Overview

Dataset statistics

Number of variables27
Number of observations4986
Missing cells43644
Missing cells (%)32.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory226.0 B

Variable types

Categorical6
Numeric5
Text7
DateTime6
Unsupported3

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),지정일자,민원종류명
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-19920/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 4464 (89.5%) missing valuesMissing
폐업일자 has 1556 (31.2%) missing valuesMissing
휴업시작일자 has 4847 (97.2%) missing valuesMissing
휴업종료일자 has 4848 (97.2%) missing valuesMissing
재개업일자 has 4986 (100.0%) missing valuesMissing
전화번호 has 1353 (27.1%) missing valuesMissing
소재지면적 has 4986 (100.0%) missing valuesMissing
소재지우편번호 has 3881 (77.8%) missing valuesMissing
지번주소 has 599 (12.0%) missing valuesMissing
도로명주소 has 744 (14.9%) missing valuesMissing
도로명우편번호 has 3509 (70.4%) missing valuesMissing
업태구분명 has 4986 (100.0%) missing valuesMissing
좌표정보(X) has 407 (8.2%) missing valuesMissing
좌표정보(Y) has 407 (8.2%) missing valuesMissing
지정일자 has 2071 (41.5%) missing valuesMissing
관리번호 has unique valuesUnique
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
상세영업상태코드 has 923 (18.5%) zerosZeros

Reproduction

Analysis started2024-04-06 12:30:26.435335
Analysis finished2024-04-06 12:30:29.034702
Duration2.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
3180000
4986 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 4986
100.0%

Length

2024-04-06T21:30:29.163451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:30:29.342297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 4986
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct4986
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0079582 × 1018
Minimum1.991318 × 1018
Maximum2.024318 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.0 KiB
2024-04-06T21:30:29.542704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.991318 × 1018
5-th percentile2.001318 × 1018
Q12.001318 × 1018
median2.006318 × 1018
Q32.013318 × 1018
95-th percentile2.020318 × 1018
Maximum2.024318 × 1018
Range3.3000009 × 1016
Interquartile range (IQR)1.2000009 × 1016

Descriptive statistics

Standard deviation6.6869359 × 1015
Coefficient of variation (CV)0.0033302167
Kurtosis-0.74693978
Mean2.0079582 × 1018
Median Absolute Deviation (MAD)5 × 1015
Skewness0.67678736
Sum-4.9024249 × 1018
Variance4.4715112 × 1031
MonotonicityStrictly increasing
2024-04-06T21:30:29.820367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1991318016305600000 1
 
< 0.1%
2010318011705600106 1
 
< 0.1%
2010318011705600113 1
 
< 0.1%
2010318011705600112 1
 
< 0.1%
2010318011705600111 1
 
< 0.1%
2010318011705600110 1
 
< 0.1%
2010318011705600109 1
 
< 0.1%
2010318011705600108 1
 
< 0.1%
2010318011705600107 1
 
< 0.1%
2010318011705600105 1
 
< 0.1%
Other values (4976) 4976
99.8%
ValueCountFrequency (%)
1991318016305600000 1
< 0.1%
1991318016305600022 1
< 0.1%
1995318011705609031 1
< 0.1%
1995318016305600002 1
< 0.1%
1998318016305600001 1
< 0.1%
2000318007605600050 1
< 0.1%
2000318007605600727 1
< 0.1%
2000318007605600839 1
< 0.1%
2000318007605609035 1
< 0.1%
2000318011705601184 1
< 0.1%
ValueCountFrequency (%)
2024318025505600017 1
< 0.1%
2024318025505600016 1
< 0.1%
2024318025505600015 1
< 0.1%
2024318025505600014 1
< 0.1%
2024318025505600013 1
< 0.1%
2024318025505600012 1
< 0.1%
2024318025505600011 1
< 0.1%
2024318025505600010 1
< 0.1%
2024318025505600009 1
< 0.1%
2024318025505600008 1
< 0.1%
Distinct2417
Distinct (%)48.5%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
2024-04-06T21:30:30.644629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.2374649
Min length8

Characters and Unicode

Total characters41072
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

Unique1537 ?
Unique (%)30.8%

Sample

1st row19910118
2nd row19910101
3rd row1995-02-15
4th row19950213
5th row19980601
ValueCountFrequency (%)
20000111 938
 
18.8%
2000-01-11 70
 
1.4%
20050217 18
 
0.4%
20030423 16
 
0.3%
20000011 15
 
0.3%
20001111 13
 
0.3%
20040528 11
 
0.2%
20070903 9
 
0.2%
20071102 8
 
0.2%
20070514 8
 
0.2%
Other values (2410) 3883
77.8%
2024-04-06T21:30:31.913737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14964
36.4%
1 8667
21.1%
2 7668
18.7%
9 1629
 
4.0%
3 1341
 
3.3%
7 1233
 
3.0%
- 1184
 
2.9%
8 1115
 
2.7%
6 1099
 
2.7%
4 1095
 
2.7%
Other values (2) 1077
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39878
97.1%
Dash Punctuation 1184
 
2.9%
Space Separator 10
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14964
37.5%
1 8667
21.7%
2 7668
19.2%
9 1629
 
4.1%
3 1341
 
3.4%
7 1233
 
3.1%
8 1115
 
2.8%
6 1099
 
2.8%
4 1095
 
2.7%
5 1067
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 1184
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41072
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14964
36.4%
1 8667
21.1%
2 7668
18.7%
9 1629
 
4.0%
3 1341
 
3.3%
7 1233
 
3.0%
- 1184
 
2.9%
8 1115
 
2.7%
6 1099
 
2.7%
4 1095
 
2.7%
Other values (2) 1077
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41072
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14964
36.4%
1 8667
21.1%
2 7668
18.7%
9 1629
 
4.0%
3 1341
 
3.3%
7 1233
 
3.0%
- 1184
 
2.9%
8 1115
 
2.7%
6 1099
 
2.7%
4 1095
 
2.7%
Other values (2) 1077
 
2.6%

인허가취소일자
Date

MISSING 

Distinct149
Distinct (%)28.5%
Missing4464
Missing (%)89.5%
Memory size39.1 KiB
Minimum2001-10-15 00:00:00
Maximum2024-03-06 00:00:00
2024-04-06T21:30:32.191778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:30:32.482028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
3
3430 
1
923 
4
628 
2
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 3430
68.8%
1 923
 
18.5%
4 628
 
12.6%
2 5
 
0.1%

Length

2024-04-06T21:30:32.783123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:30:32.977276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3430
68.8%
1 923
 
18.5%
4 628
 
12.6%
2 5
 
0.1%

영업상태명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
폐업
3430 
영업/정상
923 
취소/말소/만료/정지/중지
628 
휴업
 
5

Length

Max length14
Median length2
Mean length4.066787
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3430
68.8%
영업/정상 923
 
18.5%
취소/말소/만료/정지/중지 628
 
12.6%
휴업 5
 
0.1%

Length

2024-04-06T21:30:33.223104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:30:33.449132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3430
68.8%
영업/정상 923
 
18.5%
취소/말소/만료/정지/중지 628
 
12.6%
휴업 5
 
0.1%

상세영업상태코드
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9288006
Minimum0
Maximum5
Zeros923
Zeros (%)18.5%
Negative0
Negative (%)0.0%
Memory size44.0 KiB
2024-04-06T21:30:33.742670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q32
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2479652
Coefficient of variation (CV)0.64701616
Kurtosis1.256933
Mean1.9288006
Median Absolute Deviation (MAD)0
Skewness0.63346768
Sum9617
Variance1.5574171
MonotonicityNot monotonic
2024-04-06T21:30:34.119868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 3430
68.8%
0 923
 
18.5%
5 430
 
8.6%
3 190
 
3.8%
4 8
 
0.2%
1 5
 
0.1%
ValueCountFrequency (%)
0 923
 
18.5%
1 5
 
0.1%
2 3430
68.8%
3 190
 
3.8%
4 8
 
0.2%
5 430
 
8.6%
ValueCountFrequency (%)
5 430
 
8.6%
4 8
 
0.2%
3 190
 
3.8%
2 3430
68.8%
1 5
 
0.1%
0 923
 
18.5%
Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
폐업처리
3430 
정상영업
923 
지정취소
430 
직권취소
 
190
임시소매기간만료
 
8

Length

Max length8
Median length4
Mean length4.006418
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 3430
68.8%
정상영업 923
 
18.5%
지정취소 430
 
8.6%
직권취소 190
 
3.8%
임시소매기간만료 8
 
0.2%
휴업처리 5
 
0.1%

Length

2024-04-06T21:30:34.587205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:30:35.000872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 3430
68.8%
정상영업 923
 
18.5%
지정취소 430
 
8.6%
직권취소 190
 
3.8%
임시소매기간만료 8
 
0.2%
휴업처리 5
 
0.1%

폐업일자
Date

MISSING 

Distinct2279
Distinct (%)66.4%
Missing1556
Missing (%)31.2%
Memory size39.1 KiB
Minimum1999-04-14 00:00:00
Maximum2024-04-03 00:00:00
2024-04-06T21:30:35.372038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:30:35.692813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct126
Distinct (%)90.6%
Missing4847
Missing (%)97.2%
Memory size39.1 KiB
Minimum2001-01-22 00:00:00
Maximum2023-07-10 00:00:00
2024-04-06T21:30:35.999117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:30:36.395569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업종료일자
Date

MISSING 

Distinct128
Distinct (%)92.8%
Missing4848
Missing (%)97.2%
Memory size39.1 KiB
Minimum2001-02-22 00:00:00
Maximum2032-10-26 00:00:00
2024-04-06T21:30:36.682542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:30:36.972152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4986
Missing (%)100.0%
Memory size44.0 KiB

전화번호
Text

MISSING 

Distinct2438
Distinct (%)67.1%
Missing1353
Missing (%)27.1%
Memory size39.1 KiB
2024-04-06T21:30:37.578686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length10
Mean length8.9157721
Min length1

Characters and Unicode

Total characters32391
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

Unique2229 ?
Unique (%)61.4%

Sample

1st row2676-8785
2nd row02-784-5349
3rd row02 6703365
4th row02 8155268
5th row2631-9353
ValueCountFrequency (%)
02 1210
25.2%
0211111111 445
 
9.3%
224
 
4.7%
1111111 147
 
3.1%
0226308984 16
 
0.3%
1577-0711 16
 
0.3%
11111111 15
 
0.3%
070-7092-7136 9
 
0.2%
02-6916-1500 6
 
0.1%
000-0000 6
 
0.1%
Other values (2417) 2714
56.4%
2024-04-06T21:30:38.474857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6261
19.3%
2 4669
14.4%
0 4052
12.5%
8 2805
8.7%
6 2449
 
7.6%
3 2410
 
7.4%
7 2254
 
7.0%
4 2028
 
6.3%
5 1458
 
4.5%
- 1351
 
4.2%
Other values (4) 2654
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29678
91.6%
Dash Punctuation 1351
 
4.2%
Space Separator 1178
 
3.6%
Other Punctuation 184
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6261
21.1%
2 4669
15.7%
0 4052
13.7%
8 2805
9.5%
6 2449
 
8.3%
3 2410
 
8.1%
7 2254
 
7.6%
4 2028
 
6.8%
5 1458
 
4.9%
9 1292
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 183
99.5%
, 1
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 1351
100.0%
Space Separator
ValueCountFrequency (%)
1178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32391
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6261
19.3%
2 4669
14.4%
0 4052
12.5%
8 2805
8.7%
6 2449
 
7.6%
3 2410
 
7.4%
7 2254
 
7.0%
4 2028
 
6.3%
5 1458
 
4.5%
- 1351
 
4.2%
Other values (4) 2654
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32391
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6261
19.3%
2 4669
14.4%
0 4052
12.5%
8 2805
8.7%
6 2449
 
7.6%
3 2410
 
7.4%
7 2254
 
7.0%
4 2028
 
6.3%
5 1458
 
4.5%
- 1351
 
4.2%
Other values (4) 2654
8.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4986
Missing (%)100.0%
Memory size44.0 KiB

소재지우편번호
Text

MISSING 

Distinct216
Distinct (%)19.5%
Missing3881
Missing (%)77.8%
Memory size39.1 KiB
2024-04-06T21:30:39.148980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.078733
Min length6

Characters and Unicode

Total characters6717
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

Unique79 ?
Unique (%)7.1%

Sample

1st row150033
2nd row150010
3rd row150-010
4th row150853
5th row150848
ValueCountFrequency (%)
150010 96
 
8.7%
150050 52
 
4.7%
150070 39
 
3.5%
150103 23
 
2.1%
150030 21
 
1.9%
150093 19
 
1.7%
150037 17
 
1.5%
150033 16
 
1.4%
150815 16
 
1.4%
150042 16
 
1.4%
Other values (206) 790
71.5%
2024-04-06T21:30:40.344537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2102
31.3%
1 1410
21.0%
5 1327
19.8%
8 547
 
8.1%
3 329
 
4.9%
4 238
 
3.5%
9 213
 
3.2%
7 179
 
2.7%
2 154
 
2.3%
6 128
 
1.9%
Other values (2) 90
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6627
98.7%
Dash Punctuation 87
 
1.3%
Space Separator 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2102
31.7%
1 1410
21.3%
5 1327
20.0%
8 547
 
8.3%
3 329
 
5.0%
4 238
 
3.6%
9 213
 
3.2%
7 179
 
2.7%
2 154
 
2.3%
6 128
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6717
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2102
31.3%
1 1410
21.0%
5 1327
19.8%
8 547
 
8.1%
3 329
 
4.9%
4 238
 
3.5%
9 213
 
3.2%
7 179
 
2.7%
2 154
 
2.3%
6 128
 
1.9%
Other values (2) 90
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6717
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2102
31.3%
1 1410
21.0%
5 1327
19.8%
8 547
 
8.1%
3 329
 
4.9%
4 238
 
3.5%
9 213
 
3.2%
7 179
 
2.7%
2 154
 
2.3%
6 128
 
1.9%
Other values (2) 90
 
1.3%

지번주소
Text

MISSING 

Distinct3842
Distinct (%)87.6%
Missing599
Missing (%)12.0%
Memory size39.1 KiB
2024-04-06T21:30:41.077104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length47
Mean length27.310235
Min length17

Characters and Unicode

Total characters119810
Distinct characters397
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3439 ?
Unique (%)78.4%

Sample

1st row서울특별시 영등포구 영등포동3가 11번지 21호
2nd row서울특별시 영등포구 여의도동 26번지 4호 교보증권빌딩 지하1층
3rd row서울특별시 영등포구 여의도동 31번지
4th row서울특별시 영등포구 신길1동 448번지 3호
5th row서울특별시 영등포구 신길3동 347번지 265호
ValueCountFrequency (%)
서울특별시 4387
18.6%
영등포구 4387
18.6%
911
 
3.9%
신길동 776
 
3.3%
여의도동 702
 
3.0%
대림동 526
 
2.2%
1호 331
 
1.4%
2호 229
 
1.0%
1층 225
 
1.0%
도림동 168
 
0.7%
Other values (2622) 10958
46.4%
2024-04-06T21:30:42.096593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24088
20.1%
5115
 
4.3%
5091
 
4.2%
5081
 
4.2%
1 4726
 
3.9%
4514
 
3.8%
4444
 
3.7%
4424
 
3.7%
4412
 
3.7%
4401
 
3.7%
Other values (387) 53514
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74282
62.0%
Space Separator 24088
 
20.1%
Decimal Number 20674
 
17.3%
Dash Punctuation 334
 
0.3%
Uppercase Letter 193
 
0.2%
Open Punctuation 73
 
0.1%
Close Punctuation 73
 
0.1%
Other Punctuation 64
 
0.1%
Lowercase Letter 23
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5115
 
6.9%
5091
 
6.9%
5081
 
6.8%
4514
 
6.1%
4444
 
6.0%
4424
 
6.0%
4412
 
5.9%
4401
 
5.9%
4390
 
5.9%
4387
 
5.9%
Other values (332) 28023
37.7%
Uppercase Letter
ValueCountFrequency (%)
B 49
25.4%
S 20
10.4%
A 16
 
8.3%
K 15
 
7.8%
C 12
 
6.2%
G 10
 
5.2%
E 8
 
4.1%
L 7
 
3.6%
I 6
 
3.1%
X 6
 
3.1%
Other values (14) 44
22.8%
Decimal Number
ValueCountFrequency (%)
1 4726
22.9%
2 2659
12.9%
3 2594
12.5%
4 2138
10.3%
6 1661
 
8.0%
5 1636
 
7.9%
0 1535
 
7.4%
7 1337
 
6.5%
8 1227
 
5.9%
9 1161
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
k 5
21.7%
e 5
21.7%
b 3
13.0%
c 3
13.0%
n 2
 
8.7%
a 2
 
8.7%
t 1
 
4.3%
s 1
 
4.3%
r 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 50
78.1%
. 6
 
9.4%
@ 5
 
7.8%
& 1
 
1.6%
/ 1
 
1.6%
? 1
 
1.6%
Space Separator
ValueCountFrequency (%)
24088
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 334
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74282
62.0%
Common 45312
37.8%
Latin 216
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5115
 
6.9%
5091
 
6.9%
5081
 
6.8%
4514
 
6.1%
4444
 
6.0%
4424
 
6.0%
4412
 
5.9%
4401
 
5.9%
4390
 
5.9%
4387
 
5.9%
Other values (332) 28023
37.7%
Latin
ValueCountFrequency (%)
B 49
22.7%
S 20
 
9.3%
A 16
 
7.4%
K 15
 
6.9%
C 12
 
5.6%
G 10
 
4.6%
E 8
 
3.7%
L 7
 
3.2%
I 6
 
2.8%
X 6
 
2.8%
Other values (23) 67
31.0%
Common
ValueCountFrequency (%)
24088
53.2%
1 4726
 
10.4%
2 2659
 
5.9%
3 2594
 
5.7%
4 2138
 
4.7%
6 1661
 
3.7%
5 1636
 
3.6%
0 1535
 
3.4%
7 1337
 
3.0%
8 1227
 
2.7%
Other values (12) 1711
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74282
62.0%
ASCII 45528
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24088
52.9%
1 4726
 
10.4%
2 2659
 
5.8%
3 2594
 
5.7%
4 2138
 
4.7%
6 1661
 
3.6%
5 1636
 
3.6%
0 1535
 
3.4%
7 1337
 
2.9%
8 1227
 
2.7%
Other values (45) 1927
 
4.2%
Hangul
ValueCountFrequency (%)
5115
 
6.9%
5091
 
6.9%
5081
 
6.8%
4514
 
6.1%
4444
 
6.0%
4424
 
6.0%
4412
 
5.9%
4401
 
5.9%
4390
 
5.9%
4387
 
5.9%
Other values (332) 28023
37.7%

도로명주소
Text

MISSING 

Distinct3132
Distinct (%)73.8%
Missing744
Missing (%)14.9%
Memory size39.1 KiB
2024-04-06T21:30:42.720544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length60
Mean length31.408534
Min length20

Characters and Unicode

Total characters133235
Distinct characters402
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2451 ?
Unique (%)57.8%

Sample

1st row서울특별시 영등포구 의사당대로 97 (여의도동,교보증권빌딩 지하1층)
2nd row서울특별시 영등포구 여의나루로 96 (여의도동)
3rd row서울특별시 영등포구 신길로 63 (신길동)
4th row서울특별시 영등포구 가마산로 431 (신길동)
5th row서울특별시 영등포구 영등포로43가길 10 (영등포동5가)
ValueCountFrequency (%)
서울특별시 4242
 
17.7%
영등포구 4236
 
17.7%
신길동 781
 
3.3%
1층 629
 
2.6%
대림동 616
 
2.6%
여의도동 404
 
1.7%
영등포로 155
 
0.6%
도림동 140
 
0.6%
도림로 119
 
0.5%
선유로 117
 
0.5%
Other values (2632) 12465
52.1%
2024-04-06T21:30:43.840965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19668
 
14.8%
5570
 
4.2%
1 5516
 
4.1%
5214
 
3.9%
5202
 
3.9%
4571
 
3.4%
4360
 
3.3%
4321
 
3.2%
( 4281
 
3.2%
) 4281
 
3.2%
Other values (392) 70251
52.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81645
61.3%
Decimal Number 19929
 
15.0%
Space Separator 19668
 
14.8%
Open Punctuation 4281
 
3.2%
Close Punctuation 4281
 
3.2%
Other Punctuation 2416
 
1.8%
Dash Punctuation 742
 
0.6%
Uppercase Letter 242
 
0.2%
Lowercase Letter 21
 
< 0.1%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5570
 
6.8%
5214
 
6.4%
5202
 
6.4%
4571
 
5.6%
4360
 
5.3%
4321
 
5.3%
4276
 
5.2%
4264
 
5.2%
4257
 
5.2%
4245
 
5.2%
Other values (338) 35365
43.3%
Uppercase Letter
ValueCountFrequency (%)
B 78
32.2%
A 25
 
10.3%
S 21
 
8.7%
K 18
 
7.4%
C 14
 
5.8%
G 13
 
5.4%
L 9
 
3.7%
T 9
 
3.7%
V 7
 
2.9%
M 6
 
2.5%
Other values (14) 42
17.4%
Decimal Number
ValueCountFrequency (%)
1 5516
27.7%
2 2624
13.2%
3 2308
11.6%
4 1769
 
8.9%
0 1691
 
8.5%
6 1491
 
7.5%
5 1393
 
7.0%
7 1264
 
6.3%
8 1031
 
5.2%
9 842
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
e 6
28.6%
k 4
19.0%
a 2
 
9.5%
c 2
 
9.5%
b 2
 
9.5%
n 2
 
9.5%
s 1
 
4.8%
t 1
 
4.8%
r 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 2403
99.5%
. 6
 
0.2%
@ 3
 
0.1%
? 2
 
0.1%
& 1
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
19668
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4281
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4281
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 742
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81645
61.3%
Common 51327
38.5%
Latin 263
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5570
 
6.8%
5214
 
6.4%
5202
 
6.4%
4571
 
5.6%
4360
 
5.3%
4321
 
5.3%
4276
 
5.2%
4264
 
5.2%
4257
 
5.2%
4245
 
5.2%
Other values (338) 35365
43.3%
Latin
ValueCountFrequency (%)
B 78
29.7%
A 25
 
9.5%
S 21
 
8.0%
K 18
 
6.8%
C 14
 
5.3%
G 13
 
4.9%
L 9
 
3.4%
T 9
 
3.4%
V 7
 
2.7%
e 6
 
2.3%
Other values (23) 63
24.0%
Common
ValueCountFrequency (%)
19668
38.3%
1 5516
 
10.7%
( 4281
 
8.3%
) 4281
 
8.3%
2 2624
 
5.1%
, 2403
 
4.7%
3 2308
 
4.5%
4 1769
 
3.4%
0 1691
 
3.3%
6 1491
 
2.9%
Other values (11) 5295
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81645
61.3%
ASCII 51590
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19668
38.1%
1 5516
 
10.7%
( 4281
 
8.3%
) 4281
 
8.3%
2 2624
 
5.1%
, 2403
 
4.7%
3 2308
 
4.5%
4 1769
 
3.4%
0 1691
 
3.3%
6 1491
 
2.9%
Other values (44) 5558
 
10.8%
Hangul
ValueCountFrequency (%)
5570
 
6.8%
5214
 
6.4%
5202
 
6.4%
4571
 
5.6%
4360
 
5.3%
4321
 
5.3%
4276
 
5.2%
4264
 
5.2%
4257
 
5.2%
4245
 
5.2%
Other values (338) 35365
43.3%

도로명우편번호
Text

MISSING 

Distinct404
Distinct (%)27.4%
Missing3509
Missing (%)70.4%
Memory size39.1 KiB
2024-04-06T21:30:45.030493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.3622207
Min length5

Characters and Unicode

Total characters7920
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

Unique124 ?
Unique (%)8.4%

Sample

1st row07328
2nd row07269
3rd row07204
4th row07291
5th row07307
ValueCountFrequency (%)
07236 21
 
1.4%
150841 20
 
1.4%
07306 16
 
1.1%
07333 16
 
1.1%
150804 15
 
1.0%
07319 13
 
0.9%
07247 13
 
0.9%
07275 11
 
0.7%
150033 11
 
0.7%
07301 11
 
0.7%
Other values (394) 1330
90.0%
2024-04-06T21:30:46.243423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1994
25.2%
7 1229
15.5%
1 831
10.5%
5 804
10.2%
2 761
 
9.6%
3 734
 
9.3%
4 502
 
6.3%
8 485
 
6.1%
9 288
 
3.6%
6 251
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7879
99.5%
Dash Punctuation 41
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1994
25.3%
7 1229
15.6%
1 831
10.5%
5 804
10.2%
2 761
 
9.7%
3 734
 
9.3%
4 502
 
6.4%
8 485
 
6.2%
9 288
 
3.7%
6 251
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1994
25.2%
7 1229
15.5%
1 831
10.5%
5 804
10.2%
2 761
 
9.6%
3 734
 
9.3%
4 502
 
6.3%
8 485
 
6.1%
9 288
 
3.6%
6 251
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1994
25.2%
7 1229
15.5%
1 831
10.5%
5 804
10.2%
2 761
 
9.6%
3 734
 
9.3%
4 502
 
6.3%
8 485
 
6.1%
9 288
 
3.6%
6 251
 
3.2%
Distinct3891
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
2024-04-06T21:30:46.963957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length6.5633775
Min length1

Characters and Unicode

Total characters32725
Distinct characters658
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3351 ?
Unique (%)67.2%

Sample

1st row24시 금강편의점
2nd row새로나
3rd row문화방송새마을금고
4th row종점식품
5th row승리슈퍼
ValueCountFrequency (%)
gs25 184
 
3.0%
씨유 143
 
2.3%
세븐일레븐 79
 
1.3%
주)코리아세븐 63
 
1.0%
55
 
0.9%
이마트24 50
 
0.8%
지에스25 46
 
0.8%
가로판매점 45
 
0.7%
cu 44
 
0.7%
지에스(gs)25 29
 
0.5%
Other values (3862) 5354
87.9%
2024-04-06T21:30:47.840443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1465
 
4.5%
1106
 
3.4%
2 657
 
2.0%
642
 
2.0%
624
 
1.9%
597
 
1.8%
563
 
1.7%
5 553
 
1.7%
518
 
1.6%
513
 
1.6%
Other values (648) 25487
77.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27733
84.7%
Decimal Number 1525
 
4.7%
Uppercase Letter 1324
 
4.0%
Space Separator 1106
 
3.4%
Close Punctuation 457
 
1.4%
Open Punctuation 456
 
1.4%
Lowercase Letter 86
 
0.3%
Other Punctuation 19
 
0.1%
Dash Punctuation 15
 
< 0.1%
Other Symbol 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1465
 
5.3%
642
 
2.3%
624
 
2.3%
597
 
2.2%
563
 
2.0%
518
 
1.9%
513
 
1.8%
500
 
1.8%
465
 
1.7%
441
 
1.6%
Other values (581) 21405
77.2%
Uppercase Letter
ValueCountFrequency (%)
S 491
37.1%
G 438
33.1%
C 92
 
6.9%
U 63
 
4.8%
K 44
 
3.3%
L 27
 
2.0%
I 21
 
1.6%
B 16
 
1.2%
F 14
 
1.1%
O 13
 
1.0%
Other values (15) 105
 
7.9%
Lowercase Letter
ValueCountFrequency (%)
s 15
17.4%
e 8
9.3%
a 8
9.3%
t 8
9.3%
o 7
8.1%
k 7
8.1%
y 6
 
7.0%
l 5
 
5.8%
n 4
 
4.7%
g 3
 
3.5%
Other values (11) 15
17.4%
Decimal Number
ValueCountFrequency (%)
2 657
43.1%
5 553
36.3%
4 106
 
7.0%
1 64
 
4.2%
3 48
 
3.1%
6 28
 
1.8%
9 27
 
1.8%
8 17
 
1.1%
7 15
 
1.0%
0 10
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 10
52.6%
. 6
31.6%
& 2
 
10.5%
/ 1
 
5.3%
Space Separator
ValueCountFrequency (%)
1106
100.0%
Close Punctuation
ValueCountFrequency (%)
) 457
100.0%
Open Punctuation
ValueCountFrequency (%)
( 456
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27735
84.8%
Common 3580
 
10.9%
Latin 1410
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1465
 
5.3%
642
 
2.3%
624
 
2.2%
597
 
2.2%
563
 
2.0%
518
 
1.9%
513
 
1.8%
500
 
1.8%
465
 
1.7%
441
 
1.6%
Other values (582) 21407
77.2%
Latin
ValueCountFrequency (%)
S 491
34.8%
G 438
31.1%
C 92
 
6.5%
U 63
 
4.5%
K 44
 
3.1%
L 27
 
1.9%
I 21
 
1.5%
B 16
 
1.1%
s 15
 
1.1%
F 14
 
1.0%
Other values (36) 189
 
13.4%
Common
ValueCountFrequency (%)
1106
30.9%
2 657
18.4%
5 553
15.4%
) 457
12.8%
( 456
12.7%
4 106
 
3.0%
1 64
 
1.8%
3 48
 
1.3%
6 28
 
0.8%
9 27
 
0.8%
Other values (10) 78
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27733
84.7%
ASCII 4990
 
15.2%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1465
 
5.3%
642
 
2.3%
624
 
2.3%
597
 
2.2%
563
 
2.0%
518
 
1.9%
513
 
1.8%
500
 
1.8%
465
 
1.7%
441
 
1.6%
Other values (581) 21405
77.2%
ASCII
ValueCountFrequency (%)
1106
22.2%
2 657
13.2%
5 553
11.1%
S 491
9.8%
) 457
9.2%
( 456
9.1%
G 438
 
8.8%
4 106
 
2.1%
C 92
 
1.8%
1 64
 
1.3%
Other values (56) 570
11.4%
None
ValueCountFrequency (%)
2
100.0%
Distinct3658
Distinct (%)73.4%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
Minimum2007-07-12 14:47:03
Maximum2024-04-03 17:56:48
2024-04-06T21:30:48.118241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:30:48.447030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
I
3882 
U
1104 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowI
3rd rowU
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 3882
77.9%
U 1104
 
22.1%

Length

2024-04-06T21:30:48.689854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:30:48.871524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3882
77.9%
u 1104
 
22.1%
Distinct700
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-04-06T21:30:49.059558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:30:49.331949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4986
Missing (%)100.0%
Memory size44.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2063
Distinct (%)45.1%
Missing407
Missing (%)8.2%
Infinite0
Infinite (%)0.0%
Mean191693.34
Minimum189549.85
Maximum194892.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.0 KiB
2024-04-06T21:30:49.746108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189549.85
5-th percentile190121.88
Q1190873.95
median191536.04
Q3192445.38
95-th percentile193726.74
Maximum194892.13
Range5342.2871
Interquartile range (IQR)1571.4285

Descriptive statistics

Standard deviation1086.3847
Coefficient of variation (CV)0.0056673053
Kurtosis-0.31374069
Mean191693.34
Median Absolute Deviation (MAD)712.67166
Skewness0.50739956
Sum8.7776379 × 108
Variance1180231.6
MonotonicityNot monotonic
2024-04-06T21:30:50.042799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194632.526367463 31
 
0.6%
191741.345847708 31
 
0.6%
193078.153751051 17
 
0.3%
190555.768991595 13
 
0.3%
192747.419300064 13
 
0.3%
190394.571819262 13
 
0.3%
191854.942252901 12
 
0.2%
194294.277022719 11
 
0.2%
193674.743726431 11
 
0.2%
191205.317101406 11
 
0.2%
Other values (2053) 4416
88.6%
(Missing) 407
 
8.2%
ValueCountFrequency (%)
189549.847307536 4
0.1%
189570.401236233 4
0.1%
189574.962072527 8
0.2%
189586.236800721 3
 
0.1%
189602.337205545 1
 
< 0.1%
189614.372793612 1
 
< 0.1%
189639.780967523 1
 
< 0.1%
189641.475801911 1
 
< 0.1%
189645.257372816 2
 
< 0.1%
189653.829218246 3
 
0.1%
ValueCountFrequency (%)
194892.134419761 1
 
< 0.1%
194859.098093218 1
 
< 0.1%
194632.526367463 31
0.6%
194599.854707059 3
 
0.1%
194592.276750438 7
 
0.1%
194561.746032498 1
 
< 0.1%
194530.535390096 3
 
0.1%
194504.656267957 5
 
0.1%
194475.664839714 1
 
< 0.1%
194370.32715363 10
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2063
Distinct (%)45.1%
Missing407
Missing (%)8.2%
Infinite0
Infinite (%)0.0%
Mean445895.68
Minimum442605.7
Maximum449199.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.0 KiB
2024-04-06T21:30:50.374628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442605.7
5-th percentile443321.85
Q1444816.99
median446176.69
Q3446927.96
95-th percentile448064.2
Maximum449199.04
Range6593.334
Interquartile range (IQR)2110.9667

Descriptive statistics

Standard deviation1434.2825
Coefficient of variation (CV)0.0032166325
Kurtosis-0.69897444
Mean445895.68
Median Absolute Deviation (MAD)983.86179
Skewness-0.31080215
Sum2.0417563 × 109
Variance2057166.4
MonotonicityNot monotonic
2024-04-06T21:30:50.669947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446401.926526228 31
 
0.6%
445970.307641467 31
 
0.6%
447096.138540329 17
 
0.3%
446698.814322782 13
 
0.3%
447054.988337321 13
 
0.3%
448656.726986041 13
 
0.3%
445656.346287669 12
 
0.2%
447429.005416948 11
 
0.2%
447296.226305826 11
 
0.2%
448034.65486381 11
 
0.2%
Other values (2053) 4416
88.6%
(Missing) 407
 
8.2%
ValueCountFrequency (%)
442605.70463744 1
 
< 0.1%
442621.787911877 8
0.2%
442663.748373343 1
 
< 0.1%
442700.796497298 1
 
< 0.1%
442710.662421803 6
0.1%
442715.677609564 1
 
< 0.1%
442717.639571997 2
 
< 0.1%
442744.165176674 3
 
0.1%
442751.471769958 2
 
< 0.1%
442756.531513655 3
 
0.1%
ValueCountFrequency (%)
449199.038668984 2
 
< 0.1%
449133.481757616 2
 
< 0.1%
449107.834531278 1
 
< 0.1%
449105.000294519 2
 
< 0.1%
449045.705457074 2
 
< 0.1%
449033.097215692 6
0.1%
449021.440559054 2
 
< 0.1%
449011.743315832 1
 
< 0.1%
448990.816559516 2
 
< 0.1%
448990.217887945 1
 
< 0.1%

지정일자
Real number (ℝ)

MISSING 

Distinct1586
Distinct (%)54.4%
Missing2071
Missing (%)41.5%
Infinite0
Infinite (%)0.0%
Mean20086719
Minimum19890311
Maximum20220325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.0 KiB
2024-04-06T21:30:51.028747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19890311
5-th percentile20000111
Q120040620
median20081218
Q320131109
95-th percentile20190652
Maximum20220325
Range330014
Interquartile range (IQR)90489.5

Descriptive statistics

Standard deviation61850.225
Coefficient of variation (CV)0.0030791601
Kurtosis-0.80686632
Mean20086719
Median Absolute Deviation (MAD)49512
Skewness0.031127935
Sum5.8552787 × 1010
Variance3.8254503 × 109
MonotonicityNot monotonic
2024-04-06T21:30:51.334807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000111 355
 
7.1%
20050217 18
 
0.4%
20070903 9
 
0.2%
20070514 8
 
0.2%
20071010 8
 
0.2%
20071102 8
 
0.2%
20070309 7
 
0.1%
20070706 7
 
0.1%
20080805 7
 
0.1%
20001111 6
 
0.1%
Other values (1576) 2482
49.8%
(Missing) 2071
41.5%
ValueCountFrequency (%)
19890311 1
< 0.1%
19891201 1
< 0.1%
19900110 1
< 0.1%
19910101 1
< 0.1%
19910118 1
< 0.1%
19910212 1
< 0.1%
19950213 1
< 0.1%
19960126 1
< 0.1%
19960304 1
< 0.1%
19960308 1
< 0.1%
ValueCountFrequency (%)
20220325 1
< 0.1%
20220322 1
< 0.1%
20220125 1
< 0.1%
20220117 1
< 0.1%
20220107 2
< 0.1%
20211228 1
< 0.1%
20211210 1
< 0.1%
20211124 1
< 0.1%
20211020 2
< 0.1%
20211015 1
< 0.1%

민원종류명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
<NA>
2071 
2009년11월법개정전자료
1597 
제7조의3제2항에따른경우
1183 
제7조의3제3항에따른경우
 
135

Length

Max length14
Median length13
Mean length9.5820297
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2009년11월법개정전자료
2nd row2009년11월법개정전자료
3rd row<NA>
4th row2009년11월법개정전자료
5th row2009년11월법개정전자료

Common Values

ValueCountFrequency (%)
<NA> 2071
41.5%
2009년11월법개정전자료 1597
32.0%
제7조의3제2항에따른경우 1183
23.7%
제7조의3제3항에따른경우 135
 
2.7%

Length

2024-04-06T21:30:51.637580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:30:51.846155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2071
41.5%
2009년11월법개정전자료 1597
32.0%
제7조의3제2항에따른경우 1183
23.7%
제7조의3제3항에따른경우 135
 
2.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자민원종류명
03180000199131801630560000019910118<NA>3폐업2폐업처리20120619<NA><NA><NA>2676-8785<NA>150033서울특별시 영등포구 영등포동3가 11번지 21호<NA><NA>24시 금강편의점2012-06-19 16:12:13I2018-08-31 23:59:59.0<NA>191910.921333446159.317667199101182009년11월법개정전자료
13180000199131801630560002219910101<NA>3폐업2폐업처리20110623<NA><NA><NA>02-784-5349<NA>150010서울특별시 영등포구 여의도동 26번지 4호 교보증권빌딩 지하1층서울특별시 영등포구 의사당대로 97 (여의도동,교보증권빌딩 지하1층)<NA>새로나2011-06-23 17:19:09I2018-08-31 23:59:59.0<NA>193253.666518446701.353544199101012009년11월법개정전자료
2318000019953180117056090311995-02-15<NA>3폐업2폐업처리2023-12-06<NA><NA><NA><NA><NA>150-010서울특별시 영등포구 여의도동 31번지서울특별시 영등포구 여의나루로 96 (여의도동)<NA>문화방송새마을금고2023-12-06 17:05:55U2022-11-02 00:08:00.0<NA>193726.322806446876.150473<NA><NA>
33180000199531801630560000219950213<NA>3폐업2폐업처리20110502<NA><NA><NA><NA><NA>150853서울특별시 영등포구 신길1동 448번지 3호서울특별시 영등포구 신길로 63 (신길동)<NA>종점식품2011-05-02 14:57:25I2018-08-31 23:59:59.0<NA>191796.973563444009.952051199502132009년11월법개정전자료
43180000199831801630560000119980601<NA>3폐업2폐업처리20121204<NA><NA><NA><NA><NA>150848서울특별시 영등포구 신길3동 347번지 265호서울특별시 영등포구 가마산로 431 (신길동)<NA>승리슈퍼2012-12-04 17:03:58I2018-08-31 23:59:59.0<NA>191489.923212444755.62924199806012009년11월법개정전자료
53180000200031800760560005019891201<NA>3폐업2폐업처리20001229<NA><NA><NA>02 6703365<NA><NA>서울특별시 영등포구 영등포동5가 34번지 21호서울특별시 영등포구 영등포로43가길 10 (영등포동5가)<NA>부산식품2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>191806.367017446492.050559<NA><NA>
63180000200031800760560072719891201<NA>1영업/정상0정상영업<NA>2021063020211028<NA>02 8155268<NA><NA>서울특별시 영등포구 여의도동 3 가로판매대14서울특별시 영등포구 여의나루로 42-2, 가로판매대14 (여의도동)07328하나복권(하나텔레콤)2021-11-15 20:00:34U2021-11-17 02:40:00.0<NA>193471.519358446781.847319198912012009년11월법개정전자료
7318000020003180076056008392000-01-11<NA>3폐업2폐업처리2024-01-19<NA><NA><NA>2631-9353<NA>150-042서울특별시 영등포구 당산동2가 164번지 현대상가 116서울특별시 영등포구 당산로 95 (당산동2가,현대상가 116)<NA>슈퍼복권방2024-01-19 17:45:29U2023-11-30 22:01:00.0<NA>190637.878211446813.206451<NA><NA>
83180000200031800760560903520000111<NA>3폐업2폐업처리20001227<NA><NA><NA>02 7802989<NA><NA>서울특별시 영등포구 여의도동 17번지 20호 원정빌딩1층서울특별시 영등포구 국회대로62길 23 (여의도동,원정빌딩1층)<NA>반석가든2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>192636.733285447145.450292<NA><NA>
93180000200031801170560118420000111<NA>3폐업2폐업처리20120412<NA><NA><NA>8440770<NA><NA>서울특별시 영등포구 신길동 209번지 120호서울특별시 영등포구 신길로42길 13 (신길동)<NA>나약국2012-04-12 17:43:53I2018-08-31 23:59:59.0<NA>192172.91382445074.031634200001112009년11월법개정전자료
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자민원종류명
4976318000020243180255056000082024-02-02<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 대림동 710서울특별시 영등포구 도림로41길 6, 1층 (대림동)07413지에스(GS)25 대림으뜸점2024-02-05 09:17:22I2023-12-02 00:07:00.0<NA>190938.080289443591.339482<NA><NA>
4977318000020243180255056000092024-02-08<NA>1영업/정상0정상영업<NA><NA><NA><NA>02-3434-8017<NA><NA>서울특별시 영등포구 여의도동 16-1 한국수출입은행빌딩서울특별시 영등포구 은행로 38, 한국수출입은행빌딩 8층 (여의도동)07242(주)후니드 한국수출입은행마트2024-02-08 10:10:34I2023-12-01 23:01:00.0<NA>193159.124448447376.605815<NA><NA>
4978318000020243180255056000102024-02-08<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 45-3 엔에이치농협캐피탈빌딩서울특별시 영등포구 국제금융로8길 27-8, 엔에이치농협캐피탈빌딩 1층 (여의도동)07332GS25 여의캐피탈점2024-02-08 10:11:34I2023-12-01 23:01:00.0<NA>193598.53644446357.770653<NA><NA>
4979318000020243180255056000112024-02-22<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동6가 127-8서울특별시 영등포구 영등포로33길 15, 1층 (영등포동6가)07251세븐일레븐 영신로점2024-02-27 11:03:28U2023-12-01 22:09:00.0<NA>191324.0145446624.390643<NA><NA>
4980318000020243180255056000122024-03-12<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 5-6 샛강역서울특별시 영등포구 의사당대로 지하166, 샛강역 (여의도동)07324GS25 S9샛강역점2024-03-12 11:01:16I2023-12-02 23:04:00.0<NA>193753.311604446103.601051<NA><NA>
4981318000020243180255056000132024-03-19<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동6가 145서울특별시 영등포구 영신로 166, 124,125,126호 (영등포동6가)07251CU 영등포아이비밸리점2024-03-19 08:47:33I2023-12-02 22:01:00.0<NA>191287.220817446748.752489<NA><NA>
4982318000020243180255056000142024-03-19<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 문래동6가 24-1 에이스하이테크시티2서울특별시 영등포구 선유로13길 25, 에이스하이테크시티2 101,102호 (문래동6가)07282이마트24 문래에이스점2024-03-19 17:23:25I2023-12-02 22:01:00.0<NA>189849.410292446314.681886<NA><NA>
4983318000020243180255056000152024-03-19<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 525 브라이튼 여의도서울특별시 영등포구 국제금융로 39, 지상3층 307호 (여의도동, 브라이튼 여의도)07339GS25 브라이튼여의도2호2024-03-19 17:24:05I2023-12-02 22:01:00.0<NA><NA><NA><NA><NA>
4984318000020243180255056000162024-03-26<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 문래동2가 57-4서울특별시 영등포구 도림로139길 12-1, 1층 (문래동2가)07290상승플러스2024-03-28 10:11:43U2023-12-02 21:00:00.0<NA>190438.656287445751.213217<NA><NA>
4985318000020243180255056000172024-03-29<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 신길동 448-15서울특별시 영등포구 신길로 61, 1층 (신길동)07424GS25신길본점2024-04-01 16:51:18I2023-12-04 00:03:00.0<NA>191791.111085443998.478784<NA><NA>