Overview

Dataset statistics

Number of variables27
Number of observations100
Missing cells252
Missing cells (%)9.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.3 KiB
Average record size in memory228.3 B

Variable types

Text10
Categorical8
Numeric8
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
branch_nm has 90 (90.0%) missing valuesMissing
sub_nm has 100 (100.0%) missing valuesMissing
ri_nm has 62 (62.0%) missing valuesMissing
id has unique valuesUnique
id_poi has unique valuesUnique
pnu has unique valuesUnique
badm_cd has unique valuesUnique
rd_cd has unique valuesUnique
x has unique valuesUnique
y has unique valuesUnique
grid_cd has unique valuesUnique
sub_nm is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 09:55:03.085542
Analysis finished2023-12-10 09:55:04.110296
Duration1.02 second
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
2023-12-10T18:55:04.384158image/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 rowKCRSTPO21N000000001
2nd rowKCRSTPO21N000884305
3rd rowKCRSTPO21N000000003
4th rowKCRSTPO21N000000004
5th rowKCRSTPO21N000000005
ValueCountFrequency (%)
kcrstpo21n000000001 1
 
1.0%
kcrstpo21n000000063 1
 
1.0%
kcrstpo21n000000074 1
 
1.0%
kcrstpo21n000000073 1
 
1.0%
kcrstpo21n000000072 1
 
1.0%
kcrstpo21n000000071 1
 
1.0%
kcrstpo21n000000070 1
 
1.0%
kcrstpo21n000000069 1
 
1.0%
kcrstpo21n000000068 1
 
1.0%
kcrstpo21n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:55:05.165457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 708
37.3%
1 121
 
6.4%
2 118
 
6.2%
K 100
 
5.3%
O 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
P 100
 
5.3%
T 100
 
5.3%
S 100
 
5.3%
Other values (8) 253
 
13.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 708
64.4%
1 121
 
11.0%
2 118
 
10.7%
8 25
 
2.3%
4 23
 
2.1%
3 22
 
2.0%
5 21
 
1.9%
6 21
 
1.9%
7 21
 
1.9%
9 20
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
K 100
12.5%
O 100
12.5%
C 100
12.5%
N 100
12.5%
P 100
12.5%
T 100
12.5%
S 100
12.5%
R 100
12.5%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 708
64.4%
1 121
 
11.0%
2 118
 
10.7%
8 25
 
2.3%
4 23
 
2.1%
3 22
 
2.0%
5 21
 
1.9%
6 21
 
1.9%
7 21
 
1.9%
9 20
 
1.8%
Latin
ValueCountFrequency (%)
K 100
12.5%
O 100
12.5%
C 100
12.5%
N 100
12.5%
P 100
12.5%
T 100
12.5%
S 100
12.5%
R 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 708
37.3%
1 121
 
6.4%
2 118
 
6.2%
K 100
 
5.3%
O 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
P 100
 
5.3%
T 100
 
5.3%
S 100
 
5.3%
Other values (8) 253
 
13.3%

lclas
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장소 100
100.0%

Length

2023-12-10T18:55:05.470348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:05.655919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장소 100
100.0%

mlsfc
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식당 100
100.0%

Length

2023-12-10T18:55:06.276062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:06.606705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식당 100
100.0%

id_poi
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4986780.3
Minimum106901
Maximum22234084
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:06.910384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106901
5-th percentile148339.4
Q14950779
median5472146.5
Q35831277
95-th percentile5908777
Maximum22234084
Range22127183
Interquartile range (IQR)880498

Descriptive statistics

Standard deviation3688885.8
Coefficient of variation (CV)0.73973297
Kurtosis12.794646
Mean4986780.3
Median Absolute Deviation (MAD)426194
Skewness2.7748193
Sum4.9867803 × 108
Variance1.3607878 × 1013
MonotonicityNot monotonic
2023-12-10T18:55:07.304039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
106901 1
 
1.0%
5721374 1
 
1.0%
5796903 1
 
1.0%
5793986 1
 
1.0%
5790781 1
 
1.0%
5788880 1
 
1.0%
5786714 1
 
1.0%
5786191 1
 
1.0%
5784057 1
 
1.0%
5780576 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
106901 1
1.0%
112539 1
1.0%
113020 1
1.0%
113344 1
1.0%
135275 1
1.0%
149027 1
1.0%
219114 1
1.0%
414923 1
1.0%
415754 1
1.0%
417535 1
1.0%
ValueCountFrequency (%)
22234084 1
1.0%
22233880 1
1.0%
22233852 1
1.0%
5910274 1
1.0%
5910258 1
1.0%
5908699 1
1.0%
5908489 1
1.0%
5908443 1
1.0%
5908411 1
1.0%
5908194 1
1.0%

poi_nm
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:07.814534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length5.11
Min length1

Characters and Unicode

Total characters511
Distinct characters201
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

Unique98 ?
Unique (%)98.0%

Sample

1st row남지횟집
2nd row아랑경양회관
3rd row고성횟집
4th row부산횟집
5th row산호횟집
ValueCountFrequency (%)
다사랑치킨피자 2
 
2.0%
한일가든 1
 
1.0%
바다횟집 1
 
1.0%
일산칼국수 1
 
1.0%
푸른횟집 1
 
1.0%
1
 
1.0%
항아리식당 1
 
1.0%
고바우순대 1
 
1.0%
창평시장국밥 1
 
1.0%
동백가든 1
 
1.0%
Other values (89) 89
89.0%
2023-12-10T18:55:08.689628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
3.7%
18
 
3.5%
16
 
3.1%
16
 
3.1%
14
 
2.7%
13
 
2.5%
10
 
2.0%
8
 
1.6%
6
 
1.2%
6
 
1.2%
Other values (191) 385
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 506
99.0%
Decimal Number 5
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
19
 
3.8%
18
 
3.6%
16
 
3.2%
16
 
3.2%
14
 
2.8%
13
 
2.6%
10
 
2.0%
8
 
1.6%
6
 
1.2%
6
 
1.2%
Other values (187) 380
75.1%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
5 1
20.0%
8 1
20.0%
3 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 506
99.0%
Common 5
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
19
 
3.8%
18
 
3.6%
16
 
3.2%
16
 
3.2%
14
 
2.8%
13
 
2.6%
10
 
2.0%
8
 
1.6%
6
 
1.2%
6
 
1.2%
Other values (187) 380
75.1%
Common
ValueCountFrequency (%)
1 2
40.0%
5 1
20.0%
8 1
20.0%
3 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 506
99.0%
ASCII 5
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
19
 
3.8%
18
 
3.6%
16
 
3.2%
16
 
3.2%
14
 
2.8%
13
 
2.6%
10
 
2.0%
8
 
1.6%
6
 
1.2%
6
 
1.2%
Other values (187) 380
75.1%
ASCII
ValueCountFrequency (%)
1 2
40.0%
5 1
20.0%
8 1
20.0%
3 1
20.0%

branch_nm
Text

MISSING 

Distinct8
Distinct (%)80.0%
Missing90
Missing (%)90.0%
Memory size932.0 B
2023-12-10T18:55:09.015638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.9
Min length2

Characters and Unicode

Total characters29
Distinct characters17
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

Unique7 ?
Unique (%)70.0%

Sample

1st row구리점
2nd row수성점
3rd row본점
4th row송탄점
5th row본점
ValueCountFrequency (%)
본점 3
30.0%
구리점 1
 
10.0%
수성점 1
 
10.0%
송탄점 1
 
10.0%
거창점 1
 
10.0%
순창점 1
 
10.0%
김해어방점 1
 
10.0%
서학점 1
 
10.0%
2023-12-10T18:55:09.690288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
34.5%
3
 
10.3%
2
 
6.9%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
Other values (7) 7
24.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10
34.5%
3
 
10.3%
2
 
6.9%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
Other values (7) 7
24.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10
34.5%
3
 
10.3%
2
 
6.9%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
Other values (7) 7
24.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
10
34.5%
3
 
10.3%
2
 
6.9%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
Other values (7) 7
24.1%

sub_nm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

mcate_cd
Real number (ℝ)

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81021.97
Minimum80611
Maximum81204
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:10.006425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum80611
5-th percentile81001
Q181001
median81001
Q381011.25
95-th percentile81201
Maximum81204
Range593
Interquartile range (IQR)10.25

Descriptive statistics

Standard deviation110.48684
Coefficient of variation (CV)0.0013636652
Kurtosis6.018468
Mean81021.97
Median Absolute Deviation (MAD)0
Skewness-1.4007768
Sum8102197
Variance12207.343
MonotonicityNot monotonic
2023-12-10T18:55:10.432888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
81001 56
56.0%
81201 14
 
14.0%
81004 5
 
5.0%
81101 4
 
4.0%
80615 3
 
3.0%
81006 3
 
3.0%
81009 2
 
2.0%
81003 2
 
2.0%
81012 2
 
2.0%
81017 2
 
2.0%
Other values (7) 7
 
7.0%
ValueCountFrequency (%)
80611 1
 
1.0%
80615 3
 
3.0%
81001 56
56.0%
81002 1
 
1.0%
81003 2
 
2.0%
81004 5
 
5.0%
81006 3
 
3.0%
81009 2
 
2.0%
81010 1
 
1.0%
81011 1
 
1.0%
ValueCountFrequency (%)
81204 1
 
1.0%
81201 14
14.0%
81105 1
 
1.0%
81101 4
 
4.0%
81017 2
 
2.0%
81015 1
 
1.0%
81012 2
 
2.0%
81011 1
 
1.0%
81010 1
 
1.0%
81009 2
 
2.0%

mcate_nm
Categorical

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
일반한식
56 
생선회
14 
갈비/불고기
 
5
경양식
 
4
치킨
 
3
Other values (12)
18 

Length

Max length6
Median length4
Mean length3.84
Min length2

Unique

Unique7 ?
Unique (%)7.0%

Sample

1st row생선회
2nd row경양식
3rd row생선회
4th row생선회
5th row생선회

Common Values

ValueCountFrequency (%)
일반한식 56
56.0%
생선회 14
 
14.0%
갈비/불고기 5
 
5.0%
경양식 4
 
4.0%
치킨 3
 
3.0%
닭/오리구이 3
 
3.0%
분식 2
 
2.0%
해물요리 2
 
2.0%
삼겹살 2
 
2.0%
냉면 2
 
2.0%
Other values (7) 7
 
7.0%

Length

2023-12-10T18:55:10.884045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반한식 56
56.0%
생선회 14
 
14.0%
갈비/불고기 5
 
5.0%
경양식 4
 
4.0%
치킨 3
 
3.0%
닭/오리구이 3
 
3.0%
냉면 2
 
2.0%
삼겹살 2
 
2.0%
해물요리 2
 
2.0%
분식 2
 
2.0%
Other values (7) 7
 
7.0%

pnu
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9604501 × 1018
Minimum1.1140129 × 1018
Maximum5.013032 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:11.273901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1140129 × 1018
5-th percentile1.1668105 × 1018
Q14.126587 × 1018
median4.3113103 × 1018
Q34.6365273 × 1018
95-th percentile5.0111248 × 1018
Maximum5.013032 × 1018
Range3.8990191 × 1018
Interquartile range (IQR)5.0994033 × 1017

Descriptive statistics

Standard deviation1.0710584 × 1018
Coefficient of variation (CV)0.27043855
Kurtosis1.4516268
Mean3.9604501 × 1018
Median Absolute Deviation (MAD)3.0772228 × 1017
Skewness-1.5438936
Sum8.663384 × 1018
Variance1.1471661 × 1036
MonotonicityNot monotonic
2023-12-10T18:55:11.786219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2614010600102490012 1
 
1.0%
4785025621102130002 1
 
1.0%
4613012500100580000 1
 
1.0%
4817013200106140001 1
 
1.0%
4128510600111580005 1
 
1.0%
4713032022101670002 1
 
1.0%
2726011100101750001 1
 
1.0%
4283025038101940002 1
 
1.0%
4313012700120700000 1
 
1.0%
4577025021101130014 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1114012900100140008 1
1.0%
1114016100100460013 1
1.0%
1120010500107920000 1
1.0%
1141011600100520075 1
1.0%
1144011000100310090 1
1.0%
1168010500101070000 1
1.0%
1171010300104010004 1
1.0%
1171011200100080004 1
1.0%
2611013800100010001 1
1.0%
2614010600102490012 1
1.0%
ValueCountFrequency (%)
5013032023116500003 1
1.0%
5013032021100400044 1
1.0%
5013011900121190000 1
1.0%
5013011600101420013 1
1.0%
5013010100100700000 1
1.0%
5011025625126020004 1
1.0%
5011010200103290005 1
1.0%
4888025022102830008 1
1.0%
4833010700108940003 1
1.0%
4831033023100500000 1
1.0%

sido_nm
Categorical

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기도
16 
전라북도
11 
충청북도
강원도
서울특별시
Other values (11)
49 

Length

Max length7
Median length5
Mean length4.23
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row부산광역시
2nd row경기도
3rd row부산광역시
4th row울산광역시
5th row충청북도

Common Values

ValueCountFrequency (%)
경기도 16
16.0%
전라북도 11
11.0%
충청북도 8
8.0%
강원도 8
8.0%
서울특별시 8
8.0%
경상남도 8
8.0%
전라남도 7
7.0%
경상북도 7
7.0%
제주특별자치도 7
7.0%
부산광역시 6
 
6.0%
Other values (6) 14
14.0%

Length

2023-12-10T18:55:12.339249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 16
16.0%
전라북도 11
11.0%
충청북도 8
8.0%
강원도 8
8.0%
서울특별시 8
8.0%
경상남도 8
8.0%
전라남도 7
7.0%
경상북도 7
7.0%
제주특별자치도 7
7.0%
부산광역시 6
 
6.0%
Other values (6) 14
14.0%

sgg_nm
Text

Distinct70
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:13.064874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.43
Min length2

Characters and Unicode

Total characters343
Distinct characters83
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

Unique50 ?
Unique (%)50.0%

Sample

1st row서구
2nd row구리시
3rd row수영구
4th row북구
5th row청주시 서원구
ValueCountFrequency (%)
서귀포시 5
 
4.5%
익산시 5
 
4.5%
청주시 4
 
3.6%
양평군 3
 
2.7%
중구 3
 
2.7%
고양시 3
 
2.7%
북구 3
 
2.7%
전주시 3
 
2.7%
완산구 3
 
2.7%
김해시 2
 
1.8%
Other values (63) 76
69.1%
2023-12-10T18:55:13.891289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
62
18.1%
34
 
9.9%
19
 
5.5%
17
 
5.0%
15
 
4.4%
12
 
3.5%
10
 
2.9%
10
 
2.9%
9
 
2.6%
6
 
1.7%
Other values (73) 149
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 333
97.1%
Space Separator 10
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
62
18.6%
34
 
10.2%
19
 
5.7%
17
 
5.1%
15
 
4.5%
12
 
3.6%
10
 
3.0%
9
 
2.7%
6
 
1.8%
6
 
1.8%
Other values (72) 143
42.9%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 333
97.1%
Common 10
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
62
18.6%
34
 
10.2%
19
 
5.7%
17
 
5.1%
15
 
4.5%
12
 
3.6%
10
 
3.0%
9
 
2.7%
6
 
1.8%
6
 
1.8%
Other values (72) 143
42.9%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 333
97.1%
ASCII 10
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
62
18.6%
34
 
10.2%
19
 
5.7%
17
 
5.1%
15
 
4.5%
12
 
3.6%
10
 
3.0%
9
 
2.7%
6
 
1.8%
6
 
1.8%
Other values (72) 143
42.9%
ASCII
ValueCountFrequency (%)
10
100.0%
Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:14.587799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.18
Min length2

Characters and Unicode

Total characters318
Distinct characters114
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 row서대신동3가
2nd row인창동
3rd row민락동
4th row정자동
5th row모충동
ValueCountFrequency (%)
양평읍 2
 
2.0%
표선면 2
 
2.0%
어방동 1
 
1.0%
순창읍 1
 
1.0%
서대신동3가 1
 
1.0%
대포동 1
 
1.0%
만흥동 1
 
1.0%
호탄동 1
 
1.0%
백석동 1
 
1.0%
양남면 1
 
1.0%
Other values (88) 88
88.0%
2023-12-10T18:55:15.914104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
65
 
20.4%
24
 
7.5%
14
 
4.4%
9
 
2.8%
9
 
2.8%
7
 
2.2%
6
 
1.9%
5
 
1.6%
5
 
1.6%
5
 
1.6%
Other values (104) 169
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 311
97.8%
Decimal Number 7
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
65
20.9%
24
 
7.7%
14
 
4.5%
9
 
2.9%
9
 
2.9%
7
 
2.3%
6
 
1.9%
5
 
1.6%
5
 
1.6%
5
 
1.6%
Other values (101) 162
52.1%
Decimal Number
ValueCountFrequency (%)
2 3
42.9%
1 2
28.6%
3 2
28.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 311
97.8%
Common 7
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
65
20.9%
24
 
7.7%
14
 
4.5%
9
 
2.9%
9
 
2.9%
7
 
2.3%
6
 
1.9%
5
 
1.6%
5
 
1.6%
5
 
1.6%
Other values (101) 162
52.1%
Common
ValueCountFrequency (%)
2 3
42.9%
1 2
28.6%
3 2
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 311
97.8%
ASCII 7
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
65
20.9%
24
 
7.7%
14
 
4.5%
9
 
2.9%
9
 
2.9%
7
 
2.3%
6
 
1.9%
5
 
1.6%
5
 
1.6%
5
 
1.6%
Other values (101) 162
52.1%
ASCII
ValueCountFrequency (%)
2 3
42.9%
1 2
28.6%
3 2
28.6%

ri_nm
Text

MISSING 

Distinct38
Distinct (%)100.0%
Missing62
Missing (%)62.0%
Memory size932.0 B
2023-12-10T18:55:16.389825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0526316
Min length2

Characters and Unicode

Total characters116
Distinct characters62
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

Unique38 ?
Unique (%)100.0%

Sample

1st row양근리
2nd row금구리
3rd row분천리
4th row이천리
5th row사암리
ValueCountFrequency (%)
마전리 1
 
2.6%
신용리 1
 
2.6%
하오안리 1
 
2.6%
용담리 1
 
2.6%
대하리 1
 
2.6%
중앙리 1
 
2.6%
현리 1
 
2.6%
표선리 1
 
2.6%
월암리 1
 
2.6%
공흥리 1
 
2.6%
Other values (28) 28
73.7%
2023-12-10T18:55:17.312630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38
32.8%
3
 
2.6%
3
 
2.6%
3
 
2.6%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
Other values (52) 57
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 116
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
38
32.8%
3
 
2.6%
3
 
2.6%
3
 
2.6%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
Other values (52) 57
49.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 116
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
38
32.8%
3
 
2.6%
3
 
2.6%
3
 
2.6%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
Other values (52) 57
49.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 116
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
38
32.8%
3
 
2.6%
3
 
2.6%
3
 
2.6%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
Other values (52) 57
49.1%

beonji
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:17.885719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.8
Min length2

Characters and Unicode

Total characters480
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

Unique98 ?
Unique (%)98.0%

Sample

1st row249-12
2nd row576-10
3rd row181-43
4th row683
5th row135-11
ValueCountFrequency (%)
167-2 2
 
2.0%
187-4 1
 
1.0%
58 1
 
1.0%
1158-5 1
 
1.0%
175-1 1
 
1.0%
194-2 1
 
1.0%
2070 1
 
1.0%
113-14 1
 
1.0%
33-1 1
 
1.0%
767-1 1
 
1.0%
Other values (89) 89
89.0%
2023-12-10T18:55:18.815397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 97
20.2%
- 79
16.5%
2 48
10.0%
7 41
8.5%
6 36
 
7.5%
3 36
 
7.5%
4 33
 
6.9%
8 29
 
6.0%
5 29
 
6.0%
9 26
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 401
83.5%
Dash Punctuation 79
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 97
24.2%
2 48
12.0%
7 41
10.2%
6 36
 
9.0%
3 36
 
9.0%
4 33
 
8.2%
8 29
 
7.2%
5 29
 
7.2%
9 26
 
6.5%
0 26
 
6.5%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 480
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 97
20.2%
- 79
16.5%
2 48
10.0%
7 41
8.5%
6 36
 
7.5%
3 36
 
7.5%
4 33
 
6.9%
8 29
 
6.0%
5 29
 
6.0%
9 26
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 480
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 97
20.2%
- 79
16.5%
2 48
10.0%
7 41
8.5%
6 36
 
7.5%
3 36
 
7.5%
4 33
 
6.9%
8 29
 
6.0%
5 29
 
6.0%
9 26
 
5.4%

badm_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9604501 × 109
Minimum1.1140129 × 109
Maximum5.013032 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:19.156295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1140129 × 109
5-th percentile1.1668105 × 109
Q14.126587 × 109
median4.3113102 × 109
Q34.6365273 × 109
95-th percentile5.0111248 × 109
Maximum5.013032 × 109
Range3.8990191 × 109
Interquartile range (IQR)5.0994033 × 108

Descriptive statistics

Standard deviation1.0710584 × 109
Coefficient of variation (CV)0.27043855
Kurtosis1.4516268
Mean3.9604501 × 109
Median Absolute Deviation (MAD)3.0772228 × 108
Skewness-1.5438936
Sum3.9604501 × 1011
Variance1.1471661 × 1018
MonotonicityNot monotonic
2023-12-10T18:55:19.504183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2614010600 1
 
1.0%
4785025621 1
 
1.0%
4613012500 1
 
1.0%
4817013200 1
 
1.0%
4128510600 1
 
1.0%
4713032022 1
 
1.0%
2726011100 1
 
1.0%
4283025038 1
 
1.0%
4313012700 1
 
1.0%
4577025021 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1114012900 1
1.0%
1114016100 1
1.0%
1120010500 1
1.0%
1141011600 1
1.0%
1144011000 1
1.0%
1168010500 1
1.0%
1171010300 1
1.0%
1171011200 1
1.0%
2611013800 1
1.0%
2614010600 1
1.0%
ValueCountFrequency (%)
5013032023 1
1.0%
5013032021 1
1.0%
5013011900 1
1.0%
5013011600 1
1.0%
5013010100 1
1.0%
5011025625 1
1.0%
5011010200 1
1.0%
4888025022 1
1.0%
4833010700 1
1.0%
4831033023 1
1.0%

hadm_cd
Real number (ℝ)

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9604802 × 109
Minimum1.114055 × 109
Maximum5.013062 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:19.855231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.114055 × 109
5-th percentile1.1668581 × 109
Q14.1266356 × 109
median4.311353 × 109
Q34.6365272 × 109
95-th percentile5.011151 × 109
Maximum5.013062 × 109
Range3.899007 × 109
Interquartile range (IQR)5.0989162 × 108

Descriptive statistics

Standard deviation1.0710488 × 109
Coefficient of variation (CV)0.27043408
Kurtosis1.4516773
Mean3.9604802 × 109
Median Absolute Deviation (MAD)3.076795 × 108
Skewness-1.5439041
Sum3.9604802 × 1011
Variance1.1471456 × 1018
MonotonicityNot monotonic
2023-12-10T18:55:20.210583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5013032000 2
 
2.0%
3120054000 2
 
2.0%
4183025000 2
 
2.0%
4128163000 2
 
2.0%
4577025000 1
 
1.0%
4514056000 1
 
1.0%
4713025000 1
 
1.0%
4613076500 1
 
1.0%
4817074000 1
 
1.0%
4128555100 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
1114055000 1
1.0%
1114060500 1
1.0%
1120054000 1
1.0%
1141058500 1
1.0%
1144060000 1
1.0%
1168058000 1
1.0%
1171052000 1
1.0%
1171057000 1
1.0%
2611057000 1
1.0%
2614056000 1
1.0%
ValueCountFrequency (%)
5013062000 1
1.0%
5013060000 1
1.0%
5013051000 1
1.0%
5013032000 2
2.0%
5011052000 1
1.0%
5011025600 1
1.0%
4888025000 1
1.0%
4833052000 1
1.0%
4831033000 1
1.0%
4825059000 1
1.0%

rd_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9604679 × 1011
Minimum1.114041 × 1011
Maximum5.0130485 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:20.525151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.114041 × 1011
5-th percentile1.1668217 × 1011
Q14.1266099 × 1011
median4.3113324 × 1011
Q34.6365363 × 1011
95-th percentile5.0111335 × 1011
Maximum5.0130485 × 1011
Range3.8990075 × 1011
Interquartile range (IQR)5.0992646 × 1010

Descriptive statistics

Standard deviation1.0710551 × 1011
Coefficient of variation (CV)0.2704365
Kurtosis1.4516444
Mean3.9604679 × 1011
Median Absolute Deviation (MAD)3.0770731 × 1010
Skewness-1.5438967
Sum3.9604679 × 1013
Variance1.147159 × 1022
MonotonicityNot monotonic
2023-12-10T18:55:20.827852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
261404178061 1
 
1.0%
478504766354 1
 
1.0%
461304646319 1
 
1.0%
481704797670 1
 
1.0%
412854379100 1
 
1.0%
471304715711 1
 
1.0%
272603146011 1
 
1.0%
428304505049 1
 
1.0%
431302246001 1
 
1.0%
457703278035 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
111404103226 1
1.0%
111404103328 1
1.0%
112003005009 1
1.0%
114104136245 1
1.0%
114403005016 1
1.0%
116802122002 1
1.0%
117103123023 1
1.0%
117104169454 1
1.0%
261103125004 1
1.0%
261403126009 1
1.0%
ValueCountFrequency (%)
501304850542 1
1.0%
501303350263 1
1.0%
501303350258 1
1.0%
501303350145 1
1.0%
501303350090 1
1.0%
501103349234 1
1.0%
501103349007 1
1.0%
488803347018 1
1.0%
483303338098 1
1.0%
483104811427 1
1.0%

rd_nm
Text

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:21.348667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.71
Min length3

Characters and Unicode

Total characters471
Distinct characters139
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

Unique95 ?
Unique (%)95.0%

Sample

1st row구덕로345번길
2nd row응달말로
3rd row광안해변로279번길
4th row정자7길
5th row남들로
ValueCountFrequency (%)
중앙로 3
 
3.0%
동해안로 2
 
2.0%
행주로 1
 
1.0%
용마루1길 1
 
1.0%
호탄길21번길 1
 
1.0%
백석로108번길 1
 
1.0%
수렴길 1
 
1.0%
무학로 1
 
1.0%
단지길 1
 
1.0%
중원대로 1
 
1.0%
Other values (87) 87
87.0%
2023-12-10T18:55:22.137894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
83
 
17.6%
43
 
9.1%
2 19
 
4.0%
18
 
3.8%
16
 
3.4%
1 14
 
3.0%
3 10
 
2.1%
9 9
 
1.9%
8
 
1.7%
7
 
1.5%
Other values (129) 244
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 399
84.7%
Decimal Number 72
 
15.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
83
20.8%
43
 
10.8%
18
 
4.5%
16
 
4.0%
8
 
2.0%
7
 
1.8%
6
 
1.5%
6
 
1.5%
6
 
1.5%
6
 
1.5%
Other values (119) 200
50.1%
Decimal Number
ValueCountFrequency (%)
2 19
26.4%
1 14
19.4%
3 10
13.9%
9 9
12.5%
5 6
 
8.3%
7 5
 
6.9%
0 5
 
6.9%
4 2
 
2.8%
8 1
 
1.4%
6 1
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 399
84.7%
Common 72
 
15.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
83
20.8%
43
 
10.8%
18
 
4.5%
16
 
4.0%
8
 
2.0%
7
 
1.8%
6
 
1.5%
6
 
1.5%
6
 
1.5%
6
 
1.5%
Other values (119) 200
50.1%
Common
ValueCountFrequency (%)
2 19
26.4%
1 14
19.4%
3 10
13.9%
9 9
12.5%
5 6
 
8.3%
7 5
 
6.9%
0 5
 
6.9%
4 2
 
2.8%
8 1
 
1.4%
6 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 399
84.7%
ASCII 72
 
15.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
83
20.8%
43
 
10.8%
18
 
4.5%
16
 
4.0%
8
 
2.0%
7
 
1.8%
6
 
1.5%
6
 
1.5%
6
 
1.5%
6
 
1.5%
Other values (119) 200
50.1%
ASCII
ValueCountFrequency (%)
2 19
26.4%
1 14
19.4%
3 10
13.9%
9 9
12.5%
5 6
 
8.3%
7 5
 
6.9%
0 5
 
6.9%
4 2
 
2.8%
8 1
 
1.4%
6 1
 
1.4%
Distinct85
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:22.721873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length2.8
Min length1

Characters and Unicode

Total characters280
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

Unique71 ?
Unique (%)71.0%

Sample

1st row20
2nd row51
3rd row23
4th row22-5
5th row45-1
ValueCountFrequency (%)
31 3
 
3.0%
8 2
 
2.0%
53 2
 
2.0%
7 2
 
2.0%
23 2
 
2.0%
4 2
 
2.0%
51 2
 
2.0%
74 2
 
2.0%
49 2
 
2.0%
13 2
 
2.0%
Other values (75) 79
79.0%
2023-12-10T18:55:23.529507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 54
19.3%
2 43
15.4%
3 32
11.4%
4 32
11.4%
6 21
 
7.5%
5 20
 
7.1%
7 19
 
6.8%
- 19
 
6.8%
9 15
 
5.4%
0 13
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 261
93.2%
Dash Punctuation 19
 
6.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 54
20.7%
2 43
16.5%
3 32
12.3%
4 32
12.3%
6 21
 
8.0%
5 20
 
7.7%
7 19
 
7.3%
9 15
 
5.7%
0 13
 
5.0%
8 12
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 280
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 54
19.3%
2 43
15.4%
3 32
11.4%
4 32
11.4%
6 21
 
7.5%
5 20
 
7.1%
7 19
 
6.8%
- 19
 
6.8%
9 15
 
5.4%
0 13
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 280
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 54
19.3%
2 43
15.4%
3 32
11.4%
4 32
11.4%
6 21
 
7.5%
5 20
 
7.1%
7 19
 
6.8%
- 19
 
6.8%
9 15
 
5.4%
0 13
 
4.6%

x
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.65264
Minimum126.39432
Maximum129.49489
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:23.854194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.39432
5-th percentile126.53829
Q1126.97358
median127.45442
Q3128.33181
95-th percentile129.13438
Maximum129.49489
Range3.1005723
Interquartile range (IQR)1.3582355

Descriptive statistics

Standard deviation0.87491886
Coefficient of variation (CV)0.0068539035
Kurtosis-0.87108249
Mean127.65264
Median Absolute Deviation (MAD)0.60608502
Skewness0.59294528
Sum12765.264
Variance0.76548302
MonotonicityNot monotonic
2023-12-10T18:55:24.242164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.014416117563 1
 
1.0%
128.446098786164 1
 
1.0%
127.744088607675 1
 
1.0%
128.113909946366 1
 
1.0%
126.788392366039 1
 
1.0%
129.460197154001 1
 
1.0%
128.617530011262 1
 
1.0%
128.589138850599 1
 
1.0%
127.923170199578 1
 
1.0%
127.140697761994 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.394319712107 1
1.0%
126.408156047969 1
1.0%
126.497172953069 1
1.0%
126.509097451874 1
1.0%
126.513661865741 1
1.0%
126.539581431998 1
1.0%
126.569081803526 1
1.0%
126.602732674793 1
1.0%
126.658309771866 1
1.0%
126.689762679481 1
1.0%
ValueCountFrequency (%)
129.494892048496 1
1.0%
129.460197154001 1
1.0%
129.44918423707 1
1.0%
129.440758589995 1
1.0%
129.310201527834 1
1.0%
129.125129633722 1
1.0%
129.119599947013 1
1.0%
129.064939504659 1
1.0%
129.043266204928 1
1.0%
129.028465547142 1
1.0%

y
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.184479
Minimum33.244374
Maximum38.185571
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:24.751888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.244374
5-th percentile33.434062
Q135.222096
median36.129241
Q337.419424
95-th percentile37.735642
Maximum38.185571
Range4.9411975
Interquartile range (IQR)2.1973287

Descriptive statistics

Standard deviation1.2642363
Coefficient of variation (CV)0.034938634
Kurtosis-0.37466029
Mean36.184479
Median Absolute Deviation (MAD)1.0413594
Skewness-0.52995479
Sum3618.4479
Variance1.5982934
MonotonicityNot monotonic
2023-12-10T18:55:25.580508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.1141918673559 1
 
1.0%
36.0699373895843 1
 
1.0%
34.7774891062438 1
 
1.0%
35.1631226201402 1
 
1.0%
37.6484645636667 1
 
1.0%
35.6666404440778 1
 
1.0%
35.8301018249229 1
 
1.0%
38.0854023744736 1
 
1.0%
36.9703306876506 1
 
1.0%
35.3769150705916 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
33.244373557266 1
1.0%
33.257285164905 1
1.0%
33.2577136688583 1
1.0%
33.3252539089976 1
1.0%
33.3948101621895 1
1.0%
33.4361282073097 1
1.0%
33.5097603953461 1
1.0%
34.5094069030249 1
1.0%
34.5725535106523 1
1.0%
34.714271931443 1
1.0%
ValueCountFrequency (%)
38.1855710668622 1
1.0%
38.0854023744736 1
1.0%
37.9269671672477 1
1.0%
37.8410849774735 1
1.0%
37.7851147661511 1
1.0%
37.7330383191315 1
1.0%
37.6594328396335 1
1.0%
37.6484645636667 1
1.0%
37.6053691966287 1
1.0%
37.604700465022 1
1.0%

grid_cd
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:26.133892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters800
Distinct characters17
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 row마라380809
2nd row다사677562
3rd row마라480858
4th row마마765373
5th row다바986471
ValueCountFrequency (%)
마라380809 1
 
1.0%
다사332496 1
 
1.0%
라라559854 1
 
1.0%
다사372612 1
 
1.0%
마마774429 1
 
1.0%
마마009598 1
 
1.0%
라아955100 1
 
1.0%
라바376858 1
 
1.0%
다마673090 1
 
1.0%
다라446882 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:55:27.008794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 68
 
8.5%
2 67
 
8.4%
4 65
 
8.1%
6 63
 
7.9%
8 61
 
7.6%
3 60
 
7.5%
9 58
 
7.2%
7 57
 
7.1%
56
 
7.0%
0 52
 
6.5%
Other values (7) 193
24.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 68
11.3%
2 67
11.2%
4 65
10.8%
6 63
10.5%
8 61
10.2%
3 60
10.0%
9 58
9.7%
7 57
9.5%
0 52
8.7%
1 49
8.2%
Other Letter
ValueCountFrequency (%)
56
28.0%
44
22.0%
43
21.5%
30
15.0%
17
 
8.5%
8
 
4.0%
2
 
1.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
5 68
11.3%
2 67
11.2%
4 65
10.8%
6 63
10.5%
8 61
10.2%
3 60
10.0%
9 58
9.7%
7 57
9.5%
0 52
8.7%
1 49
8.2%
Hangul
ValueCountFrequency (%)
56
28.0%
44
22.0%
43
21.5%
30
15.0%
17
 
8.5%
8
 
4.0%
2
 
1.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 68
11.3%
2 67
11.2%
4 65
10.8%
6 63
10.5%
8 61
10.2%
3 60
10.0%
9 58
9.7%
7 57
9.5%
0 52
8.7%
1 49
8.2%
Hangul
ValueCountFrequency (%)
56
28.0%
44
22.0%
43
21.5%
30
15.0%
17
 
8.5%
8
 
4.0%
2
 
1.0%

lst_updt_dt
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210917100801
100 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210917100801
2nd row20210917100801
3rd row20210917100801
4th row20210917100801
5th row20210917100801

Common Values

ValueCountFrequency (%)
20210917100801 100
100.0%

Length

2023-12-10T18:55:27.289212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:27.504113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210917100801 100
100.0%

data_orgn
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KT 100
100.0%

Length

2023-12-10T18:55:27.735414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:27.945945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kt 100
100.0%

file_name
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_505_DMSTC_MCST_RSTRT_2021
100 

Length

Max length28
Median length28
Mean length28
Min length28

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_505_DMSTC_MCST_RSTRT_2021
2nd rowKC_505_DMSTC_MCST_RSTRT_2021
3rd rowKC_505_DMSTC_MCST_RSTRT_2021
4th rowKC_505_DMSTC_MCST_RSTRT_2021
5th rowKC_505_DMSTC_MCST_RSTRT_2021

Common Values

ValueCountFrequency (%)
KC_505_DMSTC_MCST_RSTRT_2021 100
100.0%

Length

2023-12-10T18:55:28.163810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:28.353557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_505_dmstc_mcst_rstrt_2021 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210917
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210917
2nd row20210917
3rd row20210917
4th row20210917
5th row20210917

Common Values

ValueCountFrequency (%)
20210917 100
100.0%

Length

2023-12-10T18:55:28.568250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:28.817746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210917 100
100.0%

Sample

idlclasmlsfcid_poipoi_nmbranch_nmsub_nmmcate_cdmcate_nmpnusido_nmsgg_nmbemd_nmri_nmbeonjibadm_cdhadm_cdrd_cdrd_nmbld_numxygrid_cdlst_updt_dtdata_orgnfile_namebase_ymd
0KCRSTPO21N000000001장소식당106901남지횟집<NA><NA>81201생선회2614010600102490012부산광역시서구서대신동3가<NA>249-1226140106002614056000261404178061구덕로345번길20129.01441635.114192마라38080920210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
1KCRSTPO21N000884305장소식당22233852아랑경양회관구리점<NA>81101경양식4131010300105760010경기도구리시인창동<NA>576-1041310103004131053000413103196009응달말로51127.13439237.6047다사67756220210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
2KCRSTPO21N000000003장소식당112539고성횟집<NA><NA>81201생선회2650010300101810043부산광역시수영구민락동<NA>181-4326500103002650080000265004214071광안해변로279번길23129.1251335.156687마라48085820210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
3KCRSTPO21N000000004장소식당113020부산횟집<NA><NA>81201생선회3120011300106830000울산광역시북구정자동<NA>68331200113003120054000312004316280정자7길22-5129.44918435.616458마마76537320210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
4KCRSTPO21N000000005장소식당113344산호횟집<NA><NA>81201생선회4311210300101350011충청북도청주시 서원구모충동<NA>135-1143112103004311254000431123237015남들로45-1127.48462536.621987다바98647120210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
5KCRSTPO21N000000006장소식당135275남영삼겹살매운갈비<NA><NA>81003삼겹살4183025021101760007경기도양평군양평읍양근리176-741830250214183025000418304451770시민로39번길4127.49619837.490717다사99643420210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
6KCRSTPO21N000000007장소식당149027이조면옥<NA><NA>81009냉면4221010800114900261강원도속초시조양동<NA>1490-26142210108004221059000422104469035동해대로3930번길4128.60166438.185571라아96421120210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
7KCRSTPO21N000884306장소식당22233880피제리아지알로<NA><NA>81101경양식3611010300107060000세종특별자치시세종특별자치시보람동<NA>70636110103003611056000361102348105시청대로137127.28677936.479994다바80931320210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
8KCRSTPO21N000000009장소식당219114푸줏간정육식당<NA><NA>81001일반한식4373025036101630003충청북도옥천군옥천읍금구리163-343730250364373025000437303242015삼금로30127.56759336.300855라바06011520210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
9KCRSTPO21N000000010장소식당414923파스타리또<NA><NA>81105파스타전문1171010300104010004서울특별시송파구풍납동<NA>401-411710103001171052000117103123023올림픽로505127.1183237.527265다사66247620210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
idlclasmlsfcid_poipoi_nmbranch_nmsub_nmmcate_cdmcate_nmpnusido_nmsgg_nmbemd_nmri_nmbeonjibadm_cdhadm_cdrd_cdrd_nmbld_numxygrid_cdlst_updt_dtdata_orgnfile_namebase_ymd
90KCRSTPO21N000000091장소식당5904769풍원<NA><NA>81001일반한식1171011200100080004서울특별시송파구오금동<NA>8-411710112001171057000117104169454위례성대로22길8127.13099837.509566다사67345620210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
91KCRSTPO21N000000092장소식당5905019진영식육식당<NA><NA>81001일반한식4824035022100320006경상남도사천시곤양면남문외리32-648240350224824035000482403334030서삼로19-2127.96316535.057062라라42273620210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
92KCRSTPO21N000000093장소식당5906935잣나무집<NA><NA>81001일반한식4150011100101670002경기도이천시사음동<NA>167-241500111004150053000415004421062경충대로2921번길51127.42105237.292046다사93021420210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
93KCRSTPO21N000000094장소식당5908194다사랑치킨피자서학점<NA>80615치킨4511112600101590007전라북도전주시 완산구서서학동<NA>159-745111126004511166000451113266063장승배기로366127.14998335.804013다마68356420210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
94KCRSTPO21N000000095장소식당5908411이대감갈비<NA><NA>81004갈비/불고기1144011000100310090서울특별시마포구노고산동<NA>31-9011440110001144060000114403005016백범로13126.93750637.553472다사50350620210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
95KCRSTPO21N000000096장소식당5908443괴강매운탕<NA><NA>81011찌개/탕전문4311112100101380010충청북도청주시 상당구용담동<NA>138-1043111121004311169000431113236042용담로138127.50528236.63486라바00448520210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
96KCRSTPO21N000000097장소식당5908489또오리<NA><NA>81006닭/오리구이4418010200106660000충청남도보령시죽정동<NA>66644180102004418051500441803252044현대로23126.60273336.360267다바19518420210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
97KCRSTPO21N000000098장소식당5908699보배원<NA><NA>81001일반한식4511112800101990001전라북도전주시 완산구중화산동2가<NA>199-145111128004511167100451113266049어은로26127.12582435.816604다마66157820210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
98KCRSTPO21N000000099장소식당5910258삼미옥<NA><NA>81001일반한식1114012900100140008서울특별시중구남산동2가<NA>14-811140129001114055000111404103328퇴계로20가길6126.98603737.559528다사54651220210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917
99KCRSTPO21N000000100장소식당5910274해조옥<NA><NA>81001일반한식2729010100102190001대구광역시달서구성당동<NA>219-127290101002729051500272904241107대명천로11길67128.55678335.838287라마95460720210917100801KTKC_505_DMSTC_MCST_RSTRT_202120210917