소지자 ,특수임무유공자증, 특수임무유공자유족증 소지자,공무수행을 위하여 출입하는 자 ,꿈나무사랑카드 소지자(배우자 포함),대전광역시 명예시민증 소지자(배우자 포함),투표확인증(1회에 한하여 선거일 후 3개월까지 유효) 1
 
1.0%
65세 이상 성인, 7세 이하 아동, 국가유공자, 장애인 1
 
1.0%
희망교실카드 제시, 미술관 카페 이용자, 75세 이상 어르신 1
 
1.0%
미취학아동 등 1
 
1.0%
Other values (9) 9
 
9.0%

Length

2023-12-10T18:39:43.150426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 53
25.5%
na 29
 
13.9%
장애인 8
 
3.8%
소지자 4
 
1.9%
4
 
1.9%
이하 4
 
1.9%
이상 4
 
1.9%
미취학 3
 
1.4%
미취학아동 3
 
1.4%
65세 3
 
1.4%
Other values (81) 93
44.7%

spc_fee
Text

MISSING 

Distinct20
Distinct (%)54.1%
Missing63
Missing (%)63.0%
Memory size932.0 B
2023-12-10T18:39:43.429716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length4
Mean length6.2702703
Min length3

Characters and Unicode

Total characters232
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)35.1%

Sample

1st row기획전시별 별도 책정,(2,000원~3,000원 수준)
2nd row기획전시별 별도 책정,(2,000원~3,000원 수준),* 덕수궁 입장료 제외
3rd row1000
4th row15000
5th row15000
ValueCountFrequency (%)
5000 7
 
14.6%
2000 4
 
8.3%
1000 3
 
6.2%
15000 3
 
6.2%
4000 3
 
6.2%
기획전시별 2
 
4.2%
수준 2
 
4.2%
책정,(2,000원~3,000원 2
 
4.2%
별도 2
 
4.2%
3000 2
 
4.2%
Other values (17) 18
37.5%
2023-12-10T18:39:43.984547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 116
50.0%
5 13
 
5.6%
11
 
4.7%
1 10
 
4.3%
, 10
 
4.3%
2 8
 
3.4%
5
 
2.2%
3 5
 
2.2%
4
 
1.7%
4 4
 
1.7%
Other values (28) 46
 
19.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 162
69.8%
Other Letter 41
 
17.7%
Space Separator 11
 
4.7%
Other Punctuation 11
 
4.7%
Math Symbol 3
 
1.3%
Close Punctuation 2
 
0.9%
Open Punctuation 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
 
12.2%
4
 
9.8%
3
 
7.3%
3
 
7.3%
3
 
7.3%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (12) 13
31.7%
Decimal Number
ValueCountFrequency (%)
0 116
71.6%
5 13
 
8.0%
1 10
 
6.2%
2 8
 
4.9%
3 5
 
3.1%
4 4
 
2.5%
6 2
 
1.2%
8 2
 
1.2%
9 1
 
0.6%
7 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
, 10
90.9%
* 1
 
9.1%
Space Separator
ValueCountFrequency (%)
11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 191
82.3%
Hangul 41
 
17.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
 
12.2%
4
 
9.8%
3
 
7.3%
3
 
7.3%
3
 
7.3%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (12) 13
31.7%
Common
ValueCountFrequency (%)
0 116
60.7%
5 13
 
6.8%
11
 
5.8%
1 10
 
5.2%
, 10
 
5.2%
2 8
 
4.2%
3 5
 
2.6%
4 4
 
2.1%
~ 3
 
1.6%
6 2
 
1.0%
Other values (6) 9
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 191
82.3%
Hangul 41
 
17.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 116
60.7%
5 13
 
6.8%
11
 
5.8%
1 10
 
5.2%
, 10
 
5.2%
2 8
 
4.2%
3 5
 
2.6%
4 4
 
2.1%
~ 3
 
1.6%
6 2
 
1.0%
Other values (6) 9
 
4.7%
Hangul
ValueCountFrequency (%)
5
 
12.2%
4
 
9.8%
3
 
7.3%
3
 
7.3%
3
 
7.3%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (12) 13
31.7%

pre_schl_spc_fee
Text

MISSING 

Distinct11
Distinct (%)91.7%
Missing88
Missing (%)88.0%
Memory size932.0 B
2023-12-10T18:39:44.247646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.1666667
Min length2

Characters and Unicode

Total characters50
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)83.3%

Sample

1st row8000
2nd row평균 3,000
3rd row2000
4th row3000
5th row3000
ValueCountFrequency (%)
3000 2
14.3%
8000 1
 
7.1%
평균 1
 
7.1%
3,000 1
 
7.1%
2000 1
 
7.1%
4500 1
 
7.1%
전시별 1
 
7.1%
상이 1
 
7.1%
300 1
 
7.1%
4000 1
 
7.1%
Other values (3) 3
21.4%
2023-12-10T18:39:44.761214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 27
54.0%
3 4
 
8.0%
2
 
4.0%
2
 
4.0%
5 2
 
4.0%
4 2
 
4.0%
, 1
 
2.0%
2 1
 
2.0%
1
 
2.0%
1
 
2.0%
Other values (7) 7
 
14.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38
76.0%
Other Letter 9
 
18.0%
Space Separator 2
 
4.0%
Other Punctuation 1
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Decimal Number
ValueCountFrequency (%)
0 27
71.1%
3 4
 
10.5%
5 2
 
5.3%
4 2
 
5.3%
2 1
 
2.6%
8 1
 
2.6%
1 1
 
2.6%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41
82.0%
Hangul 9
 
18.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 27
65.9%
3 4
 
9.8%
2
 
4.9%
5 2
 
4.9%
4 2
 
4.9%
, 1
 
2.4%
2 1
 
2.4%
8 1
 
2.4%
1 1
 
2.4%
Hangul
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41
82.0%
Hangul 9
 
18.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 27
65.9%
3 4
 
9.8%
2
 
4.9%
5 2
 
4.9%
4 2
 
4.9%
, 1
 
2.4%
2 1
 
2.4%
8 1
 
2.4%
1 1
 
2.4%
Hangul
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

pre_ele_schl_spc_fee
Text

MISSING 

Distinct18
Distinct (%)56.2%
Missing68
Missing (%)68.0%
Memory size932.0 B
2023-12-10T18:39:45.068941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length4
Mean length4.21875
Min length2

Characters and Unicode

Total characters135
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)40.6%

Sample

1st row500
2nd row10000
3rd row9000
4th row평균 3,000
5th row3000
ValueCountFrequency (%)
3000 6
17.6%
1000 5
14.7%
5000 4
 
11.8%
9000 2
 
5.9%
500 2
 
5.9%
상이 1
 
2.9%
700 1
 
2.9%
2000 1
 
2.9%
전체 1
 
2.9%
300 1
 
2.9%
Other values (10) 10
29.4%
2023-12-10T18:39:45.503677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 88
65.2%
3 8
 
5.9%
1 7
 
5.2%
5 6
 
4.4%
, 3
 
2.2%
7 2
 
1.5%
2
 
1.5%
4 2
 
1.5%
2 2
 
1.5%
2
 
1.5%
Other values (11) 13
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 119
88.1%
Other Letter 9
 
6.7%
Other Punctuation 4
 
3.0%
Space Separator 2
 
1.5%
Math Symbol 1
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 88
73.9%
3 8
 
6.7%
1 7
 
5.9%
5 6
 
5.0%
7 2
 
1.7%
4 2
 
1.7%
2 2
 
1.7%
6 2
 
1.7%
9 2
 
1.7%
Other Letter
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
. 1
 
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 126
93.3%
Hangul 9
 
6.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 88
69.8%
3 8
 
6.3%
1 7
 
5.6%
5 6
 
4.8%
, 3
 
2.4%
7 2
 
1.6%
4 2
 
1.6%
2 2
 
1.6%
2
 
1.6%
6 2
 
1.6%
Other values (3) 4
 
3.2%
Hangul
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 126
93.3%
Hangul 9
 
6.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 88
69.8%
3 8
 
6.3%
1 7
 
5.6%
5 6
 
4.8%
, 3
 
2.4%
7 2
 
1.6%
4 2
 
1.6%
2 2
 
1.6%
2
 
1.6%
6 2
 
1.6%
Other values (3) 4
 
3.2%
Hangul
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

mid_hi_spc_fee
Text

MISSING 

Distinct18
Distinct (%)54.5%
Missing67
Missing (%)67.0%
Memory size932.0 B
2023-12-10T18:39:45.754076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length4
Mean length4.3030303
Min length2

Characters and Unicode

Total characters142
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)39.4%

Sample

1st row500
2nd row13000
3rd row11000
4th row평균 4,500
5th row3000
ValueCountFrequency (%)
3000 6
17.1%
5000 5
14.3%
1000 4
 
11.4%
2000 3
 
8.6%
700 2
 
5.7%
2,000~12,000 1
 
2.9%
4,500 1
 
2.9%
평균 1
 
2.9%
11000 1
 
2.9%
13000 1
 
2.9%
Other values (10) 10
28.6%
2023-12-10T18:39:46.238575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89
62.7%
1 9
 
6.3%
3 8
 
5.6%
5 7
 
4.9%
2 6
 
4.2%
, 3
 
2.1%
7 3
 
2.1%
4 3
 
2.1%
2
 
1.4%
2
 
1.4%
Other values (10) 10
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 126
88.7%
Other Letter 9
 
6.3%
Other Punctuation 4
 
2.8%
Space Separator 2
 
1.4%
Math Symbol 1
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 89
70.6%
1 9
 
7.1%
3 8
 
6.3%
5 7
 
5.6%
2 6
 
4.8%
7 3
 
2.4%
4 3
 
2.4%
6 1
 
0.8%
Other Letter
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
. 1
 
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 133
93.7%
Hangul 9
 
6.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89
66.9%
1 9
 
6.8%
3 8
 
6.0%
5 7
 
5.3%
2 6
 
4.5%
, 3
 
2.3%
7 3
 
2.3%
4 3
 
2.3%
2
 
1.5%
6 1
 
0.8%
Other values (2) 2
 
1.5%
Hangul
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 133
93.7%
Hangul 9
 
6.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89
66.9%
1 9
 
6.8%
3 8
 
6.0%
5 7
 
5.3%
2 6
 
4.5%
, 3
 
2.3%
7 3
 
2.3%
4 3
 
2.3%
2
 
1.5%
6 1
 
0.8%
Other values (2) 2
 
1.5%
Hangul
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

age_19_25_spc_fee
Text

MISSING 

Distinct17
Distinct (%)58.6%
Missing71
Missing (%)71.0%
Memory size932.0 B
2023-12-10T18:39:46.498049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length4.5172414
Min length3

Characters and Unicode

Total characters131
Distinct characters19
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)41.4%

Sample

1st row1000
2nd row15000
3rd row평균 4,500
4th row10000
5th row12000
ValueCountFrequency (%)
3000 5
16.1%
5000 4
12.9%
4000 3
 
9.7%
1000 3
 
9.7%
15000 2
 
6.5%
6000 1
 
3.2%
상이 1
 
3.2%
전시별 1
 
3.2%
300 1
 
3.2%
2500 1
 
3.2%
Other values (9) 9
29.0%
2023-12-10T18:39:46.954886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 84
64.1%
5 9
 
6.9%
1 9
 
6.9%
3 7
 
5.3%
4 5
 
3.8%
2 3
 
2.3%
2
 
1.5%
7 1
 
0.8%
1
 
0.8%
1
 
0.8%
Other values (9) 9
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 120
91.6%
Other Letter 7
 
5.3%
Space Separator 2
 
1.5%
Other Punctuation 1
 
0.8%
Math Symbol 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 84
70.0%
5 9
 
7.5%
1 9
 
7.5%
3 7
 
5.8%
4 5
 
4.2%
2 3
 
2.5%
7 1
 
0.8%
6 1
 
0.8%
8 1
 
0.8%
Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 124
94.7%
Hangul 7
 
5.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 84
67.7%
5 9
 
7.3%
1 9
 
7.3%
3 7
 
5.6%
4 5
 
4.0%
2 3
 
2.4%
2
 
1.6%
7 1
 
0.8%
, 1
 
0.8%
6 1
 
0.8%
Other values (2) 2
 
1.6%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 124
94.7%
Hangul 7
 
5.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 84
67.7%
5 9
 
7.3%
1 9
 
7.3%
3 7
 
5.6%
4 5
 
4.0%
2 3
 
2.4%
2
 
1.6%
7 1
 
0.8%
, 1
 
0.8%
6 1
 
0.8%
Other values (2) 2
 
1.6%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

grp_spc_fee_dcrate
Categorical

IMBALANCE 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
73 
20
13 
25
 
3
10
 
2
50
 
2
Other values (7)
 
7

Length

Max length14
Median length4
Mean length3.65
Min length2

Unique

Unique7 ?
Unique (%)7.0%

Sample

1st row20
2nd row<NA>
3rd row20
4th row<NA>
5th row30~40

Common Values

ValueCountFrequency (%)
<NA> 73
73.0%
20 13
 
13.0%
25 3
 
3.0%
10 2
 
2.0%
50 2
 
2.0%
30~40 1
 
1.0%
0.15 1
 
1.0%
20인이상 1,000원할인 1
 
1.0%
0.5 1
 
1.0%
40 1
 
1.0%
Other values (2) 2
 
2.0%

Length

2023-12-10T18:39:47.167331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 73
72.3%
20 13
 
12.9%
25 3
 
3.0%
10 2
 
2.0%
50 2
 
2.0%
30~40 1
 
1.0%
0.15 1
 
1.0%
20인이상 1
 
1.0%
1,000원할인 1
 
1.0%
0.5 1
 
1.0%
Other values (3) 3
 
3.0%

etc_spc_fee_dcrate
Text

MISSING 

Distinct13
Distinct (%)54.2%
Missing76
Missing (%)76.0%
Memory size932.0 B
2023-12-10T18:39:47.398644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10.5
Mean length3.9583333
Min length2

Characters and Unicode

Total characters95
Distinct characters18
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)33.3%

Sample

1st row20~50
2nd row20~50
3rd row30
4th row0.2
5th row20~40
ValueCountFrequency (%)
50 7
26.9%
30 3
11.5%
20~50 2
 
7.7%
20~40 2
 
7.7%
40 2
 
7.7%
0.2 1
 
3.8%
30-50 1
 
3.8%
10~40 1
 
3.8%
33-50 1
 
3.8%
10%,~50 1
 
3.8%
Other values (5) 5
19.2%
2023-12-10T18:39:47.826503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 31
32.6%
5 16
16.8%
3 7
 
7.4%
2 7
 
7.4%
~ 7
 
7.4%
% 5
 
5.3%
4 5
 
5.3%
. 2
 
2.1%
- 2
 
2.1%
1 2
 
2.1%
Other values (8) 11
 
11.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
71.6%
Other Punctuation 9
 
9.5%
Math Symbol 7
 
7.4%
Other Letter 7
 
7.4%
Dash Punctuation 2
 
2.1%
Space Separator 2
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31
45.6%
5 16
23.5%
3 7
 
10.3%
2 7
 
10.3%
4 5
 
7.4%
1 2
 
2.9%
Other Letter
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Other Punctuation
ValueCountFrequency (%)
% 5
55.6%
. 2
 
22.2%
, 2
 
22.2%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88
92.6%
Hangul 7
 
7.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 31
35.2%
5 16
18.2%
3 7
 
8.0%
2 7
 
8.0%
~ 7
 
8.0%
% 5
 
5.7%
4 5
 
5.7%
. 2
 
2.3%
- 2
 
2.3%
1 2
 
2.3%
Other values (2) 4
 
4.5%
Hangul
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
92.6%
Hangul 7
 
7.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 31
35.2%
5 16
18.2%
3 7
 
8.0%
2 7
 
8.0%
~ 7
 
8.0%
% 5
 
5.7%
4 5
 
5.7%
. 2
 
2.3%
- 2
 
2.3%
1 2
 
2.3%
Other values (2) 4
 
4.5%
Hangul
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

spc_fee_dc_policy
Text

MISSING 

Distinct36
Distinct (%)92.3%
Missing61
Missing (%)61.0%
Memory size932.0 B
2023-12-10T18:39:48.252153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length156
Median length57
Mean length46.333333
Min length5

Characters and Unicode

Total characters1807
Distinct characters208
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)84.6%

Sample

1st row현대카드 플래티넘 회원 50% (동반 1인 포함, 월5회, 해당 카드결제 시),아시아나클럽 일반회원 20% (카드제시자에 한함),SPC 해피포인트 회원 50% 할인(앱 쿠폰 인증 회원)
2nd row현대카드 플래티넘 회원 50% (동반 1인 포함, 월5회, 해당 카드결제 시),아시아나클럽 일반회원 20% (카드제시자에 한함),SPC 해피포인트 회원 50% 할인(앱 쿠폰 인증 회원)
3rd row허준박물관-겸재정선미술관 통합관람권(35%), 제로페이 성인 입장객(2019. 8. 1 ~ 12. 31까지 30%할인), 문화가 있는 날 야간 무료입장 등
4th row*특별할인: 다둥이행복카드, 문화가 있는 날 (50%/6시 이후 발권),*제휴할인: 카카오/제로페이 결제시 20%,*단체: 20인 이상 인솔자 1명 무료,*특별권: 만 65세 이상, 장애인 4~6급, 미취학 아동, 국가/독립유공자유족증 소유자, 의사상자유족, 서울명예시민증 소유자
5th row도민 할인, 제휴처 할인 등
ValueCountFrequency (%)
할인 21
 
5.6%
회원 13
 
3.5%
13
 
3.5%
11
 
2.9%
이상 10
 
2.7%
10
 
2.7%
장애인 9
 
2.4%
50 8
 
2.1%
문화가 8
 
2.1%
있는 8
 
2.1%
Other values (184) 264
70.4%
2023-12-10T18:39:48.956721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
336
 
18.6%
, 99
 
5.5%
87
 
4.8%
0 73
 
4.0%
% 55
 
3.0%
38
 
2.1%
5 35
 
1.9%
32
 
1.8%
) 32
 
1.8%
( 32
 
1.8%
Other values (198) 988
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1021
56.5%
Space Separator 336
 
18.6%
Other Punctuation 185
 
10.2%
Decimal Number 183
 
10.1%
Close Punctuation 32
 
1.8%
Open Punctuation 32
 
1.8%
Uppercase Letter 10
 
0.6%
Math Symbol 6
 
0.3%
Lowercase Letter 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
87
 
8.5%
38
 
3.7%
32
 
3.1%
28
 
2.7%
25
 
2.4%
25
 
2.4%
23
 
2.3%
21
 
2.1%
21
 
2.1%
20
 
2.0%
Other values (169) 701
68.7%
Decimal Number
ValueCountFrequency (%)
0 73
39.9%
5 35
19.1%
1 24
 
13.1%
2 22
 
12.0%
3 9
 
4.9%
6 8
 
4.4%
4 6
 
3.3%
9 3
 
1.6%
7 2
 
1.1%
8 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 99
53.5%
% 55
29.7%
: 12
 
6.5%
/ 6
 
3.2%
. 5
 
2.7%
4
 
2.2%
* 4
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
C 2
20.0%
P 2
20.0%
S 2
20.0%
M 2
20.0%
L 1
10.0%
A 1
10.0%
Space Separator
ValueCountFrequency (%)
336
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1021
56.5%
Common 775
42.9%
Latin 11
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
87
 
8.5%
38
 
3.7%
32
 
3.1%
28
 
2.7%
25
 
2.4%
25
 
2.4%
23
 
2.3%
21
 
2.1%
21
 
2.1%
20
 
2.0%
Other values (169) 701
68.7%
Common
ValueCountFrequency (%)
336
43.4%
, 99
 
12.8%
0 73
 
9.4%
% 55
 
7.1%
5 35
 
4.5%
) 32
 
4.1%
( 32
 
4.1%
1 24
 
3.1%
2 22
 
2.8%
: 12
 
1.5%
Other values (12) 55
 
7.1%
Latin
ValueCountFrequency (%)
C 2
18.2%
P 2
18.2%
S 2
18.2%
M 2
18.2%
L 1
9.1%
o 1
9.1%
A 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1021
56.5%
ASCII 782
43.3%
Punctuation 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
336
43.0%
, 99
 
12.7%
0 73
 
9.3%
% 55
 
7.0%
5 35
 
4.5%
) 32
 
4.1%
( 32
 
4.1%
1 24
 
3.1%
2 22
 
2.8%
: 12
 
1.5%
Other values (18) 62
 
7.9%
Hangul
ValueCountFrequency (%)
87
 
8.5%
38
 
3.7%
32
 
3.1%
28
 
2.7%
25
 
2.4%
25
 
2.4%
23
 
2.3%
21
 
2.1%
21
 
2.1%
20
 
2.0%
Other values (169) 701
68.7%
Punctuation
ValueCountFrequency (%)
4
100.0%

spc_fee_free_trgt
Text

MISSING 

Distinct34
Distinct (%)50.0%
Missing32
Missing (%)32.0%
Memory size932.0 B
2023-12-10T18:39:49.345869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length351
Median length262
Mean length36.029412
Min length2

Characters and Unicode

Total characters2450
Distinct characters201
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)41.2%

Sample

1st row1.일반,만24세 이하 또는 만65세 이상,대학생,국가유공자·독립유공자(유공자증 소지시 본인 및 동반가족),국가유공자·독립유공자 유족증 소지자,미술관에 미술작품 등의 자료 기증자(기증자 카드 소지시 본인 및 동반가족) ,국립현대미술관 유료회원,박물관·미술관 학예사 자격 취득자,예술인패스 소지자,ICOM(국제박물관협의회)카드 소지자,학생인솔교사 및 관광안내사(사전예약 단체에 한함),장애인 및 동행보호자,기초수급 대상자 및 차상위 계층(증명서 제시자에 한함),,2.제휴사,현대카드 프리미엄 회원 (동반 1인 포함, 월5회, 해당 카드 결제시),아시아나클럽 우수회원 카드(카드제시자에 한함,,3.매월 마지막 수요일 문화가 있는 날
2nd row1.일반,만24세 이하 또는 만65세 이상,대학생,국가유공자·독립유공자(유공자증 소지시 본인 및 동반가족),국가유공자·독립유공자 유족증 소지자,미술관에 미술작품 등의 자료 기증자(기증자 카드 소지시 본인 및 동반가족) ,국립현대미술관 유료회원,박물관·미술관 학예사 자격 취득자,예술인패스 소지자,ICOM(국제박물관협의회)카드 소지자,학생인솔교사 및 관광안내사(사전예약 단체에 한함),장애인 및 동행보호자,기초수급 대상자 및 차상위 계층(증명서 제시자에 한함),,2.제휴사,현대카드 프리미엄 회원 (동반 1인 포함, 월5회, 해당 카드 결제시),아시아나클럽 우수회원 카드(카드제시자에 한함,,3.매월 마지막 수요일 문화가 있는 날
3rd row전체
4th row미취학 6세이하, 65세이상 어르신,,장애인, 국가유공자, 독립유공자, 장애인, 다둥이행복카드 소지자, 투표확인증 제출자 등
5th row36개월 미만 유아
ValueCountFrequency (%)
전체 30
 
6.4%
장애인 16
 
3.4%
15
 
3.2%
미만 12
 
2.6%
이상 11
 
2.4%
소지자 11
 
2.4%
유아 10
 
2.1%
9
 
1.9%
9
 
1.9%
65세 8
 
1.7%
Other values (169) 335
71.9%
2023-12-10T18:39:50.308476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
398
 
16.2%
, 168
 
6.9%
113
 
4.6%
79
 
3.2%
48
 
2.0%
45
 
1.8%
42
 
1.7%
39
 
1.6%
39
 
1.6%
38
 
1.6%
Other values (191) 1441
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1650
67.3%
Space Separator 398
 
16.2%
Other Punctuation 197
 
8.0%
Decimal Number 124
 
5.1%
Open Punctuation 29
 
1.2%
Close Punctuation 27
 
1.1%
Uppercase Letter 17
 
0.7%
Math Symbol 5
 
0.2%
Lowercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
113
 
6.8%
79
 
4.8%
48
 
2.9%
45
 
2.7%
42
 
2.5%
39
 
2.4%
39
 
2.4%
38
 
2.3%
38
 
2.3%
35
 
2.1%
Other values (167) 1134
68.7%
Decimal Number
ValueCountFrequency (%)
6 31
25.0%
5 28
22.6%
1 20
16.1%
3 16
12.9%
2 9
 
7.3%
8 8
 
6.5%
4 7
 
5.6%
7 4
 
3.2%
0 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 168
85.3%
. 19
 
9.6%
· 6
 
3.0%
/ 4
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
I 5
29.4%
C 4
23.5%
O 4
23.5%
M 4
23.5%
Lowercase Letter
ValueCountFrequency (%)
c 1
33.3%
o 1
33.3%
m 1
33.3%
Space Separator
ValueCountFrequency (%)
398
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1650
67.3%
Common 780
31.8%
Latin 20
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
113
 
6.8%
79
 
4.8%
48
 
2.9%
45
 
2.7%
42
 
2.5%
39
 
2.4%
39
 
2.4%
38
 
2.3%
38
 
2.3%
35
 
2.1%
Other values (167) 1134
68.7%
Common
ValueCountFrequency (%)
398
51.0%
, 168
21.5%
6 31
 
4.0%
( 29
 
3.7%
5 28
 
3.6%
) 27
 
3.5%
1 20
 
2.6%
. 19
 
2.4%
3 16
 
2.1%
2 9
 
1.2%
Other values (7) 35
 
4.5%
Latin
ValueCountFrequency (%)
I 5
25.0%
C 4
20.0%
O 4
20.0%
M 4
20.0%
c 1
 
5.0%
o 1
 
5.0%
m 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1650
67.3%
ASCII 794
32.4%
None 6
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
398
50.1%
, 168
21.2%
6 31
 
3.9%
( 29
 
3.7%
5 28
 
3.5%
) 27
 
3.4%
1 20
 
2.5%
. 19
 
2.4%
3 16
 
2.0%
2 9
 
1.1%
Other values (13) 49
 
6.2%
Hangul
ValueCountFrequency (%)
113
 
6.8%
79
 
4.8%
48
 
2.9%
45
 
2.7%
42
 
2.5%
39
 
2.4%
39
 
2.4%
38
 
2.3%
38
 
2.3%
35
 
2.1%
Other values (167) 1134
68.7%
None
ValueCountFrequency (%)
· 6
100.0%

hr_pbl_curatr_tot
Categorical

IMBALANCE 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
77 
2
 
5
4
 
4
39(4관 전체)
 
3
11
 
2
Other values (7)

Length

Max length9
Median length4
Mean length3.59
Min length1

Unique

Unique5 ?
Unique (%)5.0%

Sample

1st row39(4관 전체)
2nd row<NA>
3rd row39(4관 전체)
4th row39(4관 전체)
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 77
77.0%
2 5
 
5.0%
4 4
 
4.0%
39(4관 전체) 3
 
3.0%
11 2
 
2.0%
1 2
 
2.0%
8 2
 
2.0%
13 1
 
1.0%
10 1
 
1.0%
0 1
 
1.0%
Other values (2) 2
 
2.0%

Length

2023-12-10T18:39:50.530499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 77
74.8%
2 5
 
4.9%
4 4
 
3.9%
39(4관 3
 
2.9%
전체 3
 
2.9%
11 2
 
1.9%
1 2
 
1.9%
8 2
 
1.9%
13 1
 
1.0%
10 1
 
1.0%
Other values (3) 3
 
2.9%

hr_pbl_pbsvnt_subtot
Text

MISSING 

Distinct9
Distinct (%)69.2%
Missing87
Missing (%)87.0%
Memory size932.0 B
2023-12-10T18:39:50.756284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length3.0769231
Min length1

Characters and Unicode

Total characters40
Distinct characters12
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)46.2%

Sample

1st row27(4관 전체)
2nd row27(4관 전체)
3rd row27(4관 전체)
4th row12
5th row1
ValueCountFrequency (%)
27(4관 3
18.8%
전체 3
18.8%
5 2
12.5%
3 2
12.5%
12 1
 
6.2%
1 1
 
6.2%
24 1
 
6.2%
7 1
 
6.2%
4 1
 
6.2%
15 1
 
6.2%
2023-12-10T18:39:51.283740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 5
12.5%
4 5
12.5%
7 4
10.0%
( 3
7.5%
3
7.5%
3
7.5%
3
7.5%
3
7.5%
) 3
7.5%
5 3
7.5%
Other values (2) 5
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22
55.0%
Other Letter 9
22.5%
Open Punctuation 3
 
7.5%
Space Separator 3
 
7.5%
Close Punctuation 3
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5
22.7%
4 5
22.7%
7 4
18.2%
5 3
13.6%
1 3
13.6%
3 2
 
9.1%
Other Letter
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31
77.5%
Hangul 9
 
22.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 5
16.1%
4 5
16.1%
7 4
12.9%
( 3
9.7%
3
9.7%
) 3
9.7%
5 3
9.7%
1 3
9.7%
3 2
 
6.5%
Hangul
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
77.5%
Hangul 9
 
22.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 5
16.1%
4 5
16.1%
7 4
12.9%
( 3
9.7%
3
9.7%
) 3
9.7%
5 3
9.7%
1 3
9.7%
3 2
 
6.5%
Hangul
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%

hr_pbl_pbsvnt_curatr_crqfc_pos_cnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
91 
10(4관 전체)
 
3
2
 
2
3
 
2
1
 
2

Length

Max length9
Median length4
Mean length3.97
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10(4관 전체)
2nd row<NA>
3rd row10(4관 전체)
4th row10(4관 전체)
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 91
91.0%
10(4관 전체) 3
 
3.0%
2 2
 
2.0%
3 2
 
2.0%
1 2
 
2.0%

Length

2023-12-10T18:39:51.527658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:51.736560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 91
88.3%
10(4관 3
 
2.9%
전체 3
 
2.9%
2 2
 
1.9%
3 2
 
1.9%
1 2
 
1.9%

hr_pbl_irgllbr_subtot
Text

MISSING 

Distinct13
Distinct (%)56.5%
Missing77
Missing (%)77.0%
Memory size932.0 B
2023-12-10T18:39:51.919697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length1
Mean length2.4347826
Min length1

Characters and Unicode

Total characters56
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)26.1%

Sample

1st row297(4관 전체)
2nd row297(4관 전체)
3rd row297(4관 전체)
4th row8
5th row3
ValueCountFrequency (%)
297(4관 3
11.5%
전체 3
11.5%
3 3
11.5%
1 3
11.5%
5 2
7.7%
4 2
7.7%
10 2
7.7%
6 2
7.7%
8 1
 
3.8%
64 1
 
3.8%
Other values (4) 4
15.4%
2023-12-10T18:39:52.368909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 6
 
10.7%
3 6
 
10.7%
2 5
 
8.9%
1 5
 
8.9%
7 4
 
7.1%
9 3
 
5.4%
( 3
 
5.4%
3
 
5.4%
3
 
5.4%
3
 
5.4%
Other values (6) 15
26.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38
67.9%
Other Letter 9
 
16.1%
Open Punctuation 3
 
5.4%
Space Separator 3
 
5.4%
Close Punctuation 3
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 6
15.8%
3 6
15.8%
2 5
13.2%
1 5
13.2%
7 4
10.5%
9 3
7.9%
5 3
7.9%
6 3
7.9%
0 2
 
5.3%
8 1
 
2.6%
Other Letter
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47
83.9%
Hangul 9
 
16.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 6
12.8%
3 6
12.8%
2 5
10.6%
1 5
10.6%
7 4
8.5%
9 3
6.4%
( 3
6.4%
3
6.4%
) 3
6.4%
5 3
6.4%
Other values (3) 6
12.8%
Hangul
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
83.9%
Hangul 9
 
16.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 6
12.8%
3 6
12.8%
2 5
10.6%
1 5
10.6%
7 4
8.5%
9 3
6.4%
( 3
6.4%
3
6.4%
) 3
6.4%
5 3
6.4%
Other values (3) 6
12.8%
Hangul
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%
Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
80 
1
 
8
80(4관 전체)
 
3
2
 
3
3
 
2
Other values (4)
 
4

Length

Max length9
Median length4
Mean length3.66
Min length1

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row80(4관 전체)
2nd row<NA>
3rd row80(4관 전체)
4th row80(4관 전체)
5th row1

Common Values

ValueCountFrequency (%)
<NA> 80
80.0%
1 8
 
8.0%
80(4관 전체) 3
 
3.0%
2 3
 
3.0%
3 2
 
2.0%
39 1
 
1.0%
33 1
 
1.0%
9 1
 
1.0%
. 1
 
1.0%

Length

2023-12-10T18:39:52.630984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:52.836136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 80
77.7%
1 8
 
7.8%
80(4관 3
 
2.9%
전체 3
 
2.9%
2 3
 
2.9%
3 2
 
1.9%
39 1
 
1.0%
33 1
 
1.0%
9 1
 
1.0%
1
 
1.0%

hr_pbl_poigs
Text

MISSING 

Distinct16
Distinct (%)64.0%
Missing75
Missing (%)75.0%
Memory size932.0 B
2023-12-10T18:39:53.064901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length2.32
Min length1

Characters and Unicode

Total characters58
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)40.0%

Sample

1st row81(4관 전체)
2nd row81(4관 전체)
3rd row81(4관 전체)
4th row2
5th row52
ValueCountFrequency (%)
2 4
14.3%
전체 3
10.7%
81(4관 3
10.7%
8 2
 
7.1%
3 2
 
7.1%
23 2
 
7.1%
1 2
 
7.1%
13 1
 
3.6%
7 1
 
3.6%
4 1
 
3.6%
Other values (7) 7
25.0%
2023-12-10T18:39:53.601394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10
17.2%
1 10
17.2%
8 6
10.3%
3 5
8.6%
4 4
 
6.9%
( 3
 
5.2%
3
 
5.2%
3
 
5.2%
3
 
5.2%
3
 
5.2%
Other values (4) 8
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40
69.0%
Other Letter 9
 
15.5%
Open Punctuation 3
 
5.2%
Space Separator 3
 
5.2%
Close Punctuation 3
 
5.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10
25.0%
1 10
25.0%
8 6
15.0%
3 5
12.5%
4 4
 
10.0%
5 3
 
7.5%
0 1
 
2.5%
7 1
 
2.5%
Other Letter
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49
84.5%
Hangul 9
 
15.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
20.4%
1 10
20.4%
8 6
12.2%
3 5
10.2%
4 4
 
8.2%
( 3
 
6.1%
3
 
6.1%
) 3
 
6.1%
5 3
 
6.1%
0 1
 
2.0%
Hangul
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49
84.5%
Hangul 9
 
15.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10
20.4%
1 10
20.4%
8 6
12.2%
3 5
10.2%
4 4
 
8.2%
( 3
 
6.1%
3
 
6.1%
) 3
 
6.1%
5 3
 
6.1%
0 1
 
2.0%
Hangul
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%

hr_pbl_irgllbr
Text

MISSING 

Distinct13
Distinct (%)56.5%
Missing77
Missing (%)77.0%
Memory size932.0 B
2023-12-10T18:39:53.840485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length1
Mean length2.4347826
Min length1

Characters and Unicode

Total characters56
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)26.1%

Sample

1st row297(4관 전체)
2nd row297(4관 전체)
3rd row297(4관 전체)
4th row8
5th row3
ValueCountFrequency (%)
297(4관 3
11.5%
전체 3
11.5%
3 3
11.5%
1 3
11.5%
5 2
7.7%
4 2
7.7%
10 2
7.7%
6 2
7.7%
8 1
 
3.8%
64 1
 
3.8%
Other values (4) 4
15.4%
2023-12-10T18:39:54.253590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 6
 
10.7%
3 6
 
10.7%
2 5
 
8.9%
1 5
 
8.9%
7 4
 
7.1%
9 3
 
5.4%
( 3
 
5.4%
3
 
5.4%
3
 
5.4%
3
 
5.4%
Other values (6) 15
26.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38
67.9%
Other Letter 9
 
16.1%
Open Punctuation 3
 
5.4%
Space Separator 3
 
5.4%
Close Punctuation 3
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 6
15.8%
3 6
15.8%
2 5
13.2%
1 5
13.2%
7 4
10.5%
9 3
7.9%
5 3
7.9%
6 3
7.9%
0 2
 
5.3%
8 1
 
2.6%
Other Letter
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47
83.9%
Hangul 9
 
16.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 6
12.8%
3 6
12.8%
2 5
10.6%
1 5
10.6%
7 4
8.5%
9 3
6.4%
( 3
6.4%
3
6.4%
) 3
6.4%
5 3
6.4%
Other values (3) 6
12.8%
Hangul
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
83.9%
Hangul 9
 
16.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 6
12.8%
3 6
12.8%
2 5
10.6%
1 5
10.6%
7 4
8.5%
9 3
6.4%
( 3
6.4%
3
6.4%
) 3
6.4%
5 3
6.4%
Other values (3) 6
12.8%
Hangul
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%

hr_pbl_intern
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
94 
2
 
3
4
 
2
1
 
1

Length

Max length4
Median length4
Mean length3.82
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 94
94.0%
2 3
 
3.0%
4 2
 
2.0%
1 1
 
1.0%

Length

2023-12-10T18:39:54.479952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:54.661971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 94
94.0%
2 3
 
3.0%
4 2
 
2.0%
1 1
 
1.0%

hr_pbl_volun
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)88.9%
Missing82
Missing (%)82.0%
Infinite0
Infinite (%)0.0%
Mean528.94444
Minimum1
Maximum4667
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:54.826375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q137
median63.5
Q3489
95-th percentile1862
Maximum4667
Range4666
Interquartile range (IQR)452

Descriptive statistics

Standard deviation1126.3665
Coefficient of variation (CV)2.129461
Kurtosis11.735491
Mean528.94444
Median Absolute Deviation (MAD)43.5
Skewness3.262155
Sum9521
Variance1268701.6
MonotonicityNot monotonic
2023-12-10T18:39:55.054229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 2
 
2.0%
40 2
 
2.0%
1231 1
 
1.0%
17 1
 
1.0%
1010 1
 
1.0%
4667 1
 
1.0%
48 1
 
1.0%
609 1
 
1.0%
70 1
 
1.0%
36 1
 
1.0%
Other values (6) 6
 
6.0%
(Missing) 82
82.0%
ValueCountFrequency (%)
1 2
2.0%
17 1
1.0%
23 1
1.0%
36 1
1.0%
40 2
2.0%
48 1
1.0%
57 1
1.0%
70 1
1.0%
74 1
1.0%
101 1
1.0%
ValueCountFrequency (%)
4667 1
1.0%
1367 1
1.0%
1231 1
1.0%
1010 1
1.0%
609 1
1.0%
129 1
1.0%
101 1
1.0%
74 1
1.0%
70 1
1.0%
57 1
1.0%

hr_prv_curatr_tot
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)20.0%
Missing40
Missing (%)40.0%
Infinite0
Infinite (%)0.0%
Mean3.5166667
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:55.257043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q34
95-th percentile10.1
Maximum19
Range18
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.4811437
Coefficient of variation (CV)0.98989869
Kurtosis8.425658
Mean3.5166667
Median Absolute Deviation (MAD)1
Skewness2.7433566
Sum211
Variance12.118362
MonotonicityNot monotonic
2023-12-10T18:39:55.424980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 23
23.0%
1 11
 
11.0%
3 10
 
10.0%
4 4
 
4.0%
5 3
 
3.0%
7 3
 
3.0%
6 1
 
1.0%
19 1
 
1.0%
16 1
 
1.0%
10 1
 
1.0%
Other values (2) 2
 
2.0%
(Missing) 40
40.0%
ValueCountFrequency (%)
1 11
11.0%
2 23
23.0%
3 10
10.0%
4 4
 
4.0%
5 3
 
3.0%
6 1
 
1.0%
7 3
 
3.0%
9 1
 
1.0%
10 1
 
1.0%
12 1
 
1.0%
ValueCountFrequency (%)
19 1
 
1.0%
16 1
 
1.0%
12 1
 
1.0%
10 1
 
1.0%
9 1
 
1.0%
7 3
 
3.0%
6 1
 
1.0%
5 3
 
3.0%
4 4
 
4.0%
3 10
10.0%

hr_prv_curatr_crqfc_pos_cnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
91 
10(4관 전체)
 
3
2
 
2
3
 
2
1
 
2

Length

Max length9
Median length4
Mean length3.97
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10(4관 전체)
2nd row<NA>
3rd row10(4관 전체)
4th row10(4관 전체)
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 91
91.0%
10(4관 전체) 3
 
3.0%
2 2
 
2.0%
3 2
 
2.0%
1 2
 
2.0%

Length

2023-12-10T18:39:55.743684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:55.919444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 91
88.3%
10(4관 3
 
2.9%
전체 3
 
2.9%
2 2
 
1.9%
3 2
 
1.9%
1 2
 
1.9%

hr_prv_curatr_crqfc_non_pos_cnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
78 
8
 
5
4
 
4
1
 
4
29(4관 전체)
 
3
Other values (4)
 
6

Length

Max length9
Median length4
Mean length3.59
Min length1

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row29(4관 전체)
2nd row<NA>
3rd row29(4관 전체)
4th row29(4관 전체)
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 78
78.0%
8 5
 
5.0%
4 4
 
4.0%
1 4
 
4.0%
29(4관 전체) 3
 
3.0%
2 3
 
3.0%
11 1
 
1.0%
5 1
 
1.0%
3 1
 
1.0%

Length

2023-12-10T18:39:56.129170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:56.328632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
75.7%
8 5
 
4.9%
4 4
 
3.9%
1 4
 
3.9%
29(4관 3
 
2.9%
전체 3
 
2.9%
2 3
 
2.9%
11 1
 
1.0%
5 1
 
1.0%
3 1
 
1.0%

hr_prv_non_curatr_exp_cnt
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)26.9%
Missing74
Missing (%)74.0%
Infinite0
Infinite (%)0.0%
Mean3.0384615
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:56.508037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile7.5
Maximum26
Range25
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.9677421
Coefficient of variation (CV)1.6349531
Kurtosis19.895165
Mean3.0384615
Median Absolute Deviation (MAD)1
Skewness4.2952255
Sum79
Variance24.678462
MonotonicityNot monotonic
2023-12-10T18:39:56.668065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 11
 
11.0%
2 9
 
9.0%
3 2
 
2.0%
26 1
 
1.0%
6 1
 
1.0%
4 1
 
1.0%
8 1
 
1.0%
(Missing) 74
74.0%
ValueCountFrequency (%)
1 11
11.0%
2 9
9.0%
3 2
 
2.0%
4 1
 
1.0%
6 1
 
1.0%
8 1
 
1.0%
26 1
 
1.0%
ValueCountFrequency (%)
26 1
 
1.0%
8 1
 
1.0%
6 1
 
1.0%
4 1
 
1.0%
3 2
 
2.0%
2 9
9.0%
1 11
11.0%

hr_prv_rgllbr
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)38.2%
Missing66
Missing (%)66.0%
Infinite0
Infinite (%)0.0%
Mean6.7941176
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:56.829116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q35.75
95-th percentile28.5
Maximum57
Range56
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation12.333201
Coefficient of variation (CV)1.8152763
Kurtosis11.275823
Mean6.7941176
Median Absolute Deviation (MAD)2
Skewness3.3520555
Sum231
Variance152.10784
MonotonicityNot monotonic
2023-12-10T18:39:56.989707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 13
 
13.0%
4 5
 
5.0%
2 3
 
3.0%
3 3
 
3.0%
7 2
 
2.0%
48 1
 
1.0%
14 1
 
1.0%
9 1
 
1.0%
18 1
 
1.0%
12 1
 
1.0%
Other values (3) 3
 
3.0%
(Missing) 66
66.0%
ValueCountFrequency (%)
1 13
13.0%
2 3
 
3.0%
3 3
 
3.0%
4 5
 
5.0%
5 1
 
1.0%
6 1
 
1.0%
7 2
 
2.0%
9 1
 
1.0%
12 1
 
1.0%
14 1
 
1.0%
ValueCountFrequency (%)
57 1
 
1.0%
48 1
 
1.0%
18 1
 
1.0%
14 1
 
1.0%
12 1
 
1.0%
9 1
 
1.0%
7 2
 
2.0%
6 1
 
1.0%
5 1
 
1.0%
4 5
5.0%

hr_prv_intern
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
78 
1
11 
2
3
 
2
4
 
1

Length

Max length4
Median length4
Mean length3.34
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 78
78.0%
1 11
 
11.0%
2 8
 
8.0%
3 2
 
2.0%
4 1
 
1.0%

Length

2023-12-10T18:39:57.198012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:57.386815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
78.0%
1 11
 
11.0%
2 8
 
8.0%
3 2
 
2.0%
4 1
 
1.0%

hr_prv_volun
Text

MISSING 

Distinct9
Distinct (%)60.0%
Missing85
Missing (%)85.0%
Memory size932.0 B
2023-12-10T18:39:57.576495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.5333333
Min length1

Characters and Unicode

Total characters23
Distinct characters7
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)33.3%

Sample

1st row12
2nd row1
3rd row4
4th row20
5th row수시
ValueCountFrequency (%)
1 3
20.0%
수시 3
20.0%
4 2
13.3%
2 2
13.3%
12 1
 
6.7%
20 1
 
6.7%
454 1
 
6.7%
5 1
 
6.7%
15 1
 
6.7%
2023-12-10T18:39:58.018573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
21.7%
4 4
17.4%
2 4
17.4%
3
13.0%
3
13.0%
5 3
13.0%
0 1
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
73.9%
Other Letter 6
 
26.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
29.4%
4 4
23.5%
2 4
23.5%
5 3
17.6%
0 1
 
5.9%
Other Letter
ValueCountFrequency (%)
3
50.0%
3
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17
73.9%
Hangul 6
 
26.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
29.4%
4 4
23.5%
2 4
23.5%
5 3
17.6%
0 1
 
5.9%
Hangul
ValueCountFrequency (%)
3
50.0%
3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
73.9%
Hangul 6
 
26.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
29.4%
4 4
23.5%
2 4
23.5%
5 3
17.6%
0 1
 
5.9%
Hangul
ValueCountFrequency (%)
3
50.0%
3
50.0%

rm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

lst_updt_dt
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210210133559
100 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210210133559
2nd row20210210133559
3rd row20210210133559
4th row20210210133559
5th row20210210133559

Common Values

ValueCountFrequency (%)
20210210133559 100
100.0%

Length

2023-12-10T18:39:58.213400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:58.378673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210210133559 100
100.0%

data_orgn
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
문화데이터총람2020
100 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row문화데이터총람2020
2nd row문화데이터총람2020
3rd row문화데이터총람2020
4th row문화데이터총람2020
5th row문화데이터총람2020

Common Values

ValueCountFrequency (%)
문화데이터총람2020 100
100.0%

Length

2023-12-10T18:39:58.529673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:58.693023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화데이터총람2020 100
100.0%

file_name
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_478_DMSTC_MCST_ARTGR_2021
100 

Length

Max length28
Median length28
Mean length28
Min length28

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_478_DMSTC_MCST_ARTGR_2021
2nd rowKC_478_DMSTC_MCST_ARTGR_2021
3rd rowKC_478_DMSTC_MCST_ARTGR_2021
4th rowKC_478_DMSTC_MCST_ARTGR_2021
5th rowKC_478_DMSTC_MCST_ARTGR_2021

Common Values

ValueCountFrequency (%)
KC_478_DMSTC_MCST_ARTGR_2021 100
100.0%

Length

2023-12-10T18:39:58.843915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:59.000309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_478_dmstc_mcst_artgr_2021 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20200101
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200101
2nd row20200101
3rd row20200101
4th row20200101
5th row20200101

Common Values

ValueCountFrequency (%)
20200101 100
100.0%

Length

2023-12-10T18:39:59.154733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:59.292821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200101 100
100.0%

Sample

idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdsdivregist_yncttpcopnngdtregist_sttsregist_dtregist_noosvc_addrosvc_av_gud_prvd_ynosvc_av_gud_feeosvc_mssys_prvd_ynplot_aeabuld_totarehbll_aeashlf_aeaedu_plce_aeaofce_aeadata_lbr_booth_aeadata_lbr_cntplan_spc_ehbll_cntprgrm_totfyer_opn_dt_totfyer_usemem_totdyrg_usemem_cntgnrl_feepre_schl_gnrl_feeele_schl_gnrl_feemid_hi_gnrl_feeage_19_25_gnrl_feegrp_gnrl_fee_dcrateetc_gnrl_fee_dcrategnrl_fee_dc_policygnrl_fee_free_trgtspc_feepre_schl_spc_feepre_ele_schl_spc_feemid_hi_spc_feeage_19_25_spc_feegrp_spc_fee_dcrateetc_spc_fee_dcratespc_fee_dc_policyspc_fee_free_trgthr_pbl_curatr_tothr_pbl_pbsvnt_subtothr_pbl_pbsvnt_curatr_crqfc_pos_cnthr_pbl_irgllbr_subtothr_pbl_irgllbr_curatr_crqfc_pos_cnthr_pbl_poigshr_pbl_irgllbrhr_pbl_internhr_pbl_volunhr_prv_curatr_tothr_prv_curatr_crqfc_pos_cnthr_prv_curatr_crqfc_non_pos_cnthr_prv_non_curatr_exp_cnthr_prv_rgllbrhr_prv_internhr_prv_volunrmlst_updt_dtdata_orgnfile_namebase_ymd
0KCDMART21N000000001문화시설미술관국립현대미술관(과천)경기도과천시4129010400막계동4129056000문원동113203000004경기 과천시 광명로 31313829다사57536937.431003127.01993국립등록02-2188-61141986.08.25.Y2017.12.14.국립13-2017-07호www.mmca.go.kr, ,www.facebook.com/MMCAKorea, www.instagram.com/MMCAKorea, ,www.twitter.com/MMCAKOREA, www.youtube.com/MMCAKorea, tv.naver.com/mmcaY1000Y6691637796.8139413899.012863533.01172.040510연 9회61(3관 전체)3126478052076.298077<NA><NA><NA><NA><NA><NA><NA><NA><NA>기획전시별 별도 책정,(2,000원~3,000원 수준)<NA><NA><NA><NA>2020~50현대카드 플래티넘 회원 50% (동반 1인 포함, 월5회, 해당 카드결제 시),아시아나클럽 일반회원 20% (카드제시자에 한함),SPC 해피포인트 회원 50% 할인(앱 쿠폰 인증 회원)1.일반,만24세 이하 또는 만65세 이상,대학생,국가유공자·독립유공자(유공자증 소지시 본인 및 동반가족),국가유공자·독립유공자 유족증 소지자,미술관에 미술작품 등의 자료 기증자(기증자 카드 소지시 본인 및 동반가족) ,국립현대미술관 유료회원,박물관·미술관 학예사 자격 취득자,예술인패스 소지자,ICOM(국제박물관협의회)카드 소지자,학생인솔교사 및 관광안내사(사전예약 단체에 한함),장애인 및 동행보호자,기초수급 대상자 및 차상위 계층(증명서 제시자에 한함),,2.제휴사,현대카드 프리미엄 회원 (동반 1인 포함, 월5회, 해당 카드 결제시),아시아나클럽 우수회원 카드(카드제시자에 한함,,3.매월 마지막 수요일 문화가 있는 날39(4관 전체)27(4관 전체)10(4관 전체)297(4관 전체)80(4관 전체)81(4관 전체)297(4관 전체)<NA>70<NA>10(4관 전체)29(4관 전체)<NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
1KCDMART21N000000268문화시설미술관제주조각공원제주특별자치도서귀포시5013031026안덕면 덕수리5013031000안덕면501303349236제주특별자치도 서귀포시 안덕면 일주서로 183663527나나90374633.257451126.322517사립등록010-8875-81741987.10.01.Y2007.08.30.제주-사립13-2007-10호www.jejuartpark.comN<NA>N4122861688.12354<NA><NA><NA><NA><NA><NA><NA>30036000100.0<NA><NA><NA><NA><NA><NA><NA><NA>전체<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
2KCDMART21N000000003문화시설미술관국립현대미술관(덕수궁)서울특별시중구1114016700정동1114052000소공동113203000004서울 중구 세종대로 994519다사53651937.565937126.975035국립등록02-2022-06001998.12.01.Y2017.12.14.국립13-2017-09호www.mmca.go.kr, www.facebook.com/MMCAKorea, ,www.instagram.com/MMCAKorea, www.twitter.com/MMCAKOREA,, www.youtube.com/MMCAKorea, tv.naver.com/mmcaY1000Y118134281212275.07864.0<NA><NA>연 3회61(3관 전체)2754520241644.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>기획전시별 별도 책정,(2,000원~3,000원 수준),* 덕수궁 입장료 제외<NA><NA><NA><NA>2020~50현대카드 플래티넘 회원 50% (동반 1인 포함, 월5회, 해당 카드결제 시),아시아나클럽 일반회원 20% (카드제시자에 한함),SPC 해피포인트 회원 50% 할인(앱 쿠폰 인증 회원)1.일반,만24세 이하 또는 만65세 이상,대학생,국가유공자·독립유공자(유공자증 소지시 본인 및 동반가족),국가유공자·독립유공자 유족증 소지자,미술관에 미술작품 등의 자료 기증자(기증자 카드 소지시 본인 및 동반가족) ,국립현대미술관 유료회원,박물관·미술관 학예사 자격 취득자,예술인패스 소지자,ICOM(국제박물관협의회)카드 소지자,학생인솔교사 및 관광안내사(사전예약 단체에 한함),장애인 및 동행보호자,기초수급 대상자 및 차상위 계층(증명서 제시자에 한함),,2.제휴사,현대카드 프리미엄 회원 (동반 1인 포함, 월5회, 해당 카드 결제시),아시아나클럽 우수회원 카드(카드제시자에 한함,,3.매월 마지막 수요일 문화가 있는 날39(4관 전체)27(4관 전체)10(4관 전체)297(4관 전체)80(4관 전체)81(4관 전체)297(4관 전체)<NA>40<NA>10(4관 전체)29(4관 전체)<NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
3KCDMART21N000000004문화시설미술관국립현대미술관 미술품수장센터(청주)충청북도청주시4311410200내덕동4311453000내덕2동431143236027충북 청주시 청원구 상당로 31428501다바99350936.656196127.492382국립미등록043-261-14002018.12.27N미등록미등록www.mmca.go.kr, www.facebook.com/MMCAKorea, ,www.instagram.com/MMCAKorea, www.twitter.com/MMCAKOREA,, www.youtube.com/MMCAKorea, tv.naver.com/mmcaN<NA>N120771986510547361.0295639.072.0744연1회36310222881719.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>전체39(4관 전체)27(4관 전체)10(4관 전체)297(4관 전체)80(4관 전체)81(4관 전체)297(4관 전체)<NA>1367<NA>10(4관 전체)29(4관 전체)<NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
4KCDMART21N000000005문화시설미술관겸재정선미술관서울특별시강서구1150010400가양동1150060300가양1동115004145407서울 강서구 양천로47길 367522다사41552737.572223126.838412공립등록02-2659-22062009.04.23.Y2014.02.14.서울-공립13-2014-03호www.gjjs.or.krN<NA>N35613305606109.034374.020.02691연10회3229685448289.01000<NA>500500100030~4035허준박물관-겸재정선미술관 통합관람권(35%), 제로페이 성인 입장객(2019. 8. 1 ~ 12. 31까지 30%할인), 문화가 있는 날 야간 무료입장 등미취학 6세이하, 65세이상 어르신,,장애인, 국가유공자, 독립유공자, 장애인, 다둥이행복카드 소지자, 투표확인증 제출자 등1000<NA>500500100030~4030허준박물관-겸재정선미술관 통합관람권(35%), 제로페이 성인 입장객(2019. 8. 1 ~ 12. 31까지 30%할인), 문화가 있는 날 야간 무료입장 등미취학 6세이하, 65세이상 어르신,,장애인, 국가유공자, 독립유공자, 장애인, 다둥이행복카드 소지자, 투표확인증 제출자 등<NA><NA><NA>81<NA>8<NA>57<NA><NA><NA><NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
5KCDMART21N000000006문화시설미술관남서울미술관서울특별시관악구1162010300남현동1162063000남현동116202000003서울 관악구 남부순환로 20768806다사53941937.476053126.979466공립등록02-598-62452004.09.02.Y2005.03.11.서울-공립13-2005-01호http://sema.seoul.go.kr/Y무료Y34491570546<NA>157170.0<NA><NA><NA><NA><NA>112113500.0<NA><NA><NA><NA><NA><NA><NA><NA>전체<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3<NA>23<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
6KCDMART21N000000007문화시설미술관서울시립미술관서울특별시중구1114016600서소문동1114052000소공동116202000003서울 중구 덕수궁길 614515다사53551737.564106126.973699공립등록02-2124-88001988.08.19.Y1999.03.15.서울-공립13-1999-01호http://sema.seoul.go.kr/Y무료Y25402134333256870.057920213.0205.038686<NA>30<NA>11478264723.0<NA><NA><NA><NA><NA><NA><NA><NA>전체15000<NA>1000013000<NA><NA><NA>*특별할인: 다둥이행복카드, 문화가 있는 날 (50%/6시 이후 발권),*제휴할인: 카카오/제로페이 결제시 20%,*단체: 20인 이상 인솔자 1명 무료,*특별권: 만 65세 이상, 장애인 4~6급, 미취학 아동, 국가/독립유공자유족증 소유자, 의사상자유족, 서울명예시민증 소유자<NA>1312264395264<NA>74<NA>211<NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
7KCDMART21N000000269문화시설미술관빛의 벙커 (제주 성산 AMIEX 전시관)제주특별자치도서귀포시5013025924성산읍 고성리5013025900성산읍501304850416제주특별자치도 서귀포시 성산읍 서성일로1168번길 89-1763641다나44294333.439645126.89982사립미등록1522-26532018.11.16N미등록미등록www.bunkerdelumieres.comN<NA>Y2979.152979.151380<NA><NA>104.0<NA><NA>연 1회<NA>3266238881900.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>150008000900011000150000.150.2도민 할인, 제휴처 할인 등36개월 미만 유아<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
8KCDMART21N000000009문화시설미술관종로구립 박노수미술관서울특별시종로구1111011100옥인동1111051500청운효자동111104100205서울 종로구 옥인1길 343034다사52953637.581319126.966819공립등록02-2148-41712013.09.11.Y2013.08.13.서울-공립13-2013-07호https://www.jfac.or.kr/site/main/content/parkns01N<NA>N95735119197.0<NA>12.0<NA><NA>연1회22992483483.03000<NA>12001800180040 (어른 40, 청소년 33, 어린이 50)50종로구민(50% 할인), 한복착용(50% 할인), 문화가 있는 날(50% 할인)국빈·외교사절단 및 수행자, 6세 이하 어린이, 만 65세 이상, 장애인 및 보호자, 국가유공자와 그 유족 또는 가족, 기초수급자, 다둥이행복카드 소지자 및 가족, 종로구 명예구민, 연구 및 공무수행<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA>3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
9KCDMART21N000000010문화시설미술관종로구립 고희동미술관서울특별시종로구1111014900원서동1111060000가회동111104100426서울 종로구 창덕궁5길 403051다사54853837.583133126.988964공립등록02-741-81492017.11.29Y2017.11.29서울-공립21-2017-04호www.jfac.or.krN<NA>N540.2162833.0<NA>3.0<NA><NA>연1회23102009965.0<NA><NA><NA><NA><NA><NA><NA><NA>전체<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>52<NA>5<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
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90KCDMART21N000000091문화시설미술관성남큐브미술관경기도성남시4113510700야탑동4113564000야탑3동411352000005경기 성남시 분당구 성남대로 80813514다사67333837.402957127.13056공립등록031-783-80002010.08.06Y2012.9.5경기-공립21-2012-09호http://www.snab.or.krN<NA>N113150231131132.0<NA>85.0<NA><NA>연9회<NA>23030660133.0<NA><NA><NA><NA><NA><NA><NA><NA>전체3000전체전체전체3000<NA><NA>20인 이상 단체할인 1,000원,성남문화재단 유료회원 할인 1,000원36개월 미만, 65세 이상, 장애 2급 이상<NA>3<NA>1<NA>712<NA><NA><NA><NA><NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
91KCDMART21N000000092문화시설미술관수원시립아이파크미술관경기도수원시4111513000신풍동4111574000행궁동411153012006경기 수원시 팔달구 정조로 83316252다사57020537.282705127.015825공립등록031-228-38002015.10.08Y2017.11.21경기-공립13-2017-05호suma.suwon.go.krY무료Y640496612059790.0219199.0110.03712연6회25310102843331.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>400010002000200040005025~50수원시민(25%), 다자녀, 자원봉사카드소지자, 수원시카톡친구(50%)만65세이상 어르신, 장애인(1~급), 기초수급자, 국가보훈대상자 등<NA>15<NA>4<NA>224<NA>4667<NA><NA><NA><NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
92KCDMART21N000000093문화시설미술관양주시립장욱진미술관경기도양주시4163034024장흥면 석현리4163034000장흥면416303212007경기 양주시 장흥면 권율로 19311519다사51470437.732816126.94925공립등록031-8082-42452014.04.28Y2014.07.08.경기-공립13-2014-03호http://changucchin.yangju.go.kr/YOY11278.991851.58482107.015860.045.0300연6회2330085720285.05000<NA>10001000500020<NA>문화가있는날 무료영유아, 노인5000<NA>10001000500020<NA>문화가있는날 무료영유아, 노인13<NA>5215<NA><NA><NA><NA>1<NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
93KCDMART21N000000094문화시설미술관양평군립미술관경기도양평군4183025021양평읍 양근리4183025000양평읍418304451442경기 양평군 양평읍 문화복지길 212546다사98544237.497099127.483999공립등록031-775-85152011.12.16.Y2012.12.17.경기-공립21-2012-11호www.ymuseum.orgN<NA>N806941851685113.027570.062.085613회24243224111619.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>10005005007001000<NA><NA>문화가 있는 날 무료입장(100%),그린카드 소지자 1인 무료 입장,예술인패스 30%군인, 경로, 장애인, 유공자, 양평군민,36개월미만유아<NA><NA><NA>62<NA>6<NA>1010<NA><NA><NA><NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
94KCDMART21N000000095문화시설미술관여주세계생활도자관경기도여주시4167012000천송동4167053000오학동416704442277경기 여주시 신륵사길 712636라사13622337.300145127.654546공립등록031-884-86442001.07.01Y2007.12.20경기-사립12-2007-13호<NA><NA><NA><NA>7149285799099.082.566.0<NA>72<NA>1023249479213.0<NA><NA><NA><NA><NA><NA><NA><NA>전체<NA><NA><NA><NA><NA><NA><NA><NA><NA>2<NA>1<NA>.<NA><NA><NA><NA><NA>11<NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
95KCDMART21N000000096문화시설미술관오산시립미술관경기도오산시4137010900은계동4137051000중앙동413703198046경기 오산시 현충로 10018131다사62406937.160222127.077081공립등록031-379-99402012.07.01.Y2017.12.01경기-공립21-2017-06호www.osan.go.kr/artsN<NA>N41603164606137.1280180.030.0<NA>연5회53102700087.0<NA><NA><NA><NA><NA><NA><NA><NA>전체<NA><NA><NA><NA><NA><NA><NA><NA>전체2<NA>1<NA><NA>2<NA><NA><NA><NA>11<NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
96KCDMART21N000000097문화시설미술관이천시립월전미술관경기도이천시4150010200관고동4150053000관고동415004421057경기 이천시 경충대로2709번길 18517379다사93220137.280167127.424047공립등록031-637-0032/32007.08.14.Y2008.03.31경기-공립13-2008-05호http://www.iwoljeon.org/Y무료N95052008637106.7478219.0<NA><NA>연8회73032607086.0396042000<NA>60010001000<NA>30~50그린카드 예술인패스(30%),이천시민 교류도시 군부대장병및가족 명예시민(50%)만65세이상, 만6세이하, 국가유공자및유족, 독립유공자및유족, 518민주유공자및유족, 장애인2000<NA>60010001000<NA>30%,50%그린카드 예술인패스(30%),이천시민 교류도시 군부대장병및가족 명예시민(50%)만65세이상, 만6세이하, 국가유공자및유족, 독립유공자및유족, 518민주유공자및유족, 장애인<NA><NA><NA>63<NA>6<NA>17<NA><NA><NA><NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
97KCDMART21N000000098문화시설미술관C아트뮤지엄경기도양평군4183038028양동면 단석리4183038000양동면418304451226경기 양평군 양동면 다락근이길 57-1312538라사21032837.394888127.737335사립등록031-775-69452006.02.07Y2006.12.29경기-사립13-2006-08호http://www.cartmuseum.com/N<NA>N225.4193219.581803147.0332185.0196.020001-2회<NA>3651600405.0700050005000700070003030교회단체 30%할인<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA>34<NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
98KCDMART21N000000099문화시설미술관CICA미술관경기도김포시4157025626양촌읍 학운리4157025600양촌읍415703209064경기 김포시 양촌읍 삼도로 196-3010049다사20356937.608197126.597774사립등록031-988-63632015.07.31.Y2015.07.07경기-사립13-2015-05호www.cicamuseum.comN<NA>N495870040066.06620.0<NA>300연17회426013005.07000<NA>500060007000<NA><NA>해당없음해당없음<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA>21<NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101
99KCDMART21N000000100문화시설미술관가일미술관경기도가평군4182032527청평면 삼회리4182032500청평면418203216053경기 가평군 청평면 북한강로 154912458다사89362337.660416127.379434사립등록031-584-47222003.05.02.Y2005.02.17경기-사립13-2005-03호<NA>N<NA>N1348889540150.0180150.0<NA><NA><NA><NA>2508754.03000<NA>2000300030002050단체 가이드 진행 인당 2,000원해당없음<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA><NA>20210210133559문화데이터총람2020KC_478_DMSTC_MCST_ARTGR_202120200101