Overview

Dataset statistics

Number of variables48
Number of observations100
Missing cells477
Missing cells (%)9.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.1 KiB
Average record size in memory400.3 B

Variable types

Text24
Categorical11
Numeric12
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
cmplx_seats has 55 (55.0%) missing valuesMissing
cmplx_aea has 54 (54.0%) missing valuesMissing
prfplc_seats has 12 (12.0%) missing valuesMissing
prfplc_aea has 12 (12.0%) missing valuesMissing
sl_prfplc_seats has 39 (39.0%) missing valuesMissing
sl_prfplc_aea has 39 (39.0%) missing valuesMissing
ehbll_aea has 22 (22.0%) missing valuesMissing
edu_plce_aea has 27 (27.0%) missing valuesMissing
mtg_rum_aea has 42 (42.0%) missing valuesMissing
feld_prfplc_aea has 52 (52.0%) missing valuesMissing
ehbll_dt_cnt has 19 (19.0%) missing valuesMissing
stag_pchrg_cnt has 4 (4.0%) missing valuesMissing
rm has 100 (100.0%) missing valuesMissing
id has unique valuesUnique
fclt_name has unique valuesUnique
rdnm_addr has unique valuesUnique
grid_cd has unique valuesUnique
x_cd has unique valuesUnique
y_cd has unique valuesUnique
opnngdt has unique valuesUnique
totar has unique valuesUnique
usemem_tot has unique valuesUnique
rm is an unsupported type, check if it needs cleaning or further analysisUnsupported
exp_emp_cnt has 5 (5.0%) zerosZeros
fyer_orpns has 3 (3.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:07:19.742766
Analysis finished2023-12-10 10:07:22.377511
Duration2.63 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
2023-12-10T19:07:22.611076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
Distinct characters16
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 rowKCDMSMC21N000000001
2nd rowKCDMSMC21N000000254
3rd rowKCDMSMC21N000000003
4th rowKCDMSMC21N000000004
5th rowKCDMSMC21N000000005
ValueCountFrequency (%)
kcdmsmc21n000000001 1
 
1.0%
kcdmsmc21n000000063 1
 
1.0%
kcdmsmc21n000000074 1
 
1.0%
kcdmsmc21n000000073 1
 
1.0%
kcdmsmc21n000000072 1
 
1.0%
kcdmsmc21n000000071 1
 
1.0%
kcdmsmc21n000000070 1
 
1.0%
kcdmsmc21n000000069 1
 
1.0%
kcdmsmc21n000000068 1
 
1.0%
kcdmsmc21n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:07:23.307216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 714
37.6%
C 200
 
10.5%
M 200
 
10.5%
2 121
 
6.4%
1 121
 
6.4%
K 100
 
5.3%
D 100
 
5.3%
S 100
 
5.3%
N 100
 
5.3%
5 24
 
1.3%
Other values (6) 120
 
6.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 714
64.9%
2 121
 
11.0%
1 121
 
11.0%
5 24
 
2.2%
4 21
 
1.9%
6 21
 
1.9%
7 20
 
1.8%
9 20
 
1.8%
3 19
 
1.7%
8 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
C 200
25.0%
M 200
25.0%
K 100
12.5%
D 100
12.5%
S 100
12.5%
N 100
12.5%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 714
64.9%
2 121
 
11.0%
1 121
 
11.0%
5 24
 
2.2%
4 21
 
1.9%
6 21
 
1.9%
7 20
 
1.8%
9 20
 
1.8%
3 19
 
1.7%
8 19
 
1.7%
Latin
ValueCountFrequency (%)
C 200
25.0%
M 200
25.0%
K 100
12.5%
D 100
12.5%
S 100
12.5%
N 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 714
37.6%
C 200
 
10.5%
M 200
 
10.5%
2 121
 
6.4%
1 121
 
6.4%
K 100
 
5.3%
D 100
 
5.3%
S 100
 
5.3%
N 100
 
5.3%
5 24
 
1.3%
Other values (6) 120
 
6.3%

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

2023-12-10T19:07:23.585741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:23.743353image/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
문예회관
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문예회관 100
100.0%

Length

2023-12-10T19:07:23.933358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:24.105299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문예회관 100
100.0%

fclt_name
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:07:24.500532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.08
Min length5

Characters and Unicode

Total characters708
Distinct characters140
Distinct categories5 ?
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 row강동아트센터
2nd row제주특별자치도 문예회관
3rd row관악문화관도서관
4th row나루아트센터
5th row구로아트밸리 예술극장
ValueCountFrequency (%)
강동아트센터 1
 
0.9%
강화문예회관 1
 
0.9%
수원sk아트리움 1
 
0.9%
경기아트센터 1
 
0.9%
세종문화예술회관 1
 
0.9%
울주문화예술회관 1
 
0.9%
북구문화예술회관 1
 
0.9%
꽃바위문화관 1
 
0.9%
중구문화의전당 1
 
0.9%
울산문화예술회관 1
 
0.9%
Other values (97) 97
90.7%
2023-12-10T19:07:25.264163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55
 
7.8%
52
 
7.3%
49
 
6.9%
46
 
6.5%
31
 
4.4%
29
 
4.1%
27
 
3.8%
25
 
3.5%
23
 
3.2%
23
 
3.2%
Other values (130) 348
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 695
98.2%
Space Separator 7
 
1.0%
Decimal Number 3
 
0.4%
Uppercase Letter 2
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
55
 
7.9%
52
 
7.5%
49
 
7.1%
46
 
6.6%
31
 
4.5%
29
 
4.2%
27
 
3.9%
25
 
3.6%
23
 
3.3%
23
 
3.3%
Other values (123) 335
48.2%
Decimal Number
ValueCountFrequency (%)
5 1
33.3%
1 1
33.3%
8 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 695
98.2%
Common 11
 
1.6%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
55
 
7.9%
52
 
7.5%
49
 
7.1%
46
 
6.6%
31
 
4.5%
29
 
4.2%
27
 
3.9%
25
 
3.6%
23
 
3.3%
23
 
3.3%
Other values (123) 335
48.2%
Common
ValueCountFrequency (%)
7
63.6%
5 1
 
9.1%
· 1
 
9.1%
1 1
 
9.1%
8 1
 
9.1%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 695
98.2%
ASCII 12
 
1.7%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
55
 
7.9%
52
 
7.5%
49
 
7.1%
46
 
6.6%
31
 
4.5%
29
 
4.2%
27
 
3.9%
25
 
3.6%
23
 
3.3%
23
 
3.3%
Other values (123) 335
48.2%
ASCII
ValueCountFrequency (%)
7
58.3%
S 1
 
8.3%
K 1
 
8.3%
5 1
 
8.3%
1 1
 
8.3%
8 1
 
8.3%
None
ValueCountFrequency (%)
· 1
100.0%

ctprvn_nm
Categorical

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기도
29 
서울특별시
19 
대구광역시
11 
부산광역시
10 
인천광역시
10 
Other values (5)
21 

Length

Max length7
Median length5
Mean length4.5
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 29
29.0%
서울특별시 19
19.0%
대구광역시 11
 
11.0%
부산광역시 10
 
10.0%
인천광역시 10
 
10.0%
광주광역시 7
 
7.0%
대전광역시 5
 
5.0%
울산광역시 5
 
5.0%
제주특별자치도 3
 
3.0%
세종특별자치시 1
 
1.0%

Length

2023-12-10T19:07:25.527863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:25.777782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 29
29.0%
서울특별시 19
19.0%
대구광역시 11
 
11.0%
부산광역시 10
 
10.0%
인천광역시 10
 
10.0%
광주광역시 7
 
7.0%
대전광역시 5
 
5.0%
울산광역시 5
 
5.0%
제주특별자치도 3
 
3.0%
세종특별자치시 1
 
1.0%
Distinct54
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:07:26.202152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.84
Min length2

Characters and Unicode

Total characters284
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)33.0%

Sample

1st row강동구
2nd row제주시
3rd row관악구
4th row광진구
5th row구로구
ValueCountFrequency (%)
서구 7
 
7.0%
남구 6
 
6.0%
중구 6
 
6.0%
북구 5
 
5.0%
파주시 4
 
4.0%
동구 4
 
4.0%
용인시 3
 
3.0%
고양시 3
 
3.0%
평택시 3
 
3.0%
수원시 3
 
3.0%
Other values (44) 56
56.0%
2023-12-10T19:07:26.834005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66
23.2%
33
 
11.6%
12
 
4.2%
10
 
3.5%
10
 
3.5%
9
 
3.2%
8
 
2.8%
8
 
2.8%
6
 
2.1%
6
 
2.1%
Other values (55) 116
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 284
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
66
23.2%
33
 
11.6%
12
 
4.2%
10
 
3.5%
10
 
3.5%
9
 
3.2%
8
 
2.8%
8
 
2.8%
6
 
2.1%
6
 
2.1%
Other values (55) 116
40.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 284
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
66
23.2%
33
 
11.6%
12
 
4.2%
10
 
3.5%
10
 
3.5%
9
 
3.2%
8
 
2.8%
8
 
2.8%
6
 
2.1%
6
 
2.1%
Other values (55) 116
40.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 284
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
66
23.2%
33
 
11.6%
12
 
4.2%
10
 
3.5%
10
 
3.5%
9
 
3.2%
8
 
2.8%
8
 
2.8%
6
 
2.1%
6
 
2.1%
Other values (55) 116
40.8%

legaldong_cd
Real number (ℝ)

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9580181 × 109
Minimum1.1110115 × 109
Maximum5.0130106 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:27.168694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110115 × 109
5-th percentile1.1200114 × 109
Q12.6342605 × 109
median2.8910185 × 109
Q34.1177355 × 109
95-th percentile4.1590134 × 109
Maximum5.0130106 × 109
Range3.9019991 × 109
Interquartile range (IQR)1.483475 × 109

Descriptive statistics

Standard deviation1.0923467 × 109
Coefficient of variation (CV)0.3692833
Kurtosis-0.69830851
Mean2.9580181 × 109
Median Absolute Deviation (MAD)1.2202948 × 109
Skewness-0.32925621
Sum2.9580181 × 1011
Variance1.1932213 × 1018
MonotonicityNot monotonic
2023-12-10T19:07:27.507069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1153010200 2
 
2.0%
4148012200 2
 
2.0%
2629010600 2
 
2.0%
2818510600 2
 
2.0%
3017012800 2
 
2.0%
1174010300 1
 
1.0%
3111010900 1
 
1.0%
4128110100 1
 
1.0%
4111513600 1
 
1.0%
4111113000 1
 
1.0%
Other values (85) 85
85.0%
ValueCountFrequency (%)
1111011500 1
1.0%
1111011900 1
1.0%
1114016300 1
1.0%
1117013000 1
1.0%
1120010700 1
1.0%
1120011400 1
1.0%
1121510500 1
1.0%
1132010700 1
1.0%
1135010600 1
1.0%
1138010200 1
1.0%
ValueCountFrequency (%)
5013010600 1
1.0%
5011012000 1
1.0%
5011010200 1
1.0%
4161010300 1
1.0%
4159026221 1
1.0%
4159012700 1
1.0%
4159011700 1
1.0%
4157010600 1
1.0%
4148025023 1
1.0%
4148012200 2
2.0%
Distinct94
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:07:28.105962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.39
Min length2

Characters and Unicode

Total characters339
Distinct characters120
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

Unique88 ?
Unique (%)88.0%

Sample

1st row상일동
2nd row일도이동
3rd row신림동
4th row자양동
5th row구로동
ValueCountFrequency (%)
와동동 2
 
1.9%
송도동 2
 
1.9%
송정동 2
 
1.9%
만년동 2
 
1.9%
구로동 2
 
1.9%
대연동 2
 
1.9%
연암동 1
 
0.9%
성사동 1
 
0.9%
상일동 1
 
0.9%
달동 1
 
0.9%
Other values (91) 91
85.0%
2023-12-10T19:07:28.899460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93
27.4%
8
 
2.4%
8
 
2.4%
8
 
2.4%
8
 
2.4%
7
 
2.1%
7
 
2.1%
5
 
1.5%
5
 
1.5%
5
 
1.5%
Other values (110) 185
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 326
96.2%
Space Separator 7
 
2.1%
Decimal Number 6
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
93
28.5%
8
 
2.5%
8
 
2.5%
8
 
2.5%
8
 
2.5%
7
 
2.1%
5
 
1.5%
5
 
1.5%
5
 
1.5%
5
 
1.5%
Other values (106) 174
53.4%
Decimal Number
ValueCountFrequency (%)
3 3
50.0%
2 2
33.3%
1 1
 
16.7%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 326
96.2%
Common 13
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
93
28.5%
8
 
2.5%
8
 
2.5%
8
 
2.5%
8
 
2.5%
7
 
2.1%
5
 
1.5%
5
 
1.5%
5
 
1.5%
5
 
1.5%
Other values (106) 174
53.4%
Common
ValueCountFrequency (%)
7
53.8%
3 3
23.1%
2 2
 
15.4%
1 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 326
96.2%
ASCII 13
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
93
28.5%
8
 
2.5%
8
 
2.5%
8
 
2.5%
8
 
2.5%
7
 
2.1%
5
 
1.5%
5
 
1.5%
5
 
1.5%
5
 
1.5%
Other values (106) 174
53.4%
ASCII
ValueCountFrequency (%)
7
53.8%
3 3
23.1%
2 2
 
15.4%
1 1
 
7.7%

adstrd_cd
Real number (ℝ)

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9580634 × 109
Minimum1.111053 × 109
Maximum5.013054 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:29.296306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111053 × 109
5-th percentile1.1200646 × 109
Q12.634303 × 109
median2.891049 × 109
Q34.1177875 × 109
95-th percentile4.1590533 × 109
Maximum5.013054 × 109
Range3.902001 × 109
Interquartile range (IQR)1.4834845 × 109

Descriptive statistics

Standard deviation1.0923435 × 109
Coefficient of variation (CV)0.36927655
Kurtosis-0.6983024
Mean2.9580634 × 109
Median Absolute Deviation (MAD)1.2203126 × 109
Skewness-0.32925641
Sum2.9580634 × 1011
Variance1.1932142 × 1018
MonotonicityNot monotonic
2023-12-10T19:07:29.700813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1153056000 2
 
2.0%
4148055000 2
 
2.0%
3017065000 2
 
2.0%
1111053000 2
 
2.0%
1174052000 1
 
1.0%
3111065000 1
 
1.0%
4128151000 1
 
1.0%
4111566000 1
 
1.0%
4111157100 1
 
1.0%
4111573000 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
1111053000 2
2.0%
1114061500 1
1.0%
1117065000 1
1.0%
1120056000 1
1.0%
1120065000 1
1.0%
1121584000 1
1.0%
1132051500 1
1.0%
1135061900 1
1.0%
1138051000 1
1.0%
1141068500 1
1.0%
ValueCountFrequency (%)
5013054000 1
1.0%
5011064000 1
1.0%
5011052000 1
1.0%
4161052000 1
1.0%
4159058500 1
1.0%
4159053000 1
1.0%
4159026200 1
1.0%
4157054000 1
1.0%
4148055000 2
2.0%
4148051000 1
1.0%
Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:07:30.247971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.6
Min length2

Characters and Unicode

Total characters360
Distinct characters115
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

Unique91 ?
Unique (%)91.0%

Sample

1st row상일동
2nd row일도2동
3rd row대학동
4th row자양3동
5th row구로5동
ValueCountFrequency (%)
사직동 3
 
3.0%
만년동 2
 
2.0%
구로5동 2
 
2.0%
운정1동 2
 
2.0%
문화1동 1
 
1.0%
삼산동 1
 
1.0%
매산동 1
 
1.0%
정자1동 1
 
1.0%
인계동 1
 
1.0%
조치원읍 1
 
1.0%
Other values (85) 85
85.0%
2023-12-10T19:07:31.398015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
95
26.4%
1 25
 
6.9%
2 17
 
4.7%
9
 
2.5%
8
 
2.2%
7
 
1.9%
7
 
1.9%
6
 
1.7%
3 6
 
1.7%
5
 
1.4%
Other values (105) 175
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 303
84.2%
Decimal Number 57
 
15.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
95
31.4%
9
 
3.0%
8
 
2.6%
7
 
2.3%
7
 
2.3%
6
 
2.0%
5
 
1.7%
4
 
1.3%
4
 
1.3%
4
 
1.3%
Other values (97) 154
50.8%
Decimal Number
ValueCountFrequency (%)
1 25
43.9%
2 17
29.8%
3 6
 
10.5%
4 3
 
5.3%
5 3
 
5.3%
6 1
 
1.8%
8 1
 
1.8%
9 1
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 303
84.2%
Common 57
 
15.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
95
31.4%
9
 
3.0%
8
 
2.6%
7
 
2.3%
7
 
2.3%
6
 
2.0%
5
 
1.7%
4
 
1.3%
4
 
1.3%
4
 
1.3%
Other values (97) 154
50.8%
Common
ValueCountFrequency (%)
1 25
43.9%
2 17
29.8%
3 6
 
10.5%
4 3
 
5.3%
5 3
 
5.3%
6 1
 
1.8%
8 1
 
1.8%
9 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 303
84.2%
ASCII 57
 
15.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
95
31.4%
9
 
3.0%
8
 
2.6%
7
 
2.3%
7
 
2.3%
6
 
2.0%
5
 
1.7%
4
 
1.3%
4
 
1.3%
4
 
1.3%
Other values (97) 154
50.8%
ASCII
ValueCountFrequency (%)
1 25
43.9%
2 17
29.8%
3 6
 
10.5%
4 3
 
5.3%
5 3
 
5.3%
6 1
 
1.8%
8 1
 
1.8%
9 1
 
1.8%

rdnmaddr_cd
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9580391 × 1011
Minimum1.1110201 × 1011
Maximum5.0130335 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:31.674520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110201 × 1011
5-th percentile1.1200411 × 1011
Q12.6342735 × 1011
median2.8910372 × 1011
Q34.1177489 × 1011
95-th percentile4.1590321 × 1011
Maximum5.0130335 × 1011
Range3.9020135 × 1011
Interquartile range (IQR)1.4834754 × 1011

Descriptive statistics

Standard deviation1.0923457 × 1011
Coefficient of variation (CV)0.36928036
Kurtosis-0.69830353
Mean2.9580391 × 1011
Median Absolute Deviation (MAD)1.2202946 × 1011
Skewness-0.32925837
Sum2.9580391 × 1013
Variance1.1932192 × 1022
MonotonicityNot monotonic
2023-12-10T19:07:32.031056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
115304148016 2
 
2.0%
301702166001 2
 
2.0%
117403000034 1
 
1.0%
311403169026 1
 
1.0%
412813192009 1
 
1.0%
411153176016 1
 
1.0%
411113174010 1
 
1.0%
411154328473 1
 
1.0%
361104574153 1
 
1.0%
317104320008 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
111102005001 1
1.0%
111104100261 1
1.0%
111403101011 1
1.0%
111702005002 1
1.0%
112004109035 1
1.0%
112004109156 1
1.0%
112153104007 1
1.0%
113203005039 1
1.0%
113503110007 1
1.0%
113803111002 1
1.0%
ValueCountFrequency (%)
501303350269 1
1.0%
501103349144 1
1.0%
501103349055 1
1.0%
416102012015 1
1.0%
415903210146 1
1.0%
415903210108 1
1.0%
415903210025 1
1.0%
415703209043 1
1.0%
414804418987 1
1.0%
414804418518 1
1.0%

rdnm_addr
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:07:32.675279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length16
Min length11

Characters and Unicode

Total characters1600
Distinct characters171
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

Unique100 ?
Unique (%)100.0%

Sample

1st row서울 강동구 동남로 870
2nd row제주특별자치도 제주시 동광로 69
3rd row서울 관악구 신림로3길 35
4th row서울 광진구 능동로 76
5th row서울 구로구 가마산로25길 9-24
ValueCountFrequency (%)
경기 29
 
6.9%
서울 19
 
4.5%
대구 11
 
2.6%
부산 10
 
2.4%
인천 10
 
2.4%
광주 7
 
1.7%
서구 7
 
1.7%
남구 6
 
1.4%
중구 6
 
1.4%
북구 5
 
1.2%
Other values (251) 309
73.7%
2023-12-10T19:07:33.405766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
319
 
19.9%
96
 
6.0%
91
 
5.7%
1 62
 
3.9%
44
 
2.8%
2 40
 
2.5%
3 38
 
2.4%
37
 
2.3%
35
 
2.2%
33
 
2.1%
Other values (161) 805
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 971
60.7%
Space Separator 319
 
19.9%
Decimal Number 308
 
19.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
96
 
9.9%
91
 
9.4%
44
 
4.5%
37
 
3.8%
35
 
3.6%
33
 
3.4%
32
 
3.3%
30
 
3.1%
30
 
3.1%
26
 
2.7%
Other values (149) 517
53.2%
Decimal Number
ValueCountFrequency (%)
1 62
20.1%
2 40
13.0%
3 38
12.3%
0 31
10.1%
6 29
9.4%
7 26
8.4%
5 25
8.1%
8 23
 
7.5%
4 18
 
5.8%
9 16
 
5.2%
Space Separator
ValueCountFrequency (%)
319
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 971
60.7%
Common 629
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
96
 
9.9%
91
 
9.4%
44
 
4.5%
37
 
3.8%
35
 
3.6%
33
 
3.4%
32
 
3.3%
30
 
3.1%
30
 
3.1%
26
 
2.7%
Other values (149) 517
53.2%
Common
ValueCountFrequency (%)
319
50.7%
1 62
 
9.9%
2 40
 
6.4%
3 38
 
6.0%
0 31
 
4.9%
6 29
 
4.6%
7 26
 
4.1%
5 25
 
4.0%
8 23
 
3.7%
4 18
 
2.9%
Other values (2) 18
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 971
60.7%
ASCII 629
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319
50.7%
1 62
 
9.9%
2 40
 
6.4%
3 38
 
6.0%
0 31
 
4.9%
6 29
 
4.6%
7 26
 
4.1%
5 25
 
4.0%
8 23
 
3.7%
4 18
 
2.9%
Other values (2) 18
 
2.9%
Hangul
ValueCountFrequency (%)
96
 
9.9%
91
 
9.4%
44
 
4.5%
37
 
3.8%
35
 
3.6%
33
 
3.4%
32
 
3.3%
30
 
3.1%
30
 
3.1%
26
 
2.7%
Other values (149) 517
53.2%

zip_cd
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27317.7
Minimum1427
Maximum63594
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:33.672413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1427
5-th percentile3643.2
Q110894.75
median21504.5
Q343205.75
95-th percentile61967.5
Maximum63594
Range62167
Interquartile range (IQR)32311

Descriptive statistics

Standard deviation18904.499
Coefficient of variation (CV)0.69202383
Kurtosis-1.1111628
Mean27317.7
Median Absolute Deviation (MAD)14060
Skewness0.4533529
Sum2731770
Variance3.573801 × 108
MonotonicityNot monotonic
2023-12-10T19:07:33.940171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8301 2
 
2.0%
35204 2
 
2.0%
5278 1
 
1.0%
44702 1
 
1.0%
10460 1
 
1.0%
16444 1
 
1.0%
16336 1
 
1.0%
16488 1
 
1.0%
30020 1
 
1.0%
44927 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
1427 1
1.0%
1736 1
1.0%
3028 1
1.0%
3172 1
1.0%
3381 1
1.0%
3657 1
1.0%
4390 1
1.0%
4569 1
1.0%
4744 1
1.0%
4778 1
1.0%
ValueCountFrequency (%)
63594 1
1.0%
63270 1
1.0%
63147 1
1.0%
62427 1
1.0%
62015 1
1.0%
61965 1
1.0%
61705 1
1.0%
61636 1
1.0%
61498 1
1.0%
61104 1
1.0%

grid_cd
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:07:34.485605image/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

Unique100 ?
Unique (%)100.0%

Sample

1st row다사697502
2nd row다다103018
3rd row다사509410
4th row다사620487
5th row다사459443
ValueCountFrequency (%)
다사697502 1
 
1.0%
다바855116 1
 
1.0%
다사566195 1
 
1.0%
다사544235 1
 
1.0%
다사589181 1
 
1.0%
다바810446 1
 
1.0%
마마569312 1
 
1.0%
마마686332 1
 
1.0%
마마733229 1
 
1.0%
마마650316 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:07:35.443340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
9.4%
4 75
9.4%
5 72
9.0%
9 69
8.6%
6 68
8.5%
3 67
8.4%
1 62
7.8%
55
 
6.9%
2 55
 
6.9%
8 54
 
6.8%
Other values (6) 148
18.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 75
12.5%
5 72
12.0%
9 69
11.5%
6 68
11.3%
3 67
11.2%
1 62
10.3%
2 55
9.2%
8 54
9.0%
7 40
6.7%
0 38
6.3%
Other Letter
ValueCountFrequency (%)
75
37.5%
55
27.5%
33
16.5%
26
 
13.0%
9
 
4.5%
2
 
1.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 75
12.5%
5 72
12.0%
9 69
11.5%
6 68
11.3%
3 67
11.2%
1 62
10.3%
2 55
9.2%
8 54
9.0%
7 40
6.7%
0 38
6.3%
Hangul
ValueCountFrequency (%)
75
37.5%
55
27.5%
33
16.5%
26
 
13.0%
9
 
4.5%
2
 
1.0%

Most occurring blocks

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

Most frequent character per block

Hangul
ValueCountFrequency (%)
75
37.5%
55
27.5%
33
16.5%
26
 
13.0%
9
 
4.5%
2
 
1.0%
ASCII
ValueCountFrequency (%)
4 75
12.5%
5 72
12.0%
9 69
11.5%
6 68
11.3%
3 67
11.2%
1 62
10.3%
2 55
9.2%
8 54
9.0%
7 40
6.7%
0 38
6.3%

x_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.618064
Minimum33.246333
Maximum37.856751
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:35.752395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.246333
5-th percentile35.121462
Q135.767294
median37.251225
Q337.518893
95-th percentile37.724207
Maximum37.856751
Range4.610418
Interquartile range (IQR)1.7515986

Descriptive statistics

Standard deviation1.1194146
Coefficient of variation (CV)0.030570011
Kurtosis-0.026917205
Mean36.618064
Median Absolute Deviation (MAD)0.40503275
Skewness-0.90463625
Sum3661.8064
Variance1.2530891
MonotonicityNot monotonic
2023-12-10T19:07:35.998418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5512205 1
 
1.0%
36.374115 1
 
1.0%
37.6584133 1
 
1.0%
37.2735969 1
 
1.0%
37.3095767 1
 
1.0%
37.2615833 1
 
1.0%
36.5998245 1
 
1.0%
35.5644309 1
 
1.0%
35.5813273 1
 
1.0%
35.4870581 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
33.2463334 1
1.0%
33.4751044 1
1.0%
33.504444 1
1.0%
35.0752654 1
1.0%
35.1100332 1
1.0%
35.1220637 1
1.0%
35.1271849 1
1.0%
35.1285935 1
1.0%
35.1307378 1
1.0%
35.1308257 1
1.0%
ValueCountFrequency (%)
37.8567514 1
1.0%
37.759193 1
1.0%
37.7453664 1
1.0%
37.7333846 1
1.0%
37.7305123 1
1.0%
37.7238754 1
1.0%
37.6614856 1
1.0%
37.6584133 1
1.0%
37.6541028 1
1.0%
37.6502369 1
1.0%

y_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.44514
Minimum126.47457
Maximum129.41126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:36.238325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.47457
5-th percentile126.62928
Q1126.83452
median127.03367
Q3128.47642
95-th percentile129.17687
Maximum129.41126
Range2.9366905
Interquartile range (IQR)1.6419072

Descriptive statistics

Standard deviation0.90693127
Coefficient of variation (CV)0.0071162483
Kurtosis-0.49992175
Mean127.44514
Median Absolute Deviation (MAD)0.2566927
Skewness1.074612
Sum12744.514
Variance0.82252432
MonotonicityNot monotonic
2023-12-10T19:07:36.531196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1573425 1
 
1.0%
127.420651 1
 
1.0%
126.8319601 1
 
1.0%
127.0113034 1
 
1.0%
126.9864012 1
 
1.0%
127.0375696 1
 
1.0%
127.2878437 1
 
1.0%
129.2320729 1
 
1.0%
129.3614066 1
 
1.0%
129.4112633 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.4745728 1
1.0%
126.5155186 1
1.0%
126.5351724 1
1.0%
126.5507911 1
1.0%
126.6267833 1
1.0%
126.629407 1
1.0%
126.6350294 1
1.0%
126.6622628 1
1.0%
126.6798899 1
1.0%
126.7000558 1
1.0%
ValueCountFrequency (%)
129.4112633 1
1.0%
129.3614066 1
1.0%
129.3270938 1
1.0%
129.3215364 1
1.0%
129.2320729 1
1.0%
129.173966 1
1.0%
129.1270845 1
1.0%
129.1024564 1
1.0%
129.0944742 1
1.0%
129.0934781 1
1.0%

erc_mby
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
기초자치단체
74 
광역자치단체
25 
민간기업
 
1

Length

Max length6
Median length6
Mean length5.98
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row기초자치단체
2nd row광역자치단체
3rd row기초자치단체
4th row기초자치단체
5th row기초자치단체

Common Values

ValueCountFrequency (%)
기초자치단체 74
74.0%
광역자치단체 25
 
25.0%
민간기업 1
 
1.0%

Length

2023-12-10T19:07:36.795472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:36.989971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기초자치단체 74
74.0%
광역자치단체 25
 
25.0%
민간기업 1
 
1.0%
Distinct79
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:07:37.413705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length15
Mean length7.55
Min length2

Characters and Unicode

Total characters755
Distinct characters111
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

Unique63 ?
Unique (%)63.0%

Sample

1st row강동구
2nd row제주특별자치도
3rd row관악문화재단
4th row광진문화재단
5th row(재)구로문화재단
ValueCountFrequency (%)
파주시시설관리공단 4
 
3.8%
화성시문화재단 3
 
2.8%
평택시 3
 
2.8%
중구 3
 
2.8%
재)용인문화재단 3
 
2.8%
인천광역시 3
 
2.8%
대구광역시 2
 
1.9%
고양문화재단 2
 
1.9%
서구 2
 
1.9%
성동문화재단 2
 
1.9%
Other values (72) 79
74.5%
2023-12-10T19:07:38.355633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
9.5%
57
 
7.5%
50
 
6.6%
46
 
6.1%
39
 
5.2%
34
 
4.5%
) 32
 
4.2%
( 31
 
4.1%
19
 
2.5%
18
 
2.4%
Other values (101) 357
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 682
90.3%
Close Punctuation 32
 
4.2%
Open Punctuation 31
 
4.1%
Space Separator 7
 
0.9%
Other Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
72
 
10.6%
57
 
8.4%
50
 
7.3%
46
 
6.7%
39
 
5.7%
34
 
5.0%
19
 
2.8%
18
 
2.6%
16
 
2.3%
14
 
2.1%
Other values (97) 317
46.5%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 682
90.3%
Common 73
 
9.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
72
 
10.6%
57
 
8.4%
50
 
7.3%
46
 
6.7%
39
 
5.7%
34
 
5.0%
19
 
2.8%
18
 
2.6%
16
 
2.3%
14
 
2.1%
Other values (97) 317
46.5%
Common
ValueCountFrequency (%)
) 32
43.8%
( 31
42.5%
7
 
9.6%
, 3
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 682
90.3%
ASCII 73
 
9.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
72
 
10.6%
57
 
8.4%
50
 
7.3%
46
 
6.7%
39
 
5.7%
34
 
5.0%
19
 
2.8%
18
 
2.6%
16
 
2.3%
14
 
2.1%
Other values (97) 317
46.5%
ASCII
ValueCountFrequency (%)
) 32
43.8%
( 31
42.5%
7
 
9.6%
, 3
 
4.1%

oper_mby_chartr
Categorical

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
공공기관 위탁
52 
지자체 직영
29 
민간기관 위탁
지자체직영
공공기간 위탁
 
1
Other values (3)
 
3

Length

Max length7
Median length7
Mean length6.53
Min length4

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row지자체 직영
2nd row지자체 직영
3rd row공공기관 위탁
4th row공공기관 위탁
5th row공공기관 위탁

Common Values

ValueCountFrequency (%)
공공기관 위탁 52
52.0%
지자체 직영 29
29.0%
민간기관 위탁 9
 
9.0%
지자체직영 6
 
6.0%
공공기간 위탁 1
 
1.0%
민간위탁 1
 
1.0%
공공기관위탁 1
 
1.0%
기초지자체 1
 
1.0%

Length

2023-12-10T19:07:38.631430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:38.828373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁 62
32.5%
공공기관 52
27.2%
지자체 29
15.2%
직영 29
15.2%
민간기관 9
 
4.7%
지자체직영 6
 
3.1%
공공기간 1
 
0.5%
민간위탁 1
 
0.5%
공공기관위탁 1
 
0.5%
기초지자체 1
 
0.5%

cttpc
Text

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:07:39.237084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.95
Min length11

Characters and Unicode

Total characters1195
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)95.0%

Sample

1st row02-440-0500
2nd row064-710-7601
3rd row02-828-5700
4th row02-2049-4700
5th row02-2029-1720
ValueCountFrequency (%)
031-260-3300 3
 
3.0%
031-960-9674 2
 
2.0%
032-500-2031 1
 
1.0%
031-250-5300 1
 
1.0%
044-301-3523 1
 
1.0%
052-229-9500 1
 
1.0%
052-241-7350 1
 
1.0%
052-209-4330 1
 
1.0%
052-290-4000 1
 
1.0%
052-275-9623 1
 
1.0%
Other values (87) 87
87.0%
2023-12-10T19:07:40.247966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 248
20.8%
- 189
15.8%
2 123
10.3%
3 115
9.6%
1 100
8.4%
5 93
 
7.8%
6 89
 
7.4%
4 64
 
5.4%
9 56
 
4.7%
7 55
 
4.6%
Other values (2) 63
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 995
83.3%
Dash Punctuation 189
 
15.8%
Close Punctuation 11
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 248
24.9%
2 123
12.4%
3 115
11.6%
1 100
10.1%
5 93
 
9.3%
6 89
 
8.9%
4 64
 
6.4%
9 56
 
5.6%
7 55
 
5.5%
8 52
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 189
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1195
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 248
20.8%
- 189
15.8%
2 123
10.3%
3 115
9.6%
1 100
8.4%
5 93
 
7.8%
6 89
 
7.4%
4 64
 
5.4%
9 56
 
4.7%
7 55
 
4.6%
Other values (2) 63
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 248
20.8%
- 189
15.8%
2 123
10.3%
3 115
9.6%
1 100
8.4%
5 93
 
7.8%
6 89
 
7.4%
4 64
 
5.4%
9 56
 
4.7%
7 55
 
4.6%
Other values (2) 63
 
5.3%

hmpg
Text

Distinct88
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:07:40.723846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length35
Mean length21.79
Min length11

Characters and Unicode

Total characters2179
Distinct characters44
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)80.0%

Sample

1st rowwww.gangdongarts.or.kr
2nd rowhttp://www.jeju.go.kr/jejuculture
3rd rowwww.gfac.or.kr
4th rowwww.naruart.or.kr
5th rowhttps://www.guroartsvalley.or.kr
ValueCountFrequency (%)
www.pajucf.or.kr 4
 
4.0%
www.yicf.or.kr 3
 
3.0%
www.pyeongtaek.go.kr 3
 
3.0%
www.bcf.or.kr 2
 
2.0%
www.ayac.or.kr 2
 
2.0%
www.bscc.or.kr 2
 
2.0%
www.sdfac.or.kr 2
 
2.0%
www.artgy.or.kr 2
 
2.0%
www.nglcc.kr 1
 
1.0%
www.seogu.go.kr 1
 
1.0%
Other values (78) 78
78.0%
2023-12-10T19:07:41.557367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 291
13.4%
w 253
 
11.6%
r 218
 
10.0%
o 140
 
6.4%
t 127
 
5.8%
/ 105
 
4.8%
a 104
 
4.8%
k 102
 
4.7%
g 93
 
4.3%
e 83
 
3.8%
Other values (34) 663
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1723
79.1%
Other Punctuation 431
 
19.8%
Decimal Number 13
 
0.6%
Uppercase Letter 6
 
0.3%
Connector Punctuation 3
 
0.1%
Math Symbol 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 253
14.7%
r 218
12.7%
o 140
 
8.1%
t 127
 
7.4%
a 104
 
6.0%
k 102
 
5.9%
g 93
 
5.4%
e 83
 
4.8%
c 79
 
4.6%
n 75
 
4.4%
Other values (15) 449
26.1%
Decimal Number
ValueCountFrequency (%)
1 3
23.1%
0 2
15.4%
4 2
15.4%
5 2
15.4%
2 2
15.4%
8 1
 
7.7%
6 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 291
67.5%
/ 105
 
24.4%
: 32
 
7.4%
? 2
 
0.5%
, 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
W 3
50.0%
U 1
 
16.7%
I 1
 
16.7%
H 1
 
16.7%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Math Symbol
ValueCountFrequency (%)
= 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1729
79.3%
Common 450
 
20.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 253
14.6%
r 218
12.6%
o 140
 
8.1%
t 127
 
7.3%
a 104
 
6.0%
k 102
 
5.9%
g 93
 
5.4%
e 83
 
4.8%
c 79
 
4.6%
n 75
 
4.3%
Other values (19) 455
26.3%
Common
ValueCountFrequency (%)
. 291
64.7%
/ 105
 
23.3%
: 32
 
7.1%
_ 3
 
0.7%
1 3
 
0.7%
0 2
 
0.4%
4 2
 
0.4%
5 2
 
0.4%
= 2
 
0.4%
? 2
 
0.4%
Other values (5) 6
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2179
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 291
13.4%
w 253
 
11.6%
r 218
 
10.0%
o 140
 
6.4%
t 127
 
5.8%
/ 105
 
4.8%
a 104
 
4.8%
k 102
 
4.7%
g 93
 
4.3%
e 83
 
3.8%
Other values (34) 663
30.4%

opnngdt
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:07:42.261038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length10
Mean length10.16
Min length5

Characters and Unicode

Total characters1016
Distinct characters17
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

Unique100 ?
Unique (%)100.0%

Sample

1st row2011.09.01
2nd row1988.08.25.
3rd row2002.10.11
4th row2005.05.02
5th row2008.07.22
ValueCountFrequency (%)
2011.09.01 1
 
1.0%
2012.9.17 1
 
1.0%
1970.12.01 1
 
1.0%
2014.03.06 1
 
1.0%
1991.06.28 1
 
1.0%
2000.10.04 1
 
1.0%
2009.11.20 1
 
1.0%
2003.9.25 1
 
1.0%
2011.06.28 1
 
1.0%
2014.11.07 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:07:43.182047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 227
22.3%
. 218
21.5%
1 179
17.6%
2 125
12.3%
9 86
 
8.5%
8 37
 
3.6%
5 37
 
3.6%
4 31
 
3.1%
3 26
 
2.6%
7 26
 
2.6%
Other values (7) 24
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 789
77.7%
Other Punctuation 219
 
21.6%
Other Letter 5
 
0.5%
Open Punctuation 2
 
0.2%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 227
28.8%
1 179
22.7%
2 125
15.8%
9 86
 
10.9%
8 37
 
4.7%
5 37
 
4.7%
4 31
 
3.9%
3 26
 
3.3%
7 26
 
3.3%
6 15
 
1.9%
Other Letter
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 218
99.5%
, 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1011
99.5%
Hangul 5
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 227
22.5%
. 218
21.6%
1 179
17.7%
2 125
12.4%
9 86
 
8.5%
8 37
 
3.7%
5 37
 
3.7%
4 31
 
3.1%
3 26
 
2.6%
7 26
 
2.6%
Other values (4) 19
 
1.9%
Hangul
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1011
99.5%
Hangul 5
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 227
22.5%
. 218
21.6%
1 179
17.7%
2 125
12.4%
9 86
 
8.5%
8 37
 
3.7%
5 37
 
3.7%
4 31
 
3.1%
3 26
 
2.6%
7 26
 
2.6%
Other values (4) 19
 
1.9%
Hangul
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%

totar
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:07:43.722966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.38
Min length3

Characters and Unicode

Total characters538
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
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 row18051
2nd row7704.31
3rd row15614.85
4th row18860.5
5th row8799.8
ValueCountFrequency (%)
18051 1
 
1.0%
4770.37 1
 
1.0%
3187 1
 
1.0%
14904 1
 
1.0%
34982 1
 
1.0%
6264 1
 
1.0%
3485 1
 
1.0%
3714 1
 
1.0%
2554.9 1
 
1.0%
7708.09 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:07:44.558465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 62
11.5%
1 57
10.6%
8 53
9.9%
7 53
9.9%
9 52
9.7%
4 46
8.6%
0 45
8.4%
5 45
8.4%
2 42
7.8%
6 41
7.6%
Other values (3) 42
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 496
92.2%
Other Punctuation 41
 
7.6%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 62
12.5%
1 57
11.5%
8 53
10.7%
7 53
10.7%
9 52
10.5%
4 46
9.3%
0 45
9.1%
5 45
9.1%
2 42
8.5%
6 41
8.3%
Other Punctuation
ValueCountFrequency (%)
. 40
97.6%
, 1
 
2.4%
Space Separator
ValueCountFrequency (%)
  1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 538
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 62
11.5%
1 57
10.6%
8 53
9.9%
7 53
9.9%
9 52
9.7%
4 46
8.6%
0 45
8.4%
5 45
8.4%
2 42
7.8%
6 41
7.6%
Other values (3) 42
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 537
99.8%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 62
11.5%
1 57
10.6%
8 53
9.9%
7 53
9.9%
9 52
9.7%
4 46
8.6%
0 45
8.4%
5 45
8.4%
2 42
7.8%
6 41
7.6%
Other values (2) 41
7.6%
None
ValueCountFrequency (%)
  1
100.0%

cmplx_seats
Text

MISSING 

Distinct28
Distinct (%)62.2%
Missing55
Missing (%)55.0%
Memory size932.0 B
2023-12-10T19:07:44.850004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length3
Min length1

Characters and Unicode

Total characters135
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)57.8%

Sample

1st row0
2nd row1184
3rd row-
4th row-
5th row1255
ValueCountFrequency (%)
13
28.9%
0 6
 
13.3%
1722 1
 
2.2%
1025 1
 
2.2%
1126 1
 
2.2%
1592 1
 
2.2%
1041 1
 
2.2%
1,808,1,102 1
 
2.2%
1258 1
 
2.2%
1218 1
 
2.2%
Other values (18) 18
40.0%
2023-12-10T19:07:45.244995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 38
28.1%
0 17
12.6%
2 14
 
10.4%
- 13
 
9.6%
8 12
 
8.9%
4 10
 
7.4%
5 8
 
5.9%
9 7
 
5.2%
6 5
 
3.7%
7 4
 
3.0%
Other values (2) 7
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 118
87.4%
Dash Punctuation 13
 
9.6%
Other Punctuation 4
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 38
32.2%
0 17
14.4%
2 14
 
11.9%
8 12
 
10.2%
4 10
 
8.5%
5 8
 
6.8%
9 7
 
5.9%
6 5
 
4.2%
7 4
 
3.4%
3 3
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 135
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 38
28.1%
0 17
12.6%
2 14
 
10.4%
- 13
 
9.6%
8 12
 
8.9%
4 10
 
7.4%
5 8
 
5.9%
9 7
 
5.2%
6 5
 
3.7%
7 4
 
3.0%
Other values (2) 7
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 38
28.1%
0 17
12.6%
2 14
 
10.4%
- 13
 
9.6%
8 12
 
8.9%
4 10
 
7.4%
5 8
 
5.9%
9 7
 
5.2%
6 5
 
3.7%
7 4
 
3.0%
Other values (2) 7
 
5.2%

cmplx_aea
Text

MISSING 

Distinct28
Distinct (%)60.9%
Missing54
Missing (%)54.0%
Memory size932.0 B
2023-12-10T19:07:45.501566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length3.5869565
Min length1

Characters and Unicode

Total characters165
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)56.5%

Sample

1st row0
2nd row2251
3rd row-
4th row-
5th row1268
ValueCountFrequency (%)
13
28.3%
0 7
 
15.2%
13704 1
 
2.2%
1147.92 1
 
2.2%
2161 1
 
2.2%
2167 1
 
2.2%
2196 1
 
2.2%
16,933.58,10,783.2 1
 
2.2%
4410 1
 
2.2%
13635.4 1
 
2.2%
Other values (18) 18
39.1%
2023-12-10T19:07:46.037666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24
14.5%
0 15
9.1%
6 15
9.1%
5 15
9.1%
2 14
8.5%
- 13
7.9%
4 13
7.9%
9 12
7.3%
3 12
7.3%
7 11
6.7%
Other values (3) 21
12.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 140
84.8%
Dash Punctuation 13
 
7.9%
Other Punctuation 12
 
7.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
17.1%
0 15
10.7%
6 15
10.7%
5 15
10.7%
2 14
10.0%
4 13
9.3%
9 12
8.6%
3 12
8.6%
7 11
7.9%
8 9
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
, 4
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 165
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24
14.5%
0 15
9.1%
6 15
9.1%
5 15
9.1%
2 14
8.5%
- 13
7.9%
4 13
7.9%
9 12
7.3%
3 12
7.3%
7 11
6.7%
Other values (3) 21
12.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 165
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24
14.5%
0 15
9.1%
6 15
9.1%
5 15
9.1%
2 14
8.5%
- 13
7.9%
4 13
7.9%
9 12
7.3%
3 12
7.3%
7 11
6.7%
Other values (3) 21
12.7%

prfplc_seats
Text

MISSING 

Distinct78
Distinct (%)88.6%
Missing12
Missing (%)12.0%
Memory size932.0 B
2023-12-10T19:07:46.503625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length3
Mean length3.4659091
Min length1

Characters and Unicode

Total characters305
Distinct characters22
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

Unique70 ?
Unique (%)79.5%

Sample

1st row850
2nd row828
3rd row698
4th row601
5th row611
ValueCountFrequency (%)
3
 
3.3%
300 3
 
3.3%
638 2
 
2.2%
531 2
 
2.2%
0 2
 
2.2%
382 2
 
2.2%
548 2
 
2.2%
802 2
 
2.2%
402 1
 
1.1%
750 1
 
1.1%
Other values (71) 71
78.0%
2023-12-10T19:07:47.189914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 39
12.8%
0 38
12.5%
4 37
12.1%
8 30
9.8%
6 27
8.9%
5 27
8.9%
2 27
8.9%
7 23
7.5%
1 18
5.9%
9 12
 
3.9%
Other values (12) 27
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 278
91.1%
Other Letter 10
 
3.3%
Other Punctuation 9
 
3.0%
Space Separator 3
 
1.0%
Dash Punctuation 3
 
1.0%
Uppercase Letter 2
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 39
14.0%
0 38
13.7%
4 37
13.3%
8 30
10.8%
6 27
9.7%
5 27
9.7%
2 27
9.7%
7 23
8.3%
1 18
6.5%
9 12
 
4.3%
Other Letter
ValueCountFrequency (%)
2
20.0%
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
50.0%
S 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 293
96.1%
Hangul 10
 
3.3%
Latin 2
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
3 39
13.3%
0 38
13.0%
4 37
12.6%
8 30
10.2%
6 27
9.2%
5 27
9.2%
2 27
9.2%
7 23
7.8%
1 18
6.1%
9 12
 
4.1%
Other values (3) 15
 
5.1%
Hangul
ValueCountFrequency (%)
2
20.0%
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Latin
ValueCountFrequency (%)
M 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 295
96.7%
Hangul 10
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 39
13.2%
0 38
12.9%
4 37
12.5%
8 30
10.2%
6 27
9.2%
5 27
9.2%
2 27
9.2%
7 23
7.8%
1 18
6.1%
9 12
 
4.1%
Other values (5) 17
5.8%
Hangul
ValueCountFrequency (%)
2
20.0%
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%

prfplc_aea
Text

MISSING 

Distinct84
Distinct (%)95.5%
Missing12
Missing (%)12.0%
Memory size932.0 B
2023-12-10T19:07:47.676891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length4.7159091
Min length1

Characters and Unicode

Total characters415
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

Unique81 ?
Unique (%)92.0%

Sample

1st row1948
2nd row5072
3rd row886
4th row853
5th row1362
ValueCountFrequency (%)
3
 
3.4%
0 2
 
2.2%
1486 2
 
2.2%
428.22 1
 
1.1%
1703.23 1
 
1.1%
5,024,1,234 1
 
1.1%
3157,2470 1
 
1.1%
1651.79 1
 
1.1%
2854 1
 
1.1%
754 1
 
1.1%
Other values (75) 75
84.3%
2023-12-10T19:07:48.584392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 57
13.7%
2 55
13.3%
7 43
10.4%
8 42
10.1%
3 33
8.0%
5 31
7.5%
4 30
7.2%
6 30
7.2%
0 26
6.3%
. 26
6.3%
Other values (4) 42
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 370
89.2%
Other Punctuation 41
 
9.9%
Dash Punctuation 3
 
0.7%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 57
15.4%
2 55
14.9%
7 43
11.6%
8 42
11.4%
3 33
8.9%
5 31
8.4%
4 30
8.1%
6 30
8.1%
0 26
7.0%
9 23
6.2%
Other Punctuation
ValueCountFrequency (%)
. 26
63.4%
, 15
36.6%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 415
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 57
13.7%
2 55
13.3%
7 43
10.4%
8 42
10.1%
3 33
8.0%
5 31
7.5%
4 30
7.2%
6 30
7.2%
0 26
6.3%
. 26
6.3%
Other values (4) 42
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 57
13.7%
2 55
13.3%
7 43
10.4%
8 42
10.1%
3 33
8.0%
5 31
7.5%
4 30
7.2%
6 30
7.2%
0 26
6.3%
. 26
6.3%
Other values (4) 42
10.1%

sl_prfplc_seats
Text

MISSING 

Distinct36
Distinct (%)59.0%
Missing39
Missing (%)39.0%
Memory size932.0 B
2023-12-10T19:07:48.940926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.3770492
Min length1

Characters and Unicode

Total characters145
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)45.9%

Sample

1st row250
2nd row170
3rd row167
4th row60
5th row292
ValueCountFrequency (%)
9
 
14.8%
0 8
 
13.1%
200 4
 
6.6%
90 3
 
4.9%
100 3
 
4.9%
157 2
 
3.3%
212 2
 
3.3%
190 2
 
3.3%
160 1
 
1.6%
168 1
 
1.6%
Other values (26) 26
42.6%
2023-12-10T19:07:49.578846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38
26.2%
2 28
19.3%
1 23
15.9%
- 9
 
6.2%
9 8
 
5.5%
5 8
 
5.5%
8 8
 
5.5%
6 7
 
4.8%
7 6
 
4.1%
4 5
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 136
93.8%
Dash Punctuation 9
 
6.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38
27.9%
2 28
20.6%
1 23
16.9%
9 8
 
5.9%
5 8
 
5.9%
8 8
 
5.9%
6 7
 
5.1%
7 6
 
4.4%
4 5
 
3.7%
3 5
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 145
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38
26.2%
2 28
19.3%
1 23
15.9%
- 9
 
6.2%
9 8
 
5.5%
5 8
 
5.5%
8 8
 
5.5%
6 7
 
4.8%
7 6
 
4.1%
4 5
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 145
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38
26.2%
2 28
19.3%
1 23
15.9%
- 9
 
6.2%
9 8
 
5.5%
5 8
 
5.5%
8 8
 
5.5%
6 7
 
4.8%
7 6
 
4.1%
4 5
 
3.4%

sl_prfplc_aea
Text

MISSING 

Distinct45
Distinct (%)73.8%
Missing39
Missing (%)39.0%
Memory size932.0 B
2023-12-10T19:07:49.887789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.1147541
Min length1

Characters and Unicode

Total characters190
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)68.9%

Sample

1st row459
2nd row544
3rd row257.9
4th row142.84
5th row530.8
ValueCountFrequency (%)
0 9
 
14.8%
8
 
13.1%
486 2
 
3.3%
43 1
 
1.6%
362 1
 
1.6%
459 1
 
1.6%
265 1
 
1.6%
515 1
 
1.6%
277 1
 
1.6%
457 1
 
1.6%
Other values (35) 35
57.4%
2023-12-10T19:07:50.442047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 22
11.6%
4 21
11.1%
3 20
10.5%
8 17
8.9%
5 17
8.9%
0 16
8.4%
. 16
8.4%
6 14
7.4%
1 14
7.4%
7 13
6.8%
Other values (2) 20
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 166
87.4%
Other Punctuation 16
 
8.4%
Dash Punctuation 8
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 22
13.3%
4 21
12.7%
3 20
12.0%
8 17
10.2%
5 17
10.2%
0 16
9.6%
6 14
8.4%
1 14
8.4%
7 13
7.8%
9 12
7.2%
Other Punctuation
ValueCountFrequency (%)
. 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 190
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 22
11.6%
4 21
11.1%
3 20
10.5%
8 17
8.9%
5 17
8.9%
0 16
8.4%
. 16
8.4%
6 14
7.4%
1 14
7.4%
7 13
6.8%
Other values (2) 20
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 22
11.6%
4 21
11.1%
3 20
10.5%
8 17
8.9%
5 17
8.9%
0 16
8.4%
. 16
8.4%
6 14
7.4%
1 14
7.4%
7 13
6.8%
Other values (2) 20
10.5%

ehbll_cnt
Categorical

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
47 
<NA>
22 
2
12 
3
 
4
0
 
4
Other values (7)
11 

Length

Max length4
Median length1
Mean length1.67
Min length1

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row2
2nd row3
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 47
47.0%
<NA> 22
22.0%
2 12
 
12.0%
3 4
 
4.0%
0 4
 
4.0%
5 3
 
3.0%
- 2
 
2.0%
4 2
 
2.0%
13 1
 
1.0%
_ 1
 
1.0%
Other values (2) 2
 
2.0%

Length

2023-12-10T19:07:50.697682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 47
47.0%
na 22
22.0%
2 12
 
12.0%
3 4
 
4.0%
0 4
 
4.0%
5 3
 
3.0%
3
 
3.0%
4 2
 
2.0%
13 1
 
1.0%
8 1
 
1.0%

ehbll_aea
Text

MISSING 

Distinct73
Distinct (%)93.6%
Missing22
Missing (%)22.0%
Memory size932.0 B
2023-12-10T19:07:51.020499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.3717949
Min length1

Characters and Unicode

Total characters263
Distinct characters13
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

Unique70 ?
Unique (%)89.7%

Sample

1st row487.6
2nd row1050
3rd row270
4th row272.2
5th row182
ValueCountFrequency (%)
0 4
 
5.1%
3
 
3.8%
330 2
 
2.6%
2201 1
 
1.3%
645 1
 
1.3%
1350 1
 
1.3%
307.342 1
 
1.3%
957.4 1
 
1.3%
169 1
 
1.3%
82.7 1
 
1.3%
Other values (62) 62
79.5%
2023-12-10T19:07:51.583824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 36
13.7%
2 33
12.5%
3 31
11.8%
5 27
10.3%
0 22
8.4%
7 22
8.4%
4 22
8.4%
9 21
8.0%
6 18
6.8%
. 16
6.1%
Other values (3) 15
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 244
92.8%
Other Punctuation 16
 
6.1%
Dash Punctuation 2
 
0.8%
Connector Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 36
14.8%
2 33
13.5%
3 31
12.7%
5 27
11.1%
0 22
9.0%
7 22
9.0%
4 22
9.0%
9 21
8.6%
6 18
7.4%
8 12
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 263
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 36
13.7%
2 33
12.5%
3 31
11.8%
5 27
10.3%
0 22
8.4%
7 22
8.4%
4 22
8.4%
9 21
8.0%
6 18
6.8%
. 16
6.1%
Other values (3) 15
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 263
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 36
13.7%
2 33
12.5%
3 31
11.8%
5 27
10.3%
0 22
8.4%
7 22
8.4%
4 22
8.4%
9 21
8.0%
6 18
6.8%
. 16
6.1%
Other values (3) 15
5.7%

edu_plce_aea
Text

MISSING 

Distinct61
Distinct (%)83.6%
Missing27
Missing (%)27.0%
Memory size932.0 B
2023-12-10T19:07:51.922011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.1780822
Min length1

Characters and Unicode

Total characters232
Distinct characters13
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

Unique58 ?
Unique (%)79.5%

Sample

1st row504
2nd row0
3rd row524
4th row276
5th row251
ValueCountFrequency (%)
10
 
13.7%
0 4
 
5.5%
276 2
 
2.7%
265.9 1
 
1.4%
21825 1
 
1.4%
5496 1
 
1.4%
109 1
 
1.4%
363.19 1
 
1.4%
212 1
 
1.4%
326.86 1
 
1.4%
Other values (50) 50
68.5%
2023-12-10T19:07:52.512246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 36
15.5%
2 22
9.5%
5 21
9.1%
4 21
9.1%
0 20
8.6%
9 20
8.6%
8 20
8.6%
3 17
7.3%
. 16
6.9%
6 15
6.5%
Other values (3) 24
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 206
88.8%
Other Punctuation 16
 
6.9%
Dash Punctuation 9
 
3.9%
Connector Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 36
17.5%
2 22
10.7%
5 21
10.2%
4 21
10.2%
0 20
9.7%
9 20
9.7%
8 20
9.7%
3 17
8.3%
6 15
7.3%
7 14
 
6.8%
Other Punctuation
ValueCountFrequency (%)
. 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 232
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 36
15.5%
2 22
9.5%
5 21
9.1%
4 21
9.1%
0 20
8.6%
9 20
8.6%
8 20
8.6%
3 17
7.3%
. 16
6.9%
6 15
6.5%
Other values (3) 24
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 232
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 36
15.5%
2 22
9.5%
5 21
9.1%
4 21
9.1%
0 20
8.6%
9 20
8.6%
8 20
8.6%
3 17
7.3%
. 16
6.9%
6 15
6.5%
Other values (3) 24
10.3%

mtg_rum_aea
Text

MISSING 

Distinct48
Distinct (%)82.8%
Missing42
Missing (%)42.0%
Memory size932.0 B
2023-12-10T19:07:52.950114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.0517241
Min length1

Characters and Unicode

Total characters177
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)77.6%

Sample

1st row24.36
2nd row89
3rd row30.7
4th row49.9
5th row281
ValueCountFrequency (%)
6
 
10.3%
0 5
 
8.6%
460 2
 
3.4%
187 1
 
1.7%
866 1
 
1.7%
167 1
 
1.7%
56.7 1
 
1.7%
72.5 1
 
1.7%
609 1
 
1.7%
131 1
 
1.7%
Other values (38) 38
65.5%
2023-12-10T19:07:53.693115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
12.4%
. 18
10.2%
2 18
10.2%
7 17
9.6%
3 16
9.0%
6 15
8.5%
8 14
7.9%
9 14
7.9%
4 13
7.3%
5 13
7.3%
Other values (2) 17
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 153
86.4%
Other Punctuation 18
 
10.2%
Dash Punctuation 6
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
14.4%
2 18
11.8%
7 17
11.1%
3 16
10.5%
6 15
9.8%
8 14
9.2%
9 14
9.2%
4 13
8.5%
5 13
8.5%
0 11
7.2%
Other Punctuation
ValueCountFrequency (%)
. 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 177
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
12.4%
. 18
10.2%
2 18
10.2%
7 17
9.6%
3 16
9.0%
6 15
8.5%
8 14
7.9%
9 14
7.9%
4 13
7.3%
5 13
7.3%
Other values (2) 17
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 177
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
12.4%
. 18
10.2%
2 18
10.2%
7 17
9.6%
3 16
9.0%
6 15
8.5%
8 14
7.9%
9 14
7.9%
4 13
7.3%
5 13
7.3%
Other values (2) 17
9.6%
Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
52 
-
12 
0
1000
 
4
600
 
2
Other values (18)
24 

Length

Max length4
Median length4
Mean length3.22
Min length1

Unique

Unique12 ?
Unique (%)12.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 52
52.0%
- 12
 
12.0%
0 6
 
6.0%
1000 4
 
4.0%
600 2
 
2.0%
500 2
 
2.0%
150 2
 
2.0%
100 2
 
2.0%
200 2
 
2.0%
400 2
 
2.0%
Other values (13) 14
 
14.0%

Length

2023-12-10T19:07:54.106867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 52
52.0%
12
 
12.0%
0 6
 
6.0%
1000 4
 
4.0%
600 2
 
2.0%
500 2
 
2.0%
150 2
 
2.0%
100 2
 
2.0%
200 2
 
2.0%
400 2
 
2.0%
Other values (13) 14
 
14.0%

feld_prfplc_aea
Text

MISSING 

Distinct32
Distinct (%)66.7%
Missing52
Missing (%)52.0%
Memory size932.0 B
2023-12-10T19:07:54.395968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.7083333
Min length1

Characters and Unicode

Total characters130
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)62.5%

Sample

1st row0
2nd row0
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
13
27.1%
0 5
 
10.4%
304 1
 
2.1%
2190 1
 
2.1%
951 1
 
2.1%
609 1
 
2.1%
710 1
 
2.1%
431 1
 
2.1%
20000 1
 
2.1%
225 1
 
2.1%
Other values (22) 22
45.8%
2023-12-10T19:07:55.116368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23
17.7%
1 16
12.3%
2 14
10.8%
- 13
10.0%
6 12
9.2%
9 11
8.5%
4 10
7.7%
7 9
 
6.9%
3 8
 
6.2%
5 7
 
5.4%
Other values (2) 7
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 111
85.4%
Dash Punctuation 13
 
10.0%
Other Punctuation 6
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23
20.7%
1 16
14.4%
2 14
12.6%
6 12
10.8%
9 11
9.9%
4 10
9.0%
7 9
 
8.1%
3 8
 
7.2%
5 7
 
6.3%
8 1
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23
17.7%
1 16
12.3%
2 14
10.8%
- 13
10.0%
6 12
9.2%
9 11
8.5%
4 10
7.7%
7 9
 
6.9%
3 8
 
6.2%
5 7
 
5.4%
Other values (2) 7
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23
17.7%
1 16
12.3%
2 14
10.8%
- 13
10.0%
6 12
9.2%
9 11
8.5%
4 10
7.7%
7 9
 
6.9%
3 8
 
6.2%
5 7
 
5.4%
Other values (2) 7
 
5.4%

emp_cnt
Real number (ℝ)

Distinct56
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.99
Minimum1
Maximum489
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:55.374904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q110.75
median22
Q353.75
95-th percentile111.85
Maximum489
Range488
Interquartile range (IQR)43

Descriptive statistics

Standard deviation72.883537
Coefficient of variation (CV)1.6199942
Kurtosis20.556458
Mean44.99
Median Absolute Deviation (MAD)13.5
Skewness4.2055525
Sum4499
Variance5312.01
MonotonicityNot monotonic
2023-12-10T19:07:55.682052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22 5
 
5.0%
9 4
 
4.0%
19 4
 
4.0%
5 4
 
4.0%
10 4
 
4.0%
4 4
 
4.0%
13 3
 
3.0%
15 3
 
3.0%
8 3
 
3.0%
18 3
 
3.0%
Other values (46) 63
63.0%
ValueCountFrequency (%)
1 2
2.0%
2 1
 
1.0%
4 4
4.0%
5 4
4.0%
6 2
2.0%
7 1
 
1.0%
8 3
3.0%
9 4
4.0%
10 4
4.0%
11 2
2.0%
ValueCountFrequency (%)
489 1
1.0%
415 1
1.0%
280 1
1.0%
234 1
1.0%
147 1
1.0%
110 1
1.0%
98 2
2.0%
91 1
1.0%
90 1
1.0%
88 1
1.0%

exp_emp_cnt
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.3
Minimum0
Maximum76
Zeros5
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:55.945121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.95
Q13
median5
Q311.25
95-th percentile24.2
Maximum76
Range76
Interquartile range (IQR)8.25

Descriptive statistics

Standard deviation11.7047
Coefficient of variation (CV)1.2585699
Kurtosis13.981239
Mean9.3
Median Absolute Deviation (MAD)3
Skewness3.3292486
Sum930
Variance137
MonotonicityNot monotonic
2023-12-10T19:07:56.268192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
5 18
18.0%
3 13
13.0%
4 8
 
8.0%
1 8
 
8.0%
0 5
 
5.0%
9 5
 
5.0%
7 4
 
4.0%
2 4
 
4.0%
15 4
 
4.0%
22 3
 
3.0%
Other values (17) 28
28.0%
ValueCountFrequency (%)
0 5
 
5.0%
1 8
8.0%
2 4
 
4.0%
3 13
13.0%
4 8
8.0%
5 18
18.0%
6 3
 
3.0%
7 4
 
4.0%
8 1
 
1.0%
9 5
 
5.0%
ValueCountFrequency (%)
76 1
 
1.0%
60 1
 
1.0%
48 1
 
1.0%
39 1
 
1.0%
28 1
 
1.0%
24 1
 
1.0%
23 1
 
1.0%
22 3
3.0%
20 1
 
1.0%
19 1
 
1.0%

stag_dt_cnt
Real number (ℝ)

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean149.485
Minimum4
Maximum363
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:56.507392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile19.85
Q175
median149.5
Q3216.5
95-th percentile292
Maximum363
Range359
Interquartile range (IQR)141.5

Descriptive statistics

Standard deviation86.948593
Coefficient of variation (CV)0.5816543
Kurtosis-0.64185219
Mean149.485
Median Absolute Deviation (MAD)73
Skewness0.31926722
Sum14948.5
Variance7560.0579
MonotonicityNot monotonic
2023-12-10T19:07:56.851524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
233.0 2
 
2.0%
163.0 2
 
2.0%
161.0 2
 
2.0%
240.0 2
 
2.0%
160.0 2
 
2.0%
180.0 2
 
2.0%
167.0 2
 
2.0%
47.0 2
 
2.0%
75.0 2
 
2.0%
68.0 1
 
1.0%
Other values (81) 81
81.0%
ValueCountFrequency (%)
4.0 1
1.0%
8.0 1
1.0%
10.0 1
1.0%
11.0 1
1.0%
17.0 1
1.0%
20.0 1
1.0%
23.0 1
1.0%
30.0 1
1.0%
33.0 1
1.0%
42.0 1
1.0%
ValueCountFrequency (%)
363.0 1
1.0%
344.5 1
1.0%
333.0 1
1.0%
330.0 1
1.0%
311.0 1
1.0%
291.0 1
1.0%
281.0 1
1.0%
277.0 1
1.0%
269.0 1
1.0%
260.0 1
1.0%

ehbll_dt_cnt
Text

MISSING 

Distinct69
Distinct (%)85.2%
Missing19
Missing (%)19.0%
Memory size932.0 B
2023-12-10T19:07:57.273925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.4074074
Min length1

Characters and Unicode

Total characters195
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)76.5%

Sample

1st row286
2nd row317
3rd row40
4th row44
5th row309
ValueCountFrequency (%)
0 4
 
4.9%
4
 
4.9%
9 3
 
3.7%
17 2
 
2.5%
109 2
 
2.5%
123 2
 
2.5%
60 2
 
2.5%
243 1
 
1.2%
145 1
 
1.2%
135 1
 
1.2%
Other values (59) 59
72.8%
2023-12-10T19:07:58.143171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 40
20.5%
3 27
13.8%
2 25
12.8%
0 20
10.3%
9 15
 
7.7%
4 15
 
7.7%
7 14
 
7.2%
6 14
 
7.2%
8 11
 
5.6%
5 10
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 191
97.9%
Dash Punctuation 4
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 40
20.9%
3 27
14.1%
2 25
13.1%
0 20
10.5%
9 15
 
7.9%
4 15
 
7.9%
7 14
 
7.3%
6 14
 
7.3%
8 11
 
5.8%
5 10
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 195
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 40
20.5%
3 27
13.8%
2 25
12.8%
0 20
10.3%
9 15
 
7.7%
4 15
 
7.7%
7 14
 
7.2%
6 14
 
7.2%
8 11
 
5.6%
5 10
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 40
20.5%
3 27
13.8%
2 25
12.8%
0 20
10.3%
9 15
 
7.7%
4 15
 
7.7%
7 14
 
7.2%
6 14
 
7.2%
8 11
 
5.6%
5 10
 
5.1%

stag_pchrg_cnt
Text

MISSING 

Distinct90
Distinct (%)93.8%
Missing4
Missing (%)4.0%
Memory size932.0 B
2023-12-10T19:07:58.700773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.4375
Min length1

Characters and Unicode

Total characters426
Distinct characters13
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

Unique88 ?
Unique (%)91.7%

Sample

1st row81415
2nd row2221
3rd row0
4th row31777
5th row52100
ValueCountFrequency (%)
0 6
 
6.2%
1000 2
 
2.1%
10930 1
 
1.0%
15830 1
 
1.0%
81415 1
 
1.0%
3990 1
 
1.0%
38604 1
 
1.0%
64704 1
 
1.0%
30582 1
 
1.0%
4431 1
 
1.0%
Other values (80) 80
83.3%
2023-12-10T19:07:59.505872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 61
14.3%
0 57
13.4%
2 55
12.9%
3 53
12.4%
8 36
8.5%
6 36
8.5%
5 33
7.7%
9 33
7.7%
4 31
7.3%
7 28
6.6%
Other values (3) 3
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 423
99.3%
Other Letter 3
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 61
14.4%
0 57
13.5%
2 55
13.0%
3 53
12.5%
8 36
8.5%
6 36
8.5%
5 33
7.8%
9 33
7.8%
4 31
7.3%
7 28
6.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 423
99.3%
Hangul 3
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 61
14.4%
0 57
13.5%
2 55
13.0%
3 53
12.5%
8 36
8.5%
6 36
8.5%
5 33
7.8%
9 33
7.8%
4 31
7.3%
7 28
6.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 423
99.3%
Hangul 3
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 61
14.4%
0 57
13.5%
2 55
13.0%
3 53
12.5%
8 36
8.5%
6 36
8.5%
5 33
7.8%
9 33
7.8%
4 31
7.3%
7 28
6.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

usemem_tot
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean119896.87
Minimum0
Maximum2125067
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:59.948011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9327.8
Q135460.5
median76220.5
Q3116802.25
95-th percentile300779.35
Maximum2125067
Range2125067
Interquartile range (IQR)81341.75

Descriptive statistics

Standard deviation224663.89
Coefficient of variation (CV)1.8738094
Kurtosis65.311431
Mean119896.87
Median Absolute Deviation (MAD)40863.5
Skewness7.4652982
Sum11989687
Variance5.0473863 × 1010
MonotonicityNot monotonic
2023-12-10T19:08:00.233395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
113310 1
 
1.0%
62517 1
 
1.0%
174735 1
 
1.0%
18589 1
 
1.0%
64141 1
 
1.0%
234814 1
 
1.0%
72171 1
 
1.0%
31882 1
 
1.0%
115730 1
 
1.0%
15714 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
0 1
1.0%
1236 1
1.0%
3989 1
1.0%
5872 1
1.0%
6683 1
1.0%
9467 1
1.0%
12385 1
1.0%
15714 1
1.0%
16660 1
1.0%
16935 1
1.0%
ValueCountFrequency (%)
2125067 1
1.0%
589392 1
1.0%
434274 1
1.0%
382172 1
1.0%
341997 1
1.0%
298610 1
1.0%
280642 1
1.0%
270071 1
1.0%
252649 1
1.0%
234814 1
1.0%

fyer_orpns
Real number (ℝ)

ZEROS 

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4713.0887
Minimum0
Maximum46492
Zeros3
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:08:00.488183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile127.2
Q1767
median1844
Q34378.5
95-th percentile24359.45
Maximum46492
Range46492
Interquartile range (IQR)3611.5

Descriptive statistics

Standard deviation8267.551
Coefficient of variation (CV)1.7541683
Kurtosis11.515532
Mean4713.0887
Median Absolute Deviation (MAD)1428.5
Skewness3.3100796
Sum471308.87
Variance68352399
MonotonicityNot monotonic
2023-12-10T19:08:01.090702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
3.0%
9979.0 2
 
2.0%
1584.0 2
 
2.0%
4343.0 1
 
1.0%
932.0 1
 
1.0%
440.0 1
 
1.0%
1648.0 1
 
1.0%
2195.7 1
 
1.0%
378.0 1
 
1.0%
2984.0 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
0.0 3
3.0%
54.0 1
 
1.0%
55.0 1
 
1.0%
131.0 1
 
1.0%
139.0 1
 
1.0%
154.0 1
 
1.0%
205.0 1
 
1.0%
242.7 1
 
1.0%
244.0 1
 
1.0%
260.0 1
 
1.0%
ValueCountFrequency (%)
46492.0 1
1.0%
40033.0 1
1.0%
32947.0 1
1.0%
32888.0 1
1.0%
28491.0 1
1.0%
24142.0 1
1.0%
13754.0 1
1.0%
11997.0 1
1.0%
10877.0 1
1.0%
10279.0 1
1.0%

ern
Real number (ℝ)

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean442.02
Minimum0
Maximum9379
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:08:01.330181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18.55
Q159.75
median124
Q3370.5
95-th percentile1740.05
Maximum9379
Range9379
Interquartile range (IQR)310.75

Descriptive statistics

Standard deviation1072.6134
Coefficient of variation (CV)2.4266174
Kurtosis49.683486
Mean442.02
Median Absolute Deviation (MAD)91.5
Skewness6.3837257
Sum44202
Variance1150499.5
MonotonicityNot monotonic
2023-12-10T19:08:01.578226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
115 2
 
2.0%
246 2
 
2.0%
64 2
 
2.0%
34 2
 
2.0%
124 2
 
2.0%
104 2
 
2.0%
1054 2
 
2.0%
503 1
 
1.0%
970 1
 
1.0%
19 1
 
1.0%
Other values (83) 83
83.0%
ValueCountFrequency (%)
0 1
1.0%
1 1
1.0%
6 1
1.0%
7 1
1.0%
10 1
1.0%
19 1
1.0%
21 1
1.0%
22 1
1.0%
23 1
1.0%
24 1
1.0%
ValueCountFrequency (%)
9379 1
1.0%
3269 1
1.0%
2972 1
1.0%
2440 1
1.0%
1855 1
1.0%
1734 1
1.0%
1255 1
1.0%
1100 1
1.0%
1054 2
2.0%
993 1
1.0%

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
20210215123123
100 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210215123123
2nd row20210215123123
3rd row20210215123123
4th row20210215123123
5th row20210215123123

Common Values

ValueCountFrequency (%)
20210215123123 100
100.0%

Length

2023-12-10T19:08:01.831382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:02.000539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210215123123 100
100.0%

data_orgn
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
문화데이터총람 2020
100 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row문화데이터총람 2020
2nd row문화데이터총람 2020
3rd row문화데이터총람 2020
4th row문화데이터총람 2020
5th row문화데이터총람 2020

Common Values

ValueCountFrequency (%)
문화데이터총람 2020 100
100.0%

Length

2023-12-10T19:08:02.167285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:02.312654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화데이터총람 100
50.0%
2020 100
50.0%

file_name
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_479_DMSTC_MCST_CLTURARTCENT_2021
100 

Length

Max length35
Median length35
Mean length35
Min length35

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_479_DMSTC_MCST_CLTURARTCENT_2021
2nd rowKC_479_DMSTC_MCST_CLTURARTCENT_2021
3rd rowKC_479_DMSTC_MCST_CLTURARTCENT_2021
4th rowKC_479_DMSTC_MCST_CLTURARTCENT_2021
5th rowKC_479_DMSTC_MCST_CLTURARTCENT_2021

Common Values

ValueCountFrequency (%)
KC_479_DMSTC_MCST_CLTURARTCENT_2021 100
100.0%

Length

2023-12-10T19:08:02.472424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:02.605682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_479_dmstc_mcst_clturartcent_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

2023-12-10T19:08:02.780521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:02.933102image/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_cderc_mbyoper_mbyoper_mby_chartrcttpchmpgopnngdttotarcmplx_seatscmplx_aeaprfplc_seatsprfplc_aeasl_prfplc_seatssl_prfplc_aeaehbll_cntehbll_aeaedu_plce_aeamtg_rum_aeafeld_prfplc_acmd_cntfeld_prfplc_aeaemp_cntexp_emp_cntstag_dt_cntehbll_dt_cntstag_pchrg_cntusemem_totfyer_orpnsernrmlst_updt_dtdata_orgnfile_namebase_ymd
0KCDMSMC21N000000001문화시설문예회관강동아트센터서울특별시강동구1174010300상일동1174052000상일동117403000034서울 강동구 동남로 8705278다사69750237.55122127.157342기초자치단체강동구지자체 직영02-440-0500www.gangdongarts.or.kr2011.09.0118051<NA><NA>85019482504592487.6504<NA><NA><NA>3117311.0286814151133104343.0503<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
1KCDMSMC21N000000254문화시설문예회관제주특별자치도 문예회관제주특별자치도제주시5011010200일도이동5011052000일도2동501103349055제주특별자치도 제주시 동광로 6963270다다10301833.504444126.535172광역자치단체제주특별자치도지자체 직영064-710-7601http://www.jeju.go.kr/jejuculture1988.08.25.7704.3100828507217054431050024.3600326223.031722211798443009.0203<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
2KCDMSMC21N000000003문화시설문예회관관악문화관도서관서울특별시관악구1162010200신림동1162073500대학동116204160522서울 관악구 신림로3길 358825다사50941037.467598126.944871기초자치단체관악문화재단공공기관 위탁02-828-5700www.gfac.or.kr2002.10.1115614.85<NA><NA>698886<NA><NA>1270524<NA><NA><NA>905128.040040297990.021<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
3KCDMSMC21N000000004문화시설문예회관나루아트센터서울특별시광진구1121510500자양동1121584000자양3동112153104007서울 광진구 능동로 765065다사62048737.537571127.070576기초자치단체광진문화재단공공기관 위탁02-2049-4700www.naruart.or.kr2005.05.0218860.5<NA><NA>601853167257.91272.2<NA><NA><NA><NA>169161.04431777355642465.0483<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
4KCDMSMC21N000000005문화시설문예회관구로아트밸리 예술극장서울특별시구로구1153010200구로동1153056000구로5동115304148016서울 구로구 가마산로25길 9-248301다사45944337.496558126.888975기초자치단체(재)구로문화재단공공기관 위탁02-2029-1720https://www.guroartsvalley.or.kr2008.07.228799.8<NA><NA>611136260142.841182<NA><NA><NA><NA>5316243.0309521001220621941.0110<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
5KCDMSMC21N000000006문화시설문예회관금나래아트홀서울특별시금천구1154510300시흥동1154567000시흥1동115454151335서울 금천구 시흥대로73길 708611다사46539937.457066126.896037기초자치단체금천문화재단공공기관 위탁02-2627-2985https://gcfac.or.kr2009.1.31.6262<NA><NA>546755<NA><NA><NA><NA><NA><NA><NA><NA>104117.0137515775552260.055<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
6KCDMSMC21N000000007문화시설문예회관노원문화예술회관서울특별시노원구1135010600중계동1135061900중계본동113503110007서울 노원구 중계로 1811736다사62961237.650237127.080267기초자치단체노원문화재단공공기관 위탁02-2289-3400https://www.nowonart.kr2004.06.1613167.5<NA><NA>6081136.8292530.81183.527689<NA><NA>5611132.09222830730191709.0246<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
7KCDMSMC21N000000255문화시설문예회관제주아트센터제주특별자치도제주시5011012000오라이동5011064000오라동501103349144제주특별자치도 제주시 오남로 23163147다나08598533.475104126.515519광역자치단체제주시지자체 직영064-728-8952http://www.jejusi.go.kr/acenter/index.do2010.05.199482.7911842251000000251<NA>00234180.0910086693801956.0266<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
8KCDMSMC21N000000009문화시설문예회관서대문문화체육회관서울특별시서대문구1141011800홍은동1141068500홍은2동114104136099서울 서대문구 백련사길 393657다사49853637.58076126.931557기초자치단체서대문구도시관리공단공공기관 위탁02-360-8555http://www.sscmc.or.kr1993.10.15.9886.8--589785.7180289.81117.11397.430.7--28523.01574512276901345.22100<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
9KCDMSMC21N000000010문화시설문예회관서초문화예술회관서울특별시서초구1165010200양재동1165065100양재1동116502102001서울 서초구 강남대로 2016749다사58942637.481828127.035957기초자치단체서초구지자체직영02-2155-8301http://www.seocho.go.kr1989.11.134068<NA><NA>657833.2100207.41103.760.249.9<NA><NA>121252.019100083000692.028<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cderc_mbyoper_mbyoper_mby_chartrcttpchmpgopnngdttotarcmplx_seatscmplx_aeaprfplc_seatsprfplc_aeasl_prfplc_seatssl_prfplc_aeaehbll_cntehbll_aeaedu_plce_aeamtg_rum_aeafeld_prfplc_acmd_cntfeld_prfplc_aeaemp_cntexp_emp_cntstag_dt_cntehbll_dt_cntstag_pchrg_cntusemem_totfyer_orpnsernrmlst_updt_dtdata_orgnfile_namebase_ymd
90KCDMSMC21N000000091문화시설문예회관남부문화예술회관경기도평택시4122011800비전동4122063000비전2동412203188084경기 평택시 중앙로 27717901다바65688136.991134127.114086기초자치단체평택시지자체 직영031-8024-5415www.pyeongtaek.go.kr1993.11.026725<NA><NA>6061062256246131050132<NA><NA>103194.017514961040071833.0122<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
91KCDMSMC21N000000092문화시설문예회관북부문화예술회관경기도평택시4122010100서정동4122052000서정동412202012013경기 평택시 경기대로 136617730다바61396437.065812127.065091기초자치단체평택시지자체 직영031-8024-7391www.pyeongtaek.go.kr1991.12.075097<NA><NA>63116962824861330<NA><NA><NA><NA>6359.0927920450700.030<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
92KCDMSMC21N000000093문화시설문예회관서부문화예술회관경기도평택시4122025322안중읍 학현리4122025300안중읍412202012006경기 평택시 안중읍 서동대로 153117816다바48488136.990137126.920152기초자치단체평택시지자체 직영031-8024-8321www.pyeongtaek.go.kr1991.10.295417<NA><NA>7681025168486<NA><NA><NA><NA><NA><NA>5363.0<NA>15925246170.041<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
93KCDMSMC21N000000094문화시설문예회관파주시민회관경기도파주시4148010100금촌동4148051000금촌1동414804418518경기 파주시 시민회관길 3310932다사36673537.759193126.780722기초자치단체파주시시설관리공단공공기관 위탁031-950-1854www.pajucf.or.kr1994.09.277511<NA><NA>497,3023671.71 ,2570.78<NA><NA>1111.7<NA><NA>50092210130.013916100273678.064<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
94KCDMSMC21N000000095문화시설문예회관문산행복센터경기도파주시4148025023문산읍 선유리4148025000문산읍414803000008경기 파주시 문산읍 통일로 168010813다사37684337.856751126.791016기초자치단체파주시시설관리공단공공기관 위탁031-950-1897www.pajucf.or.kr2011.05.0217784.1<NA><NA>4631159.63100230.11299.17<NA><NA><NA><NA>13175.038<NA>63532205.054<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
95KCDMSMC21N000000096문화시설문예회관운정행복센터경기도파주시4148012200와동동4148055000운정1동414803206063경기 파주시 와석순환로 41510894다사34069637.723875126.751227기초자치단체파주시시설관리공단공공기관 위탁031-950-1919www.pajucf.or.kr2013.05.0229310.83<NA><NA>5421703.23200591.88<NA><NA><NA><NA><NA><NA>163126.033382582713154.074<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
96KCDMSMC21N000000097문화시설문예회관솔가람아트홀경기도파주시4148012200와동동4148055000운정1동414804418987경기 파주시 가람로116번길 17010895다사35070337.730512126.763396기초자치단체파주시시설관리공단공공기관 위탁031-950-1957www.pajucf.or.kr2014.04.283861.72<NA><NA>300428.22<NA><NA><NA><NA><NA><NA><NA><NA>1117.0<NA><NA>5872131.024<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
97KCDMSMC21N000000098문화시설문예회관의정부예술의전당경기도의정부시4115010100의정부동4115052000의정부2동411503181037경기 의정부시 의정로 111622다사58970537.733385127.034129기초자치단체(재)의정부문화재단공공기관 위탁031-828-5841www.uac.or.kr2001.04.0622372.3810251147.92<NA><NA>233866.843740976460<NA><NA>6012180.03463689820446310877.0993<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
98KCDMSMC21N000000099문화시설문예회관김포아트홀경기도김포시4157010600사우동4157054000사우동415703209043경기 김포시 돌문로 2610110다사31158037.61893126.72015기초자치단체(재)김포문화재단공공기관 위탁031-996-1603www.gcf.or.kr2014.04.019008<NA><NA>5032167<NA><NA>1370126<NA><NA><NA>274163.021964231029769695.0192<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101
99KCDMSMC21N000000100문화시설문예회관남한산성아트홀경기도광주시4161010300송정동4161052000송정동416102012015경기 광주시 회안대로 89112746다사78236437.426868127.254706기초자치단체광주도시관리공사공공기관 위탁031-798-9880www.nsart.or.kr2011.09.28605410681755<NA><NA>2703902397<NA><NA><NA><NA>2715163.06010090993123161.0277<NA>20210215123123문화데이터총람 2020KC_479_DMSTC_MCST_CLTURARTCENT_202120200101