Overview

Dataset statistics

Number of variables27
Number of observations3972
Missing cells34110
Missing cells (%)31.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory872.9 KiB
Average record size in memory225.0 B

Variable types

Categorical6
Text8
DateTime6
Numeric4
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
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-19923/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
상세영업상태명 is highly imbalanced (52.4%)Imbalance
인허가취소일자 has 3653 (92.0%) missing valuesMissing
폐업일자 has 1118 (28.1%) missing valuesMissing
휴업시작일자 has 3891 (98.0%) missing valuesMissing
휴업종료일자 has 3891 (98.0%) missing valuesMissing
재개업일자 has 3972 (100.0%) missing valuesMissing
전화번호 has 1588 (40.0%) missing valuesMissing
소재지면적 has 3972 (100.0%) missing valuesMissing
소재지우편번호 has 2916 (73.4%) missing valuesMissing
지번주소 has 49 (1.2%) missing valuesMissing
도로명주소 has 353 (8.9%) missing valuesMissing
도로명우편번호 has 2795 (70.4%) missing valuesMissing
업태구분명 has 3972 (100.0%) missing valuesMissing
좌표정보(X) has 202 (5.1%) missing valuesMissing
좌표정보(Y) has 202 (5.1%) missing valuesMissing
지정일자 has 1536 (38.7%) 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 753 (19.0%) zerosZeros

Reproduction

Analysis started2024-05-11 08:32:51.047327
Analysis finished2024-05-11 08:32:54.428074
Duration3.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
3210000
3972 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 3972
100.0%

Length

2024-05-11T08:32:54.624351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:32:54.954788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 3972
100.0%

관리번호
Text

UNIQUE 

Distinct3972
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
2024-05-11T08:32:55.681219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length18.946626
Min length17

Characters and Unicode

Total characters75256
Distinct characters22
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3972 ?
Unique (%)100.0%

Sample

1st row1968321007605600001
2nd row1973321007605600002
3rd row1974321007605600001
4th row197632100760560내15
5th row19773210076056방120
ValueCountFrequency (%)
1968321007605600001 1
 
< 0.1%
2010321012205600034 1
 
< 0.1%
2010321012205600049 1
 
< 0.1%
2010321012205600022 1
 
< 0.1%
2010321012205600023 1
 
< 0.1%
2010321012205600024 1
 
< 0.1%
2010321012205600025 1
 
< 0.1%
2010321012205600026 1
 
< 0.1%
2010321012205600027 1
 
< 0.1%
2010321012205600028 1
 
< 0.1%
Other values (3962) 3962
99.7%
2024-05-11T08:32:56.934748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26608
35.4%
2 11178
14.9%
1 10279
 
13.7%
6 7072
 
9.4%
5 6029
 
8.0%
3 5304
 
7.0%
7 3006
 
4.0%
9 2473
 
3.3%
8 1574
 
2.1%
4 1455
 
1.9%
Other values (12) 278
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74978
99.6%
Other Letter 212
 
0.3%
Dash Punctuation 64
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26608
35.5%
2 11178
14.9%
1 10279
 
13.7%
6 7072
 
9.4%
5 6029
 
8.0%
3 5304
 
7.1%
7 3006
 
4.0%
9 2473
 
3.3%
8 1574
 
2.1%
4 1455
 
1.9%
Other Letter
ValueCountFrequency (%)
52
24.5%
47
22.2%
39
18.4%
32
15.1%
17
 
8.0%
11
 
5.2%
9
 
4.2%
4
 
1.9%
1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
j 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75042
99.7%
Hangul 212
 
0.3%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26608
35.5%
2 11178
14.9%
1 10279
 
13.7%
6 7072
 
9.4%
5 6029
 
8.0%
3 5304
 
7.1%
7 3006
 
4.0%
9 2473
 
3.3%
8 1574
 
2.1%
4 1455
 
1.9%
Hangul
ValueCountFrequency (%)
52
24.5%
47
22.2%
39
18.4%
32
15.1%
17
 
8.0%
11
 
5.2%
9
 
4.2%
4
 
1.9%
1
 
0.5%
Latin
ValueCountFrequency (%)
t 1
50.0%
j 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75044
99.7%
Hangul 212
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26608
35.5%
2 11178
14.9%
1 10279
 
13.7%
6 7072
 
9.4%
5 6029
 
8.0%
3 5304
 
7.1%
7 3006
 
4.0%
9 2473
 
3.3%
8 1574
 
2.1%
4 1455
 
1.9%
Other values (3) 66
 
0.1%
Hangul
ValueCountFrequency (%)
52
24.5%
47
22.2%
39
18.4%
32
15.1%
17
 
8.0%
11
 
5.2%
9
 
4.2%
4
 
1.9%
1
 
0.5%
Distinct2552
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
2024-05-11T08:32:57.882390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.1243706
Min length8

Characters and Unicode

Total characters32270
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

Unique1715 ?
Unique (%)43.2%

Sample

1st row19981102
2nd row19981111
3rd row19990911
4th row19760416
5th row19770901
ValueCountFrequency (%)
19981111 22
 
0.5%
19981026 14
 
0.3%
19990525 14
 
0.3%
19981023 12
 
0.3%
20000121 12
 
0.3%
19981116 10
 
0.2%
20031117 8
 
0.2%
20020610 8
 
0.2%
20010212 8
 
0.2%
19981031 7
 
0.2%
Other values (2558) 3886
97.1%
2024-05-11T08:32:59.287356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10494
32.5%
2 6254
19.4%
1 5789
17.9%
9 2318
 
7.2%
3 1404
 
4.4%
8 1192
 
3.7%
4 1101
 
3.4%
6 1097
 
3.4%
5 1041
 
3.2%
7 1034
 
3.2%
Other values (2) 546
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31724
98.3%
Dash Punctuation 494
 
1.5%
Space Separator 52
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10494
33.1%
2 6254
19.7%
1 5789
18.2%
9 2318
 
7.3%
3 1404
 
4.4%
8 1192
 
3.8%
4 1101
 
3.5%
6 1097
 
3.5%
5 1041
 
3.3%
7 1034
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 494
100.0%
Space Separator
ValueCountFrequency (%)
52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32270
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10494
32.5%
2 6254
19.4%
1 5789
17.9%
9 2318
 
7.2%
3 1404
 
4.4%
8 1192
 
3.7%
4 1101
 
3.4%
6 1097
 
3.4%
5 1041
 
3.2%
7 1034
 
3.2%
Other values (2) 546
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32270
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10494
32.5%
2 6254
19.4%
1 5789
17.9%
9 2318
 
7.2%
3 1404
 
4.4%
8 1192
 
3.7%
4 1101
 
3.4%
6 1097
 
3.4%
5 1041
 
3.2%
7 1034
 
3.2%
Other values (2) 546
 
1.7%

인허가취소일자
Date

MISSING 

Distinct142
Distinct (%)44.5%
Missing3653
Missing (%)92.0%
Memory size31.2 KiB
Minimum2001-05-23 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T08:32:59.948784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:33:00.553146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
3
2854 
1
753 
4
354 
2
 
11

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 2854
71.9%
1 753
 
19.0%
4 354
 
8.9%
2 11
 
0.3%

Length

2024-05-11T08:33:01.168048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:01.596460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2854
71.9%
1 753
 
19.0%
4 354
 
8.9%
2 11
 
0.3%

영업상태명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
폐업
2854 
영업/정상
753 
취소/말소/만료/정지/중지
354 
휴업
 
11

Length

Max length14
Median length2
Mean length3.6382175
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row영업/정상
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 2854
71.9%
영업/정상 753
 
19.0%
취소/말소/만료/정지/중지 354
 
8.9%
휴업 11
 
0.3%

Length

2024-05-11T08:33:02.036191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:02.535251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2854
71.9%
영업/정상 753
 
19.0%
취소/말소/만료/정지/중지 354
 
8.9%
휴업 11
 
0.3%

상세영업상태코드
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7985901
Minimum0
Maximum5
Zeros753
Zeros (%)19.0%
Negative0
Negative (%)0.0%
Memory size35.0 KiB
2024-05-11T08:33:03.089697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q32
95-th percentile3
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0833871
Coefficient of variation (CV)0.60235351
Kurtosis1.9595637
Mean1.7985901
Median Absolute Deviation (MAD)0
Skewness0.36550323
Sum7144
Variance1.1737276
MonotonicityNot monotonic
2024-05-11T08:33:03.583191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 2854
71.9%
0 753
 
19.0%
5 178
 
4.5%
3 169
 
4.3%
1 11
 
0.3%
4 7
 
0.2%
ValueCountFrequency (%)
0 753
 
19.0%
1 11
 
0.3%
2 2854
71.9%
3 169
 
4.3%
4 7
 
0.2%
5 178
 
4.5%
ValueCountFrequency (%)
5 178
 
4.5%
4 7
 
0.2%
3 169
 
4.3%
2 2854
71.9%
1 11
 
0.3%
0 753
 
19.0%

상세영업상태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
폐업처리
2854 
정상영업
753 
지정취소
 
178
직권취소
 
169
휴업처리
 
11

Length

Max length8
Median length4
Mean length4.0070493
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 2854
71.9%
정상영업 753
 
19.0%
지정취소 178
 
4.5%
직권취소 169
 
4.3%
휴업처리 11
 
0.3%
임시소매기간만료 7
 
0.2%

Length

2024-05-11T08:33:04.397740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:04.865071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 2854
71.9%
정상영업 753
 
19.0%
지정취소 178
 
4.5%
직권취소 169
 
4.3%
휴업처리 11
 
0.3%
임시소매기간만료 7
 
0.2%

폐업일자
Date

MISSING 

Distinct2112
Distinct (%)74.0%
Missing1118
Missing (%)28.1%
Memory size31.2 KiB
Minimum2001-04-03 00:00:00
Maximum2024-05-03 00:00:00
2024-05-11T08:33:05.445726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:33:05.987364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct78
Distinct (%)96.3%
Missing3891
Missing (%)98.0%
Memory size31.2 KiB
Minimum2000-12-25 00:00:00
Maximum2024-01-04 00:00:00
2024-05-11T08:33:06.637128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:33:07.308676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업종료일자
Date

MISSING 

Distinct79
Distinct (%)97.5%
Missing3891
Missing (%)98.0%
Memory size31.2 KiB
Minimum2001-07-15 00:00:00
Maximum2026-12-31 00:00:00
2024-05-11T08:33:07.914026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:33:08.516212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3972
Missing (%)100.0%
Memory size35.0 KiB

전화번호
Text

MISSING 

Distinct1971
Distinct (%)82.7%
Missing1588
Missing (%)40.0%
Memory size31.2 KiB
2024-05-11T08:33:09.316027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length8.6967282
Min length2

Characters and Unicode

Total characters20733
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

Unique1705 ?
Unique (%)71.5%

Sample

1st row5724265
2nd row34720711
3rd row34863219
4th row02 4452323
5th row02 5830539
ValueCountFrequency (%)
02 411
 
14.6%
5706365 48
 
1.7%
031 9
 
0.3%
02-535-6103 8
 
0.3%
1577-0711 7
 
0.2%
5706366 7
 
0.2%
5990103 7
 
0.2%
21039500 7
 
0.2%
7662711 7
 
0.2%
4020043 7
 
0.2%
Other values (1927) 2291
81.6%
2024-05-11T08:33:10.735939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3047
14.7%
2 2658
12.8%
0 2340
11.3%
3 1944
9.4%
7 1766
8.5%
4 1637
7.9%
8 1621
7.8%
1 1443
7.0%
9 1404
6.8%
6 1354
6.5%
Other values (3) 1519
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19214
92.7%
Dash Punctuation 1093
 
5.3%
Space Separator 425
 
2.0%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3047
15.9%
2 2658
13.8%
0 2340
12.2%
3 1944
10.1%
7 1766
9.2%
4 1637
8.5%
8 1621
8.4%
1 1443
7.5%
9 1404
7.3%
6 1354
7.0%
Dash Punctuation
ValueCountFrequency (%)
- 1093
100.0%
Space Separator
ValueCountFrequency (%)
425
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20733
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3047
14.7%
2 2658
12.8%
0 2340
11.3%
3 1944
9.4%
7 1766
8.5%
4 1637
7.9%
8 1621
7.8%
1 1443
7.0%
9 1404
6.8%
6 1354
6.5%
Other values (3) 1519
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20733
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3047
14.7%
2 2658
12.8%
0 2340
11.3%
3 1944
9.4%
7 1766
8.5%
4 1637
7.9%
8 1621
7.8%
1 1443
7.0%
9 1404
6.8%
6 1354
6.5%
Other values (3) 1519
7.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3972
Missing (%)100.0%
Memory size35.0 KiB

소재지우편번호
Text

MISSING 

Distinct182
Distinct (%)17.2%
Missing2916
Missing (%)73.4%
Memory size31.2 KiB
2024-05-11T08:33:11.716183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0359848
Min length6

Characters and Unicode

Total characters6374
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

Unique49 ?
Unique (%)4.6%

Sample

1st row137807
2nd row137842
3rd row137807
4th row137908
5th row137044
ValueCountFrequency (%)
137070 51
 
4.8%
137073 31
 
2.9%
137030 27
 
2.6%
137060 26
 
2.5%
137040 20
 
1.9%
137071 18
 
1.7%
137140 15
 
1.4%
137810 15
 
1.4%
137041 15
 
1.4%
137132 15
 
1.4%
Other values (172) 823
77.9%
2024-05-11T08:33:13.497973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 1367
21.4%
1 1298
20.4%
3 1295
20.3%
8 739
11.6%
0 626
9.8%
9 253
 
4.0%
6 233
 
3.7%
4 209
 
3.3%
2 176
 
2.8%
5 137
 
2.1%
Other values (2) 41
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6333
99.4%
Dash Punctuation 38
 
0.6%
Space Separator 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 1367
21.6%
1 1298
20.5%
3 1295
20.4%
8 739
11.7%
0 626
9.9%
9 253
 
4.0%
6 233
 
3.7%
4 209
 
3.3%
2 176
 
2.8%
5 137
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6374
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 1367
21.4%
1 1298
20.4%
3 1295
20.3%
8 739
11.6%
0 626
9.8%
9 253
 
4.0%
6 233
 
3.7%
4 209
 
3.3%
2 176
 
2.8%
5 137
 
2.1%
Other values (2) 41
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6374
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 1367
21.4%
1 1298
20.4%
3 1295
20.3%
8 739
11.6%
0 626
9.8%
9 253
 
4.0%
6 233
 
3.7%
4 209
 
3.3%
2 176
 
2.8%
5 137
 
2.1%
Other values (2) 41
 
0.6%

지번주소
Text

MISSING 

Distinct3488
Distinct (%)88.9%
Missing49
Missing (%)1.2%
Memory size31.2 KiB
2024-05-11T08:33:14.958875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length47
Mean length27.65715
Min length16

Characters and Unicode

Total characters108499
Distinct characters446
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3147 ?
Unique (%)80.2%

Sample

1st row서울특별시 서초구 양재동 1번지 7호
2nd row서울특별시 서초구 방배동 933번지 8호 27통 1반
3rd row서울특별시 서초구 방배동 459번지 10호
4th row서울특별시 서초구 내곡동 1번지 1110호
5th row서울특별시 서초구 방배동 935번지 3호
ValueCountFrequency (%)
서울특별시 3919
 
17.3%
서초구 3913
 
17.3%
서초동 1158
 
5.1%
방배동 789
 
3.5%
614
 
2.7%
1층 587
 
2.6%
양재동 494
 
2.2%
반포동 463
 
2.0%
1호 442
 
2.0%
잠원동 272
 
1.2%
Other values (2694) 9961
44.1%
2024-05-11T08:33:16.629671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22923
21.1%
9379
 
8.6%
1 6237
 
5.7%
5393
 
5.0%
4184
 
3.9%
4051
 
3.7%
3984
 
3.7%
3982
 
3.7%
3958
 
3.6%
3921
 
3.6%
Other values (436) 40487
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63413
58.4%
Space Separator 22923
 
21.1%
Decimal Number 21360
 
19.7%
Dash Punctuation 302
 
0.3%
Uppercase Letter 240
 
0.2%
Other Punctuation 123
 
0.1%
Open Punctuation 47
 
< 0.1%
Close Punctuation 45
 
< 0.1%
Lowercase Letter 33
 
< 0.1%
Math Symbol 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9379
14.8%
5393
 
8.5%
4184
 
6.6%
4051
 
6.4%
3984
 
6.3%
3982
 
6.3%
3958
 
6.2%
3921
 
6.2%
3921
 
6.2%
3810
 
6.0%
Other values (384) 16830
26.5%
Uppercase Letter
ValueCountFrequency (%)
B 84
35.0%
A 19
 
7.9%
I 14
 
5.8%
T 13
 
5.4%
C 12
 
5.0%
G 11
 
4.6%
L 11
 
4.6%
R 9
 
3.8%
P 9
 
3.8%
K 9
 
3.8%
Other values (11) 49
20.4%
Decimal Number
ValueCountFrequency (%)
1 6237
29.2%
3 2396
 
11.2%
2 2251
 
10.5%
5 1774
 
8.3%
0 1769
 
8.3%
4 1742
 
8.2%
7 1498
 
7.0%
6 1401
 
6.6%
8 1242
 
5.8%
9 1050
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
e 6
18.2%
i 4
12.1%
n 4
12.1%
r 4
12.1%
h 4
12.1%
b 3
9.1%
u 2
 
6.1%
g 2
 
6.1%
l 2
 
6.1%
d 2
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 97
78.9%
. 10
 
8.1%
/ 10
 
8.1%
& 3
 
2.4%
? 3
 
2.4%
Math Symbol
ValueCountFrequency (%)
~ 10
76.9%
3
 
23.1%
Space Separator
ValueCountFrequency (%)
22923
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 302
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63413
58.4%
Common 44813
41.3%
Latin 273
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9379
14.8%
5393
 
8.5%
4184
 
6.6%
4051
 
6.4%
3984
 
6.3%
3982
 
6.3%
3958
 
6.2%
3921
 
6.2%
3921
 
6.2%
3810
 
6.0%
Other values (384) 16830
26.5%
Latin
ValueCountFrequency (%)
B 84
30.8%
A 19
 
7.0%
I 14
 
5.1%
T 13
 
4.8%
C 12
 
4.4%
G 11
 
4.0%
L 11
 
4.0%
R 9
 
3.3%
P 9
 
3.3%
K 9
 
3.3%
Other values (21) 82
30.0%
Common
ValueCountFrequency (%)
22923
51.2%
1 6237
 
13.9%
3 2396
 
5.3%
2 2251
 
5.0%
5 1774
 
4.0%
0 1769
 
3.9%
4 1742
 
3.9%
7 1498
 
3.3%
6 1401
 
3.1%
8 1242
 
2.8%
Other values (11) 1580
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63413
58.4%
ASCII 45083
41.6%
Math Operators 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22923
50.8%
1 6237
 
13.8%
3 2396
 
5.3%
2 2251
 
5.0%
5 1774
 
3.9%
0 1769
 
3.9%
4 1742
 
3.9%
7 1498
 
3.3%
6 1401
 
3.1%
8 1242
 
2.8%
Other values (41) 1850
 
4.1%
Hangul
ValueCountFrequency (%)
9379
14.8%
5393
 
8.5%
4184
 
6.6%
4051
 
6.4%
3984
 
6.3%
3982
 
6.3%
3958
 
6.2%
3921
 
6.2%
3921
 
6.2%
3810
 
6.0%
Other values (384) 16830
26.5%
Math Operators
ValueCountFrequency (%)
3
100.0%

도로명주소
Text

MISSING 

Distinct2965
Distinct (%)81.9%
Missing353
Missing (%)8.9%
Memory size31.2 KiB
2024-05-11T08:33:17.494864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length51
Mean length30.829787
Min length17

Characters and Unicode

Total characters111573
Distinct characters457
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2521 ?
Unique (%)69.7%

Sample

1st row서울특별시 서초구 남부순환로356길 15 (양재동)
2nd row서울특별시 서초구 방배로23길 31-2 (방배동)
3rd row서울특별시 서초구 청두곶8길 42 (방배동)
4th row서울특별시 서초구 방배로23길 13 (방배동)
5th row서울특별시 서초구 서초대로 302 (서초동)
ValueCountFrequency (%)
서울특별시 3617
 
17.3%
서초구 3601
 
17.2%
서초동 810
 
3.9%
1층 730
 
3.5%
방배동 623
 
3.0%
양재동 377
 
1.8%
반포동 331
 
1.6%
서초대로 162
 
0.8%
101호 158
 
0.8%
잠원동 156
 
0.7%
Other values (2484) 10327
49.4%
2024-05-11T08:33:19.159049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17280
 
15.5%
9390
 
8.4%
5592
 
5.0%
1 5215
 
4.7%
3975
 
3.6%
3680
 
3.3%
3666
 
3.3%
3654
 
3.3%
( 3647
 
3.3%
) 3647
 
3.3%
Other values (447) 51827
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66370
59.5%
Space Separator 17280
 
15.5%
Decimal Number 16908
 
15.2%
Open Punctuation 3647
 
3.3%
Close Punctuation 3647
 
3.3%
Other Punctuation 2868
 
2.6%
Dash Punctuation 531
 
0.5%
Uppercase Letter 278
 
0.2%
Lowercase Letter 29
 
< 0.1%
Math Symbol 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9390
 
14.1%
5592
 
8.4%
3975
 
6.0%
3680
 
5.5%
3666
 
5.5%
3654
 
5.5%
3620
 
5.5%
3619
 
5.5%
3459
 
5.2%
2030
 
3.1%
Other values (391) 23685
35.7%
Uppercase Letter
ValueCountFrequency (%)
B 109
39.2%
A 22
 
7.9%
T 16
 
5.8%
I 14
 
5.0%
C 13
 
4.7%
L 12
 
4.3%
R 11
 
4.0%
G 10
 
3.6%
P 10
 
3.6%
K 9
 
3.2%
Other values (12) 52
18.7%
Lowercase Letter
ValueCountFrequency (%)
n 4
13.8%
i 4
13.8%
b 3
10.3%
r 3
10.3%
e 3
10.3%
l 2
6.9%
u 2
6.9%
g 2
6.9%
d 2
6.9%
o 1
 
3.4%
Other values (3) 3
10.3%
Decimal Number
ValueCountFrequency (%)
1 5215
30.8%
2 2233
13.2%
3 1713
 
10.1%
0 1583
 
9.4%
4 1292
 
7.6%
5 1242
 
7.3%
7 1041
 
6.2%
6 969
 
5.7%
9 839
 
5.0%
8 781
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 2856
99.6%
/ 5
 
0.2%
& 3
 
0.1%
. 2
 
0.1%
? 2
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 12
80.0%
3
 
20.0%
Space Separator
ValueCountFrequency (%)
17280
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3647
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3647
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 531
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66370
59.5%
Common 44896
40.2%
Latin 307
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9390
 
14.1%
5592
 
8.4%
3975
 
6.0%
3680
 
5.5%
3666
 
5.5%
3654
 
5.5%
3620
 
5.5%
3619
 
5.5%
3459
 
5.2%
2030
 
3.1%
Other values (391) 23685
35.7%
Latin
ValueCountFrequency (%)
B 109
35.5%
A 22
 
7.2%
T 16
 
5.2%
I 14
 
4.6%
C 13
 
4.2%
L 12
 
3.9%
R 11
 
3.6%
G 10
 
3.3%
P 10
 
3.3%
K 9
 
2.9%
Other values (25) 81
26.4%
Common
ValueCountFrequency (%)
17280
38.5%
1 5215
 
11.6%
( 3647
 
8.1%
) 3647
 
8.1%
, 2856
 
6.4%
2 2233
 
5.0%
3 1713
 
3.8%
0 1583
 
3.5%
4 1292
 
2.9%
5 1242
 
2.8%
Other values (11) 4188
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66370
59.5%
ASCII 45200
40.5%
Math Operators 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17280
38.2%
1 5215
 
11.5%
( 3647
 
8.1%
) 3647
 
8.1%
, 2856
 
6.3%
2 2233
 
4.9%
3 1713
 
3.8%
0 1583
 
3.5%
4 1292
 
2.9%
5 1242
 
2.7%
Other values (45) 4492
 
9.9%
Hangul
ValueCountFrequency (%)
9390
 
14.1%
5592
 
8.4%
3975
 
6.0%
3680
 
5.5%
3666
 
5.5%
3654
 
5.5%
3620
 
5.5%
3619
 
5.5%
3459
 
5.2%
2030
 
3.1%
Other values (391) 23685
35.7%
Math Operators
ValueCountFrequency (%)
3
100.0%

도로명우편번호
Text

MISSING 

Distinct389
Distinct (%)33.1%
Missing2795
Missing (%)70.4%
Memory size31.2 KiB
2024-05-11T08:33:20.025069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4180119
Min length5

Characters and Unicode

Total characters6377
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

Unique127 ?
Unique (%)10.8%

Sample

1st row06602
2nd row06545
3rd row06630
4th row137888
5th row06645
ValueCountFrequency (%)
137071 22
 
1.9%
137140 13
 
1.1%
137040 13
 
1.1%
137810 12
 
1.0%
06802 12
 
1.0%
06735 12
 
1.0%
06800 11
 
0.9%
137073 10
 
0.8%
137061 10
 
0.8%
06545 10
 
0.8%
Other values (379) 1052
89.4%
2024-05-11T08:33:21.258279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1170
18.3%
0 1126
17.7%
7 1008
15.8%
1 716
11.2%
3 686
10.8%
8 497
7.8%
5 425
 
6.7%
9 258
 
4.0%
4 240
 
3.8%
2 229
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6355
99.7%
Dash Punctuation 22
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1170
18.4%
0 1126
17.7%
7 1008
15.9%
1 716
11.3%
3 686
10.8%
8 497
7.8%
5 425
 
6.7%
9 258
 
4.1%
4 240
 
3.8%
2 229
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6377
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 1170
18.3%
0 1126
17.7%
7 1008
15.8%
1 716
11.2%
3 686
10.8%
8 497
7.8%
5 425
 
6.7%
9 258
 
4.0%
4 240
 
3.8%
2 229
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6377
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 1170
18.3%
0 1126
17.7%
7 1008
15.8%
1 716
11.2%
3 686
10.8%
8 497
7.8%
5 425
 
6.7%
9 258
 
4.0%
4 240
 
3.8%
2 229
 
3.6%
Distinct3155
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
2024-05-11T08:33:22.013279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length7.8378651
Min length1

Characters and Unicode

Total characters31132
Distinct characters640
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2668 ?
Unique (%)67.2%

Sample

1st row장미식품
2nd row동해식품
3rd row동네슈퍼
4th row중앙식품
5th row고려식품
ValueCountFrequency (%)
gs25 210
 
3.9%
씨유 193
 
3.5%
세븐일레븐 101
 
1.9%
지에스25 71
 
1.3%
주)코리아세븐 68
 
1.2%
미니스톱 67
 
1.2%
훼미리마트 55
 
1.0%
이마트24 43
 
0.8%
지에스(gs)25 34
 
0.6%
주)바이더웨이 30
 
0.6%
Other values (2975) 4577
84.0%
2024-05-11T08:33:23.353601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1739
 
5.6%
1488
 
4.8%
820
 
2.6%
769
 
2.5%
765
 
2.5%
2 698
 
2.2%
677
 
2.2%
634
 
2.0%
5 595
 
1.9%
522
 
1.7%
Other values (630) 22425
72.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25562
82.1%
Decimal Number 1742
 
5.6%
Space Separator 1488
 
4.8%
Uppercase Letter 1214
 
3.9%
Close Punctuation 511
 
1.6%
Open Punctuation 505
 
1.6%
Lowercase Letter 46
 
0.1%
Dash Punctuation 40
 
0.1%
Other Punctuation 23
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1739
 
6.8%
820
 
3.2%
769
 
3.0%
765
 
3.0%
677
 
2.6%
634
 
2.5%
522
 
2.0%
464
 
1.8%
422
 
1.7%
407
 
1.6%
Other values (567) 18343
71.8%
Uppercase Letter
ValueCountFrequency (%)
G 446
36.7%
S 430
35.4%
L 61
 
5.0%
C 36
 
3.0%
A 26
 
2.1%
T 25
 
2.1%
U 21
 
1.7%
R 21
 
1.7%
M 19
 
1.6%
K 18
 
1.5%
Other values (14) 111
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
e 9
19.6%
o 5
10.9%
a 4
 
8.7%
c 3
 
6.5%
n 3
 
6.5%
p 3
 
6.5%
m 2
 
4.3%
l 2
 
4.3%
s 2
 
4.3%
k 2
 
4.3%
Other values (8) 11
23.9%
Decimal Number
ValueCountFrequency (%)
2 698
40.1%
5 595
34.2%
1 118
 
6.8%
4 99
 
5.7%
3 52
 
3.0%
6 44
 
2.5%
0 43
 
2.5%
9 42
 
2.4%
8 26
 
1.5%
7 25
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 10
43.5%
& 7
30.4%
? 3
 
13.0%
, 1
 
4.3%
1
 
4.3%
/ 1
 
4.3%
Space Separator
ValueCountFrequency (%)
1488
100.0%
Close Punctuation
ValueCountFrequency (%)
) 511
100.0%
Open Punctuation
ValueCountFrequency (%)
( 505
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25560
82.1%
Common 4310
 
13.8%
Latin 1260
 
4.0%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1739
 
6.8%
820
 
3.2%
769
 
3.0%
765
 
3.0%
677
 
2.6%
634
 
2.5%
522
 
2.0%
464
 
1.8%
422
 
1.7%
407
 
1.6%
Other values (565) 18341
71.8%
Latin
ValueCountFrequency (%)
G 446
35.4%
S 430
34.1%
L 61
 
4.8%
C 36
 
2.9%
A 26
 
2.1%
T 25
 
2.0%
U 21
 
1.7%
R 21
 
1.7%
M 19
 
1.5%
K 18
 
1.4%
Other values (32) 157
 
12.5%
Common
ValueCountFrequency (%)
1488
34.5%
2 698
16.2%
5 595
 
13.8%
) 511
 
11.9%
( 505
 
11.7%
1 118
 
2.7%
4 99
 
2.3%
3 52
 
1.2%
6 44
 
1.0%
0 43
 
1.0%
Other values (11) 157
 
3.6%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25559
82.1%
ASCII 5569
 
17.9%
CJK 2
 
< 0.1%
None 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1739
 
6.8%
820
 
3.2%
769
 
3.0%
765
 
3.0%
677
 
2.6%
634
 
2.5%
522
 
2.0%
464
 
1.8%
422
 
1.7%
407
 
1.6%
Other values (564) 18340
71.8%
ASCII
ValueCountFrequency (%)
1488
26.7%
2 698
12.5%
5 595
 
10.7%
) 511
 
9.2%
( 505
 
9.1%
G 446
 
8.0%
S 430
 
7.7%
1 118
 
2.1%
4 99
 
1.8%
L 61
 
1.1%
Other values (52) 618
11.1%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct2800
Distinct (%)70.5%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
Minimum2007-07-16 13:46:33
Maximum2024-05-08 14:40:36
2024-05-11T08:33:23.887708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:33:24.351862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
I
3301 
U
671 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 3301
83.1%
U 671
 
16.9%

Length

2024-05-11T08:33:24.769477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:25.072699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3301
83.1%
u 671
 
16.9%
Distinct592
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T08:33:25.416517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:33:25.930408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3972
Missing (%)100.0%
Memory size35.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1622
Distinct (%)43.0%
Missing202
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean201214.52
Minimum192766.24
Maximum212652.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.0 KiB
2024-05-11T08:33:26.301701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum192766.24
5-th percentile198545.7
Q1199783.06
median201235.62
Q3202376.71
95-th percentile203881.97
Maximum212652.21
Range19885.962
Interquartile range (IQR)2593.6575

Descriptive statistics

Standard deviation1730.7413
Coefficient of variation (CV)0.0086014734
Kurtosis0.14159837
Mean201214.52
Median Absolute Deviation (MAD)1246.0454
Skewness0.24089691
Sum7.5857873 × 108
Variance2995465.5
MonotonicityNot monotonic
2024-05-11T08:33:26.755072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200554.74395758 35
 
0.9%
200250.447804795 32
 
0.8%
198787.701562761 14
 
0.4%
202535.840179252 13
 
0.3%
202245.377899369 13
 
0.3%
202508.646065919 12
 
0.3%
202647.320791436 11
 
0.3%
202481.661169413 11
 
0.3%
203204.755637424 10
 
0.3%
200922.886137239 10
 
0.3%
Other values (1612) 3609
90.9%
(Missing) 202
 
5.1%
ValueCountFrequency (%)
192766.244085517 1
< 0.1%
197020.257135497 1
< 0.1%
198341.208478761 2
0.1%
198344.761390706 2
0.1%
198351.955 2
0.1%
198353.824006002 1
< 0.1%
198358.536839066 2
0.1%
198359.032400861 1
< 0.1%
198360.229504349 1
< 0.1%
198364.994691704 1
< 0.1%
ValueCountFrequency (%)
212652.206525871 1
 
< 0.1%
207858.539092723 1
 
< 0.1%
207843.274713732 2
0.1%
207409.528119388 3
0.1%
207067.171171962 1
 
< 0.1%
206761.589469844 2
0.1%
206527.143128753 1
 
< 0.1%
206300.642742233 2
0.1%
206222.68463863 2
0.1%
206203.268522037 2
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1621
Distinct (%)43.0%
Missing202
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean442912.63
Minimum437085.18
Maximum454495.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.0 KiB
2024-05-11T08:33:27.180250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437085.18
5-th percentile440338.98
Q1442049.99
median442833.26
Q3443841.25
95-th percentile445445.19
Maximum454495.26
Range17410.083
Interquartile range (IQR)1791.256

Descriptive statistics

Standard deviation1544.6879
Coefficient of variation (CV)0.0034875681
Kurtosis1.8624263
Mean442912.63
Median Absolute Deviation (MAD)880.92134
Skewness0.061560983
Sum1.6697806 × 109
Variance2386060.9
MonotonicityNot monotonic
2024-05-11T08:33:27.633128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444811.364826199 35
 
0.9%
444683.220506107 32
 
0.8%
442119.420431824 14
 
0.4%
441604.113261939 13
 
0.3%
442987.986999742 13
 
0.3%
442625.413940559 12
 
0.3%
442628.258844927 11
 
0.3%
442563.269271521 11
 
0.3%
440136.781183797 10
 
0.3%
444254.984557647 10
 
0.3%
Other values (1611) 3609
90.9%
(Missing) 202
 
5.1%
ValueCountFrequency (%)
437085.180151344 1
 
< 0.1%
437907.054302796 1
 
< 0.1%
437908.032326145 2
0.1%
437930.916808011 1
 
< 0.1%
437968.892025771 1
 
< 0.1%
437979.542859349 1
 
< 0.1%
438076.641692935 1
 
< 0.1%
438092.114640553 4
0.1%
438140.645891284 1
 
< 0.1%
438159.295209654 1
 
< 0.1%
ValueCountFrequency (%)
454495.263596728 1
 
< 0.1%
453723.397421668 1
 
< 0.1%
452523.434524578 1
 
< 0.1%
446565.028672992 2
0.1%
446493.163455058 4
0.1%
446468.203584104 2
0.1%
446439.134713956 1
 
< 0.1%
446318.215190813 1
 
< 0.1%
446314.687402426 2
0.1%
446312.955196265 3
0.1%

지정일자
Real number (ℝ)

MISSING 

Distinct1708
Distinct (%)70.1%
Missing1536
Missing (%)38.7%
Infinite0
Infinite (%)0.0%
Mean20082360
Minimum19810825
Maximum20220215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.0 KiB
2024-05-11T08:33:28.082347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19810825
5-th percentile19971231
Q120040602
median20081207
Q320130820
95-th percentile20190618
Maximum20220215
Range409390
Interquartile range (IQR)90217.5

Descriptive statistics

Standard deviation67610.207
Coefficient of variation (CV)0.0033666464
Kurtosis0.60162514
Mean20082360
Median Absolute Deviation (MAD)49000
Skewness-0.5224403
Sum4.892063 × 1010
Variance4.57114 × 109
MonotonicityNot monotonic
2024-05-11T08:33:28.549955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19981023 8
 
0.2%
20031117 6
 
0.2%
19981026 6
 
0.2%
20010212 6
 
0.2%
20050131 5
 
0.1%
20111101 5
 
0.1%
19990525 5
 
0.1%
20020610 5
 
0.1%
20150116 5
 
0.1%
20160926 5
 
0.1%
Other values (1698) 2380
59.9%
(Missing) 1536
38.7%
ValueCountFrequency (%)
19810825 1
< 0.1%
19811005 1
< 0.1%
19811118 1
< 0.1%
19821124 1
< 0.1%
19821224 1
< 0.1%
19830324 1
< 0.1%
19830512 1
< 0.1%
19830706 1
< 0.1%
19830803 1
< 0.1%
19840329 1
< 0.1%
ValueCountFrequency (%)
20220215 1
< 0.1%
20220214 1
< 0.1%
20220208 1
< 0.1%
20220203 1
< 0.1%
20220124 1
< 0.1%
20220117 1
< 0.1%
20211216 1
< 0.1%
20211118 1
< 0.1%
20211101 1
< 0.1%
20211028 1
< 0.1%

민원종류명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
<NA>
1537 
2009년11월법개정전자료
1290 
제7조의3제2항에따른경우
909 
제7조의3제3항에따른경우
236 

Length

Max length14
Median length13
Mean length9.842145
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1537
38.7%
2009년11월법개정전자료 1290
32.5%
제7조의3제2항에따른경우 909
22.9%
제7조의3제3항에따른경우 236
 
5.9%

Length

2024-05-11T08:33:28.985739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:29.335167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1537
38.7%
2009년11월법개정전자료 1290
32.5%
제7조의3제2항에따른경우 909
22.9%
제7조의3제3항에따른경우 236
 
5.9%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자민원종류명
03210000196832100760560000119981102<NA>3폐업2폐업처리20020430<NA><NA><NA>5724265<NA><NA>서울특별시 서초구 양재동 1번지 7호서울특별시 서초구 남부순환로356길 15 (양재동)<NA>장미식품2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>203288.558316442465.267742<NA><NA>
13210000197332100760560000219981111<NA>3폐업2폐업처리20011123<NA><NA><NA>34720711<NA><NA>서울특별시 서초구 방배동 933번지 8호 27통 1반서울특별시 서초구 방배로23길 31-2 (방배동)<NA>동해식품2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>199270.09136442625.457829<NA><NA>
23210000197432100760560000119990911<NA>3폐업2폐업처리20010730<NA><NA><NA>34863219<NA><NA>서울특별시 서초구 방배동 459번지 10호서울특별시 서초구 청두곶8길 42 (방배동)<NA>동네슈퍼2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>198787.701563442119.420432<NA><NA>
33210000197632100760560내1519760416<NA>1영업/정상0정상영업<NA><NA><NA><NA>02 4452323<NA><NA>서울특별시 서초구 내곡동 1번지 1110호<NA><NA>중앙식품2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>207067.171172439228.366225<NA><NA>
4321000019773210076056방12019770901<NA>3폐업2폐업처리20060922<NA><NA><NA>02 5830539<NA><NA>서울특별시 서초구 방배동 935번지 3호서울특별시 서초구 방배로23길 13 (방배동)<NA>고려식품2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>199356.032509442668.072358<NA><NA>
53210000197832100760560000119981023<NA>3폐업2폐업처리20011112<NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1673번지 1호서울특별시 서초구 서초대로 302 (서초동)<NA>서초부동산2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>201229.105262443500.998342<NA><NA>
63210000197832100760560007119780701200111074취소/말소/만료/정지/중지3직권취소<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 방배동 613호서울특별시 서초구 남부순환로296가길 10-4 (방배동)<NA>성우상회2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>199453.746113441054.634527<NA><NA>
73210000197932100760560000119981114200110104취소/말소/만료/정지/중지3직권취소<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 반포동 19번지 1호서울특별시 서초구 신반포로 162 (반포동)<NA>보성약국2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>200115.143203444741.437478<NA><NA>
8321000019793210076056000031998121<NA>3폐업2폐업처리20010712<NA><NA><NA>5861120<NA><NA>서울특별시 서초구 서초동 1603번지 22호서울특별시 서초구 서초중앙로8길 38-2 (서초동)<NA>남양슈퍼마켓2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>201470.913122442743.284578<NA><NA>
93210000198032100760560001119800125<NA>3폐업2폐업처리20030930<NA><NA><NA>1111111<NA><NA>서울특별시 서초구 반포동 809호 반포상가1블럭 22호서울특별시 서초구 신반포로 45 (반포동,반포상가1블럭 22호)<NA>우신식품2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>198894.158789444582.929319<NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자민원종류명
3962321000020243210195056000102024-04-02<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 양재동 206-6 모젠하우스서울특별시 서초구 매헌로6길 36-9, 1층 (양재동, 모젠하우스)06770이마트24R 양재잔디점2024-04-02 13:02:40I2023-12-04 00:04:00.0<NA>203071.839949440364.391562<NA><NA>
3963321000020243210195056000112024-04-09<NA>1영업/정상0정상영업<NA><NA><NA><NA>02-407-7758<NA><NA>서울특별시 서초구 반포동 115-5서울특별시 서초구 한강남자전거길 2172, 1층 (반포동)06500한강르네상스 반포2호점2024-04-09 17:56:18I2023-12-03 23:01:00.0<NA>199512.055422445283.167985<NA><NA>
3964321000020243210195056000122024-04-09<NA>1영업/정상0정상영업<NA><NA><NA><NA>02-582-9082<NA><NA>서울특별시 서초구 서초동 1610-2서울특별시 서초구 효령로67길 63, 1층 (서초동)06642세븐일레븐 서초희망점2024-04-11 09:03:37I2023-12-03 23:03:00.0<NA>201919.166343443080.814764<NA><NA>
3965321000020243210195056000132024-04-18<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 양재동 275-4 트윈타워 B동 101~2호서울특별시 서초구 마방로10길 15, 트윈타워 B동 101~102호 (양재동)06775지에스25 양재트윈타워점2024-04-18 09:23:24I2023-12-03 22:00:00.0<NA>203815.668827441633.343953<NA><NA>
3966321000020243210195056000142024-04-18<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 방배동 918-1 하나빌서울특별시 서초구 방배중앙로 18, 하나빌 1층 (방배동)06687씨유 방배중앙로점2024-04-18 13:20:04I2023-12-03 22:00:00.0<NA>199299.99769442165.404369<NA><NA>
3967321000020243210195056000152024-04-18<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1714-11서울특별시 서초구 법원로2길 17-8, 1층 (서초동)06596씨유 서초법원점2024-04-18 14:50:55I2023-12-03 22:00:00.0<NA>201042.628447443621.131715<NA><NA>
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39713210000500132101220560324019930706<NA>3폐업2폐업처리20071213<NA><NA><NA>02 5829283<NA><NA>서울특별시 서초구 서초동 1332번지 1 호<NA><NA>서문사2007-12-13 10:30:39I2018-08-31 23:59:59.0<NA><NA><NA>199307062009년11월법개정전자료