Overview

Dataset statistics

Number of variables27
Number of observations2709
Missing cells23612
Missing cells (%)32.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory598.0 KiB
Average record size in memory226.0 B

Variable types

Categorical7
Numeric4
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
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-19914/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 2391 (88.3%) missing valuesMissing
폐업일자 has 871 (32.2%) missing valuesMissing
휴업시작일자 has 2650 (97.8%) missing valuesMissing
휴업종료일자 has 2650 (97.8%) missing valuesMissing
재개업일자 has 2709 (100.0%) missing valuesMissing
전화번호 has 1177 (43.4%) missing valuesMissing
소재지면적 has 2709 (100.0%) missing valuesMissing
소재지우편번호 has 1968 (72.6%) missing valuesMissing
지번주소 has 47 (1.7%) missing valuesMissing
도로명주소 has 406 (15.0%) missing valuesMissing
도로명우편번호 has 1789 (66.0%) missing valuesMissing
업태구분명 has 2709 (100.0%) missing valuesMissing
좌표정보(X) has 260 (9.6%) missing valuesMissing
좌표정보(Y) has 260 (9.6%) missing valuesMissing
지정일자 has 1016 (37.5%) 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

Reproduction

Analysis started2024-04-06 13:26:31.773420
Analysis finished2024-04-06 13:26:32.717251
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
3120000
2709 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 2709
100.0%

Length

2024-04-06T22:26:32.771049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:26:32.850001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 2709
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct2709
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0008037 × 1018
Minimum3.1200931 × 1014
Maximum2.024312 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.9 KiB
2024-04-06T22:26:32.944650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1200931 × 1014
5-th percentile1.998312 × 1018
Q12.001312 × 1018
median2.005312 × 1018
Q32.013312 × 1018
95-th percentile2.021312 × 1018
Maximum2.024312 × 1018
Range2.024 × 1018
Interquartile range (IQR)1.2000007 × 1016

Descriptive statistics

Standard deviation1.1323615 × 1017
Coefficient of variation (CV)0.056595332
Kurtosis295.70998
Mean2.0008037 × 1018
Median Absolute Deviation (MAD)4.0000026 × 1015
Skewness-17.199065
Sum-3.1655171 × 1018
Variance1.2822426 × 1034
MonotonicityStrictly increasing
2024-04-06T22:26:33.073869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
312009305600695 1
 
< 0.1%
2010312011905600019 1
 
< 0.1%
2010312011905600011 1
 
< 0.1%
2010312011905600012 1
 
< 0.1%
2010312011905600013 1
 
< 0.1%
2010312011905600014 1
 
< 0.1%
2010312011905600015 1
 
< 0.1%
2010312011905600016 1
 
< 0.1%
2010312011905600017 1
 
< 0.1%
2010312011905600018 1
 
< 0.1%
Other values (2699) 2699
99.6%
ValueCountFrequency (%)
312009305600695 1
< 0.1%
312011905600759 1
< 0.1%
312011905600954 1
< 0.1%
312011905601474 1
< 0.1%
312014505600000 1
< 0.1%
312014505600894 1
< 0.1%
84312007505600725 1
< 0.1%
84312007505601486 1
< 0.1%
239312010705616074 1
< 0.1%
1980312011905601005 1
< 0.1%
ValueCountFrequency (%)
2024312021905600012 1
< 0.1%
2024312021905600011 1
< 0.1%
2024312021905600010 1
< 0.1%
2024312021905600009 1
< 0.1%
2024312021905600008 1
< 0.1%
2024312021905600007 1
< 0.1%
2024312021905600006 1
< 0.1%
2024312021905600005 1
< 0.1%
2024312021905600004 1
< 0.1%
2024312021905600003 1
< 0.1%

인허가일자
Text

Distinct1851
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
2024-04-06T22:26:33.338757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.1011443
Min length8

Characters and Unicode

Total characters21946
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

Unique1350 ?
Unique (%)49.8%

Sample

1st row19941210
2nd row20091119
3rd row19900101
4th row20090511
5th row19900101
ValueCountFrequency (%)
19981229 24
 
0.9%
19981221 17
 
0.6%
19981219 15
 
0.6%
19981209 15
 
0.6%
19981207 14
 
0.5%
19981226 13
 
0.5%
20010101 12
 
0.4%
19981114 10
 
0.4%
19981216 10
 
0.4%
19900101 7
 
0.3%
Other values (1842) 2573
94.9%
2024-04-06T22:26:33.741343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6701
30.5%
2 4238
19.3%
1 4223
19.2%
9 1952
 
8.9%
8 913
 
4.2%
3 898
 
4.1%
7 738
 
3.4%
5 685
 
3.1%
6 668
 
3.0%
4 654
 
3.0%
Other values (2) 276
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21670
98.7%
Dash Punctuation 274
 
1.2%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6701
30.9%
2 4238
19.6%
1 4223
19.5%
9 1952
 
9.0%
8 913
 
4.2%
3 898
 
4.1%
7 738
 
3.4%
5 685
 
3.2%
6 668
 
3.1%
4 654
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 274
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21946
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6701
30.5%
2 4238
19.3%
1 4223
19.2%
9 1952
 
8.9%
8 913
 
4.2%
3 898
 
4.1%
7 738
 
3.4%
5 685
 
3.1%
6 668
 
3.0%
4 654
 
3.0%
Other values (2) 276
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21946
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6701
30.5%
2 4238
19.3%
1 4223
19.2%
9 1952
 
8.9%
8 913
 
4.2%
3 898
 
4.1%
7 738
 
3.4%
5 685
 
3.1%
6 668
 
3.0%
4 654
 
3.0%
Other values (2) 276
 
1.3%

인허가취소일자
Date

MISSING 

Distinct120
Distinct (%)37.7%
Missing2391
Missing (%)88.3%
Memory size21.3 KiB
Minimum1998-01-10 00:00:00
Maximum2023-12-27 00:00:00
2024-04-06T22:26:33.870508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:26:33.982838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태코드
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
3
1838 
1
543 
4
328 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row4
5th row3

Common Values

ValueCountFrequency (%)
3 1838
67.8%
1 543
 
20.0%
4 328
 
12.1%

Length

2024-04-06T22:26:34.106905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:26:34.206263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1838
67.8%
1 543
 
20.0%
4 328
 
12.1%

영업상태명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
폐업
1838 
영업/정상
543 
취소/말소/만료/정지/중지
328 

Length

Max length14
Median length2
Mean length4.0542636
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row취소/말소/만료/정지/중지
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 1838
67.8%
영업/정상 543
 
20.0%
취소/말소/만료/정지/중지 328
 
12.1%

Length

2024-04-06T22:26:34.323474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:26:34.656273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1838
67.8%
영업/정상 543
 
20.0%
취소/말소/만료/정지/중지 328
 
12.1%

상세영업상태코드
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
2
1838 
0
543 
3
192 
5
 
134
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 1838
67.8%
0 543
 
20.0%
3 192
 
7.1%
5 134
 
4.9%
4 2
 
0.1%

Length

2024-04-06T22:26:34.746879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:26:34.837408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1838
67.8%
0 543
 
20.0%
3 192
 
7.1%
5 134
 
4.9%
4 2
 
0.1%

상세영업상태명
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
폐업처리
1838 
정상영업
543 
직권취소
192 
지정취소
 
134
임시소매기간만료
 
2

Length

Max length8
Median length4
Mean length4.0029531
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 1838
67.8%
정상영업 543
 
20.0%
직권취소 192
 
7.1%
지정취소 134
 
4.9%
임시소매기간만료 2
 
0.1%

Length

2024-04-06T22:26:34.941428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:26:35.041535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 1838
67.8%
정상영업 543
 
20.0%
직권취소 192
 
7.1%
지정취소 134
 
4.9%
임시소매기간만료 2
 
0.1%

폐업일자
Date

MISSING 

Distinct1445
Distinct (%)78.6%
Missing871
Missing (%)32.2%
Memory size21.3 KiB
Minimum1999-01-20 00:00:00
Maximum2024-04-02 00:00:00
2024-04-06T22:26:35.145195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:26:35.279553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct51
Distinct (%)86.4%
Missing2650
Missing (%)97.8%
Memory size21.3 KiB
Minimum2000-12-27 00:00:00
Maximum2023-07-03 00:00:00
2024-04-06T22:26:35.416061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:26:35.571316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업종료일자
Date

MISSING 

Distinct50
Distinct (%)84.7%
Missing2650
Missing (%)97.8%
Memory size21.3 KiB
Minimum2001-05-06 00:00:00
Maximum2023-08-01 00:00:00
2024-04-06T22:26:35.723126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:26:35.872713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2709
Missing (%)100.0%
Memory size23.9 KiB

전화번호
Text

MISSING 

Distinct1342
Distinct (%)87.6%
Missing1177
Missing (%)43.4%
Memory size21.3 KiB
2024-04-06T22:26:36.108761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length9.9745431
Min length2

Characters and Unicode

Total characters15281
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1198 ?
Unique (%)78.2%

Sample

1st row02 3728763
2nd row372-8420
3rd row02 3724120
4th row02 3957609
5th row391-6074
ValueCountFrequency (%)
02 778
33.3%
031 9
 
0.4%
1577-0711 6
 
0.3%
3961739 5
 
0.2%
3759937 5
 
0.2%
3138115 5
 
0.2%
3766404 4
 
0.2%
0232165402 4
 
0.2%
0232166074 4
 
0.2%
0231470908 4
 
0.2%
Other values (1345) 1509
64.7%
2024-04-06T22:26:36.461434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2538
16.6%
3 2354
15.4%
2 2314
15.1%
7 1059
6.9%
1 1026
6.7%
9 985
 
6.4%
6 972
 
6.4%
4 916
 
6.0%
5 900
 
5.9%
803
 
5.3%
Other values (6) 1414
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13776
90.2%
Space Separator 803
 
5.3%
Dash Punctuation 696
 
4.6%
Close Punctuation 3
 
< 0.1%
Math Symbol 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2538
18.4%
3 2354
17.1%
2 2314
16.8%
7 1059
7.7%
1 1026
7.4%
9 985
 
7.2%
6 972
 
7.1%
4 916
 
6.6%
5 900
 
6.5%
8 712
 
5.2%
Math Symbol
ValueCountFrequency (%)
= 1
50.0%
~ 1
50.0%
Space Separator
ValueCountFrequency (%)
803
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 696
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15281
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2538
16.6%
3 2354
15.4%
2 2314
15.1%
7 1059
6.9%
1 1026
6.7%
9 985
 
6.4%
6 972
 
6.4%
4 916
 
6.0%
5 900
 
5.9%
803
 
5.3%
Other values (6) 1414
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15281
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2538
16.6%
3 2354
15.4%
2 2314
15.1%
7 1059
6.9%
1 1026
6.7%
9 985
 
6.4%
6 972
 
6.4%
4 916
 
6.0%
5 900
 
5.9%
803
 
5.3%
Other values (6) 1414
9.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2709
Missing (%)100.0%
Memory size23.9 KiB

소재지우편번호
Text

MISSING 

Distinct121
Distinct (%)16.3%
Missing1968
Missing (%)72.6%
Memory size21.3 KiB
2024-04-06T22:26:36.681223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0269906
Min length6

Characters and Unicode

Total characters4466
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

Unique41 ?
Unique (%)5.5%

Sample

1st row120121
2nd row120130
3rd row120132
4th row120807
5th row120090
ValueCountFrequency (%)
120180 49
 
6.6%
120110 49
 
6.6%
120170 29
 
3.9%
120130 28
 
3.8%
120100 24
 
3.2%
120190 24
 
3.2%
120013 21
 
2.8%
120808 18
 
2.4%
120120 17
 
2.3%
120160 16
 
2.2%
Other values (111) 466
62.9%
2024-04-06T22:26:37.052408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1325
29.7%
1 1224
27.4%
2 861
19.3%
8 376
 
8.4%
3 145
 
3.2%
7 128
 
2.9%
5 99
 
2.2%
9 95
 
2.1%
4 92
 
2.1%
6 80
 
1.8%
Other values (2) 41
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4425
99.1%
Space Separator 21
 
0.5%
Dash Punctuation 20
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1325
29.9%
1 1224
27.7%
2 861
19.5%
8 376
 
8.5%
3 145
 
3.3%
7 128
 
2.9%
5 99
 
2.2%
9 95
 
2.1%
4 92
 
2.1%
6 80
 
1.8%
Space Separator
ValueCountFrequency (%)
21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4466
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1325
29.7%
1 1224
27.4%
2 861
19.3%
8 376
 
8.4%
3 145
 
3.2%
7 128
 
2.9%
5 99
 
2.2%
9 95
 
2.1%
4 92
 
2.1%
6 80
 
1.8%
Other values (2) 41
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4466
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1325
29.7%
1 1224
27.4%
2 861
19.3%
8 376
 
8.4%
3 145
 
3.2%
7 128
 
2.9%
5 99
 
2.2%
9 95
 
2.1%
4 92
 
2.1%
6 80
 
1.8%
Other values (2) 41
 
0.9%

지번주소
Text

MISSING 

Distinct2262
Distinct (%)85.0%
Missing47
Missing (%)1.7%
Memory size21.3 KiB
2024-04-06T22:26:37.379458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length56
Mean length27.009016
Min length14

Characters and Unicode

Total characters71898
Distinct characters348
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

Unique1955 ?
Unique (%)73.4%

Sample

1st row서울특별시 서대문구 남가좌동 171번지 2호
2nd row서울특별시 서대문구 남가좌1동 155번지 209호
3rd row서울특별시 서대문구 북가좌동 126번지 3호
4th row서울특별시 서대문구 북가좌2동 3번지 40호
5th row서울특별시 서대문구 남가좌2동 341번지 9호
ValueCountFrequency (%)
서대문구 2687
 
18.4%
서울특별시 2659
 
18.2%
호 458
 
3.1%
홍은동 348
 
2.4%
홍제동 345
 
2.4%
남가좌동 310
 
2.1%
연희동 278
 
1.9%
북가좌동 272
 
1.9%
1층 233
 
1.6%
창천동 205
 
1.4%
Other values (1659) 6818
46.7%
2024-04-06T22:26:37.889945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14548
20.2%
서 5375
 
7.5%
대 3016
 
4.2%
1 2754
 
3.8%
문 2729
 
3.8%
구 2729
 
3.8%
시 2675
 
3.7%
울 2665
 
3.7%
별 2662
 
3.7%
특 2659
 
3.7%
Other values (338) 30086
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44069
61.3%
Space Separator 14548
 
20.2%
Decimal Number 12566
 
17.5%
Dash Punctuation 199
 
0.3%
Uppercase Letter 157
 
0.2%
Other Punctuation 132
 
0.2%
Close Punctuation 108
 
0.2%
Open Punctuation 104
 
0.1%
Lowercase Letter 12
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 5375
 
12.2%
대 3016
 
6.8%
문 2729
 
6.2%
구 2729
 
6.2%
시 2675
 
6.1%
울 2665
 
6.0%
별 2662
 
6.0%
특 2659
 
6.0%
동 2639
 
6.0%
호 2468
 
5.6%
Other values (292) 14452
32.8%
Uppercase Letter
ValueCountFrequency (%)
B 28
17.8%
M 27
17.2%
D 26
16.6%
C 23
14.6%
A 23
14.6%
K 4
 
2.5%
S 3
 
1.9%
E 3
 
1.9%
L 3
 
1.9%
G 3
 
1.9%
Other values (12) 14
8.9%
Decimal Number
ValueCountFrequency (%)
1 2754
21.9%
2 1821
14.5%
3 1550
12.3%
4 1248
9.9%
0 1061
 
8.4%
5 1022
 
8.1%
7 851
 
6.8%
6 813
 
6.5%
9 767
 
6.1%
8 679
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
e 6
50.0%
a 2
 
16.7%
m 2
 
16.7%
w 1
 
8.3%
l 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 98
74.2%
@ 31
 
23.5%
& 2
 
1.5%
/ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
14548
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 199
100.0%
Close Punctuation
ValueCountFrequency (%)
) 108
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44069
61.3%
Common 27660
38.5%
Latin 169
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 5375
 
12.2%
대 3016
 
6.8%
문 2729
 
6.2%
구 2729
 
6.2%
시 2675
 
6.1%
울 2665
 
6.0%
별 2662
 
6.0%
특 2659
 
6.0%
동 2639
 
6.0%
호 2468
 
5.6%
Other values (292) 14452
32.8%
Latin
ValueCountFrequency (%)
B 28
16.6%
M 27
16.0%
D 26
15.4%
C 23
13.6%
A 23
13.6%
e 6
 
3.6%
K 4
 
2.4%
S 3
 
1.8%
E 3
 
1.8%
L 3
 
1.8%
Other values (17) 23
13.6%
Common
ValueCountFrequency (%)
14548
52.6%
1 2754
 
10.0%
2 1821
 
6.6%
3 1550
 
5.6%
4 1248
 
4.5%
0 1061
 
3.8%
5 1022
 
3.7%
7 851
 
3.1%
6 813
 
2.9%
9 767
 
2.8%
Other values (9) 1225
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44068
61.3%
ASCII 27829
38.7%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14548
52.3%
1 2754
 
9.9%
2 1821
 
6.5%
3 1550
 
5.6%
4 1248
 
4.5%
0 1061
 
3.8%
5 1022
 
3.7%
7 851
 
3.1%
6 813
 
2.9%
9 767
 
2.8%
Other values (36) 1394
 
5.0%
Hangul
ValueCountFrequency (%)
서 5375
 
12.2%
대 3016
 
6.8%
문 2729
 
6.2%
구 2729
 
6.2%
시 2675
 
6.1%
울 2665
 
6.0%
별 2662
 
6.0%
특 2659
 
6.0%
동 2639
 
6.0%
호 2468
 
5.6%
Other values (291) 14451
32.8%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%

도로명주소
Text

MISSING 

Distinct1761
Distinct (%)76.5%
Missing406
Missing (%)15.0%
Memory size21.3 KiB
2024-04-06T22:26:38.135787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length64
Mean length30.475901
Min length17

Characters and Unicode

Total characters70186
Distinct characters353
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

Unique1411 ?
Unique (%)61.3%

Sample

1st row서울특별시 서대문구 거북골로12길 18 (남가좌동)
2nd row서울특별시 서대문구 증가로24바길 71 (북가좌동)
3rd row서울특별시 서대문구 세검정로 61-22 (홍제동)
4th row서울특별시 서대문구 증가로10길 6 (남가좌동)
5th row서울특별시 서대문구 명지대3길 42-1 (남가좌동)
ValueCountFrequency (%)
서울특별시 2302
 
17.5%
서대문구 2288
 
17.4%
1층 411
 
3.1%
홍제동 307
 
2.3%
홍은동 295
 
2.2%
북가좌동 228
 
1.7%
남가좌동 227
 
1.7%
연희동 215
 
1.6%
통일로 190
 
1.4%
창천동 154
 
1.2%
Other values (1552) 6566
49.8%
2024-04-06T22:26:38.522114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10902
 
15.5%
서 4711
 
6.7%
1 2842
 
4.0%
대 2826
 
4.0%
문 2469
 
3.5%
동 2423
 
3.5%
( 2386
 
3.4%
) 2386
 
3.4%
울 2354
 
3.4%
시 2347
 
3.3%
Other values (343) 34540
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42917
61.1%
Space Separator 10902
 
15.5%
Decimal Number 9439
 
13.4%
Open Punctuation 2386
 
3.4%
Close Punctuation 2386
 
3.4%
Other Punctuation 1533
 
2.2%
Dash Punctuation 371
 
0.5%
Uppercase Letter 213
 
0.3%
Lowercase Letter 23
 
< 0.1%
Math Symbol 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 4711
 
11.0%
대 2826
 
6.6%
문 2469
 
5.8%
동 2423
 
5.6%
울 2354
 
5.5%
시 2347
 
5.5%
구 2343
 
5.5%
별 2304
 
5.4%
특 2302
 
5.4%
로 2089
 
4.9%
Other values (301) 16749
39.0%
Uppercase Letter
ValueCountFrequency (%)
B 61
28.6%
M 40
18.8%
D 38
17.8%
C 36
16.9%
A 17
 
8.0%
K 4
 
1.9%
S 3
 
1.4%
J 2
 
0.9%
T 2
 
0.9%
G 2
 
0.9%
Other values (7) 8
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 2842
30.1%
2 1248
13.2%
3 1109
 
11.7%
4 891
 
9.4%
0 841
 
8.9%
5 583
 
6.2%
7 532
 
5.6%
8 491
 
5.2%
9 453
 
4.8%
6 449
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
e 14
60.9%
m 3
 
13.0%
a 2
 
8.7%
r 1
 
4.3%
t 1
 
4.3%
w 1
 
4.3%
l 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 1519
99.1%
@ 12
 
0.8%
& 2
 
0.1%
Space Separator
ValueCountFrequency (%)
10902
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2386
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2386
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 371
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42917
61.1%
Common 27033
38.5%
Latin 236
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 4711
 
11.0%
대 2826
 
6.6%
문 2469
 
5.8%
동 2423
 
5.6%
울 2354
 
5.5%
시 2347
 
5.5%
구 2343
 
5.5%
별 2304
 
5.4%
특 2302
 
5.4%
로 2089
 
4.9%
Other values (301) 16749
39.0%
Latin
ValueCountFrequency (%)
B 61
25.8%
M 40
16.9%
D 38
16.1%
C 36
15.3%
A 17
 
7.2%
e 14
 
5.9%
K 4
 
1.7%
m 3
 
1.3%
S 3
 
1.3%
a 2
 
0.8%
Other values (14) 18
 
7.6%
Common
ValueCountFrequency (%)
10902
40.3%
1 2842
 
10.5%
( 2386
 
8.8%
) 2386
 
8.8%
, 1519
 
5.6%
2 1248
 
4.6%
3 1109
 
4.1%
4 891
 
3.3%
0 841
 
3.1%
5 583
 
2.2%
Other values (8) 2326
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42917
61.1%
ASCII 27269
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10902
40.0%
1 2842
 
10.4%
( 2386
 
8.7%
) 2386
 
8.7%
, 1519
 
5.6%
2 1248
 
4.6%
3 1109
 
4.1%
4 891
 
3.3%
0 841
 
3.1%
5 583
 
2.1%
Other values (32) 2562
 
9.4%
Hangul
ValueCountFrequency (%)
서 4711
 
11.0%
대 2826
 
6.6%
문 2469
 
5.8%
동 2423
 
5.6%
울 2354
 
5.5%
시 2347
 
5.5%
구 2343
 
5.5%
별 2304
 
5.4%
특 2302
 
5.4%
로 2089
 
4.9%
Other values (301) 16749
39.0%

도로명우편번호
Text

MISSING 

Distinct267
Distinct (%)29.0%
Missing1789
Missing (%)66.0%
Memory size21.3 KiB
2024-04-06T22:26:38.828426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4141304
Min length5

Characters and Unicode

Total characters4981
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

Unique83 ?
Unique (%)9.0%

Sample

1st row120857
2nd row120852
3rd row03614
4th row03737
5th row03718
ValueCountFrequency (%)
03766 24
 
2.6%
03709 20
 
2.2%
120180 19
 
2.1%
120110 19
 
2.1%
120857 13
 
1.4%
120160 13
 
1.4%
03711 13
 
1.4%
120170 12
 
1.3%
03665 11
 
1.2%
120013 11
 
1.2%
Other values (257) 765
83.2%
2024-04-06T22:26:39.272566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1292
25.9%
3 743
14.9%
1 692
13.9%
2 535
10.7%
7 503
 
10.1%
6 467
 
9.4%
8 300
 
6.0%
5 166
 
3.3%
4 135
 
2.7%
9 133
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4966
99.7%
Dash Punctuation 15
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1292
26.0%
3 743
15.0%
1 692
13.9%
2 535
10.8%
7 503
 
10.1%
6 467
 
9.4%
8 300
 
6.0%
5 166
 
3.3%
4 135
 
2.7%
9 133
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4981
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1292
25.9%
3 743
14.9%
1 692
13.9%
2 535
10.7%
7 503
 
10.1%
6 467
 
9.4%
8 300
 
6.0%
5 166
 
3.3%
4 135
 
2.7%
9 133
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4981
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1292
25.9%
3 743
14.9%
1 692
13.9%
2 535
10.7%
7 503
 
10.1%
6 467
 
9.4%
8 300
 
6.0%
5 166
 
3.3%
4 135
 
2.7%
9 133
 
2.7%

사업장명
Text

Distinct2019
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
2024-04-06T22:26:39.517847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length6.5068291
Min length1

Characters and Unicode

Total characters17627
Distinct characters569
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1672 ?
Unique (%)61.7%

Sample

1st row혜천상회
2nd row남양슈퍼
3rd row삼우식품
4th row진성유통할인매장
5th row친절상회
ValueCountFrequency (%)
씨유 123
 
3.6%
76
 
2.3%
gs25 74
 
2.2%
세븐일레븐 62
 
1.8%
이마트24 32
 
0.9%
주)코리아세븐 29
 
0.9%
훼미리마트 27
 
0.8%
지에스25 23
 
0.7%
미니스톱 22
 
0.7%
가로판매점 18
 
0.5%
Other values (2023) 2887
85.6%
2024-04-06T22:26:39.886099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 839
 
4.8%
667
 
3.8%
마 524
 
3.0%
트 505
 
2.9%
대 404
 
2.3%
퍼 402
 
2.3%
슈 359
 
2.0%
2 275
 
1.6%
이 262
 
1.5%
가 246
 
1.4%
Other values (559) 13144
74.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15060
85.4%
Uppercase Letter 672
 
3.8%
Space Separator 667
 
3.8%
Decimal Number 622
 
3.5%
Close Punctuation 203
 
1.2%
Open Punctuation 203
 
1.2%
Lowercase Letter 105
 
0.6%
Dash Punctuation 85
 
0.5%
Other Punctuation 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 839
 
5.6%
마 524
 
3.5%
트 505
 
3.4%
대 404
 
2.7%
퍼 402
 
2.7%
슈 359
 
2.4%
이 262
 
1.7%
가 246
 
1.6%
유 228
 
1.5%
리 208
 
1.4%
Other values (497) 11083
73.6%
Uppercase Letter
ValueCountFrequency (%)
G 185
27.5%
S 178
26.5%
C 72
 
10.7%
U 61
 
9.1%
M 26
 
3.9%
L 26
 
3.9%
A 17
 
2.5%
E 17
 
2.5%
D 14
 
2.1%
K 13
 
1.9%
Other values (13) 63
 
9.4%
Lowercase Letter
ValueCountFrequency (%)
e 20
19.0%
a 14
13.3%
r 9
 
8.6%
t 8
 
7.6%
s 6
 
5.7%
y 6
 
5.7%
u 5
 
4.8%
c 5
 
4.8%
o 5
 
4.8%
p 4
 
3.8%
Other values (10) 23
21.9%
Decimal Number
ValueCountFrequency (%)
2 275
44.2%
5 223
35.9%
4 47
 
7.6%
1 33
 
5.3%
3 18
 
2.9%
9 9
 
1.4%
6 6
 
1.0%
8 4
 
0.6%
0 4
 
0.6%
7 3
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 3
30.0%
? 2
20.0%
& 2
20.0%
: 2
20.0%
' 1
 
10.0%
Space Separator
ValueCountFrequency (%)
667
100.0%
Close Punctuation
ValueCountFrequency (%)
) 203
100.0%
Open Punctuation
ValueCountFrequency (%)
( 203
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15059
85.4%
Common 1790
 
10.2%
Latin 777
 
4.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 839
 
5.6%
마 524
 
3.5%
트 505
 
3.4%
대 404
 
2.7%
퍼 402
 
2.7%
슈 359
 
2.4%
이 262
 
1.7%
가 246
 
1.6%
유 228
 
1.5%
리 208
 
1.4%
Other values (496) 11082
73.6%
Latin
ValueCountFrequency (%)
G 185
23.8%
S 178
22.9%
C 72
 
9.3%
U 61
 
7.9%
M 26
 
3.3%
L 26
 
3.3%
e 20
 
2.6%
A 17
 
2.2%
E 17
 
2.2%
a 14
 
1.8%
Other values (33) 161
20.7%
Common
ValueCountFrequency (%)
667
37.3%
2 275
15.4%
5 223
 
12.5%
) 203
 
11.3%
( 203
 
11.3%
- 85
 
4.7%
4 47
 
2.6%
1 33
 
1.8%
3 18
 
1.0%
9 9
 
0.5%
Other values (9) 27
 
1.5%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15059
85.4%
ASCII 2567
 
14.6%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 839
 
5.6%
마 524
 
3.5%
트 505
 
3.4%
대 404
 
2.7%
퍼 402
 
2.7%
슈 359
 
2.4%
이 262
 
1.7%
가 246
 
1.6%
유 228
 
1.5%
리 208
 
1.4%
Other values (496) 11082
73.6%
ASCII
ValueCountFrequency (%)
667
26.0%
2 275
10.7%
5 223
 
8.7%
) 203
 
7.9%
( 203
 
7.9%
G 185
 
7.2%
S 178
 
6.9%
- 85
 
3.3%
C 72
 
2.8%
U 61
 
2.4%
Other values (52) 415
16.2%
CJK
ValueCountFrequency (%)
家 1
100.0%

최종수정일자
Date

Distinct1988
Distinct (%)73.4%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
Minimum2007-07-30 14:06:49
Maximum2024-04-04 10:25:58
2024-04-06T22:26:40.021316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:26:40.149391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
I
1982 
U
727 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1982
73.2%
U 727
 
26.8%

Length

2024-04-06T22:26:40.270470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:26:40.358377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1982
73.2%
u 727
 
26.8%

데이터갱신일자
Date

Distinct473
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-06T22:26:40.455963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:26:40.583200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2709
Missing (%)100.0%
Memory size23.9 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1201
Distinct (%)49.0%
Missing260
Missing (%)9.6%
Infinite0
Infinite (%)0.0%
Mean194434.96
Minimum171116.46
Maximum197170.64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.9 KiB
2024-04-06T22:26:40.713678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum171116.46
5-th percentile192190.96
Q1193369.32
median194547.32
Q3195380.97
95-th percentile196723.15
Maximum197170.64
Range26054.187
Interquartile range (IQR)2011.6473

Descriptive statistics

Standard deviation1447.7675
Coefficient of variation (CV)0.0074460244
Kurtosis26.295951
Mean194434.96
Median Absolute Deviation (MAD)950.60583
Skewness-1.7887864
Sum4.7617122 × 108
Variance2096030.7
MonotonicityNot monotonic
2024-04-06T22:26:40.842489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196058.441601385 15
 
0.6%
195259.429272709 12
 
0.4%
195332.123380254 12
 
0.4%
192672.067512964 11
 
0.4%
195628.369464108 10
 
0.4%
196397.574633596 10
 
0.4%
195057.033841623 10
 
0.4%
194199.400403698 10
 
0.4%
193802.960706954 9
 
0.3%
195477.913016234 8
 
0.3%
Other values (1191) 2342
86.5%
(Missing) 260
 
9.6%
ValueCountFrequency (%)
171116.455620765 1
 
< 0.1%
191497.867040904 3
0.1%
191519.132033814 3
0.1%
191559.918118738 6
0.2%
191562.593519562 3
0.1%
191570.192406712 1
 
< 0.1%
191572.384552653 5
0.2%
191685.357900856 5
0.2%
191686.781357428 2
 
0.1%
191693.433664168 1
 
< 0.1%
ValueCountFrequency (%)
197170.642282034 1
 
< 0.1%
197147.394631349 4
0.1%
197144.015440398 3
0.1%
197121.041523674 2
0.1%
197088.194167189 2
0.1%
197073.021981074 1
 
< 0.1%
197064.31975275 2
0.1%
197063.168570815 2
0.1%
197062.989911966 2
0.1%
197062.406516 4
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1201
Distinct (%)49.0%
Missing260
Missing (%)9.6%
Infinite0
Infinite (%)0.0%
Mean452485.86
Minimum448751.76
Maximum455906.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.9 KiB
2024-04-06T22:26:40.962789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448751.76
5-th percentile450556.56
Q1451178.26
median452563.2
Q3453534.25
95-th percentile454922.33
Maximum455906.2
Range7154.4341
Interquartile range (IQR)2355.9929

Descriptive statistics

Standard deviation1414.0074
Coefficient of variation (CV)0.0031249759
Kurtosis-1.0191664
Mean452485.86
Median Absolute Deviation (MAD)1171.965
Skewness0.22070935
Sum1.1081379 × 109
Variance1999416.9
MonotonicityNot monotonic
2024-04-06T22:26:41.090673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452437.094345339 15
 
0.6%
450806.05844472 12
 
0.4%
453430.811542203 12
 
0.4%
452221.960661496 11
 
0.4%
454188.806319642 10
 
0.4%
452896.433148713 10
 
0.4%
451592.270982609 10
 
0.4%
454786.019433577 10
 
0.4%
451983.122239876 9
 
0.3%
453112.958663193 8
 
0.3%
Other values (1191) 2342
86.5%
(Missing) 260
 
9.6%
ValueCountFrequency (%)
448751.763383712 1
< 0.1%
450368.587119035 1
< 0.1%
450375.488731434 2
0.1%
450383.390516588 1
< 0.1%
450390.671043197 1
< 0.1%
450391.53849739 1
< 0.1%
450400.988332214 2
0.1%
450414.724902658 2
0.1%
450415.027420458 1
< 0.1%
450420.161910322 2
0.1%
ValueCountFrequency (%)
455906.197498826 2
 
0.1%
455887.371968749 1
 
< 0.1%
455735.363417848 1
 
< 0.1%
455710.429910779 5
0.2%
455616.624014493 1
 
< 0.1%
455607.551464324 1
 
< 0.1%
455588.317096857 3
0.1%
455559.768052914 1
 
< 0.1%
455510.056361032 1
 
< 0.1%
455475.893749799 2
 
0.1%

지정일자
Real number (ℝ)

MISSING 

Distinct1265
Distinct (%)74.7%
Missing1016
Missing (%)37.5%
Infinite0
Infinite (%)0.0%
Mean20073034
Minimum19000101
Maximum20220321
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.9 KiB
2024-04-06T22:26:41.220805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19000101
5-th percentile19950524
Q120011228
median20080714
Q320140108
95-th percentile20191007
Maximum20220321
Range1220220
Interquartile range (IQR)128880

Descriptive statistics

Standard deviation88792.281
Coefficient of variation (CV)0.004423461
Kurtosis36.394229
Mean20073034
Median Absolute Deviation (MAD)59995
Skewness-3.2842605
Sum3.3983646 × 1010
Variance7.8840692 × 109
MonotonicityNot monotonic
2024-04-06T22:26:41.681100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19981229 12
 
0.4%
20010101 11
 
0.4%
19981219 10
 
0.4%
19981221 8
 
0.3%
19981207 7
 
0.3%
19900101 7
 
0.3%
19981231 6
 
0.2%
19981216 5
 
0.2%
20080827 5
 
0.2%
20140602 5
 
0.2%
Other values (1255) 1617
59.7%
(Missing) 1016
37.5%
ValueCountFrequency (%)
19000101 3
0.1%
19800701 3
0.1%
19810804 1
 
< 0.1%
19830720 1
 
< 0.1%
19830820 1
 
< 0.1%
19850531 1
 
< 0.1%
19860424 1
 
< 0.1%
19861223 1
 
< 0.1%
19871211 1
 
< 0.1%
19890101 2
0.1%
ValueCountFrequency (%)
20220321 1
< 0.1%
20220221 1
< 0.1%
20220121 1
< 0.1%
20220117 1
< 0.1%
20211231 1
< 0.1%
20211223 1
< 0.1%
20211217 1
< 0.1%
20211209 1
< 0.1%
20211129 1
< 0.1%
20211117 1
< 0.1%

민원종류명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
<NA>
1016 
2009년11월법개정전자료
958 
제7조의3제2항에따른경우
663 
제7조의3제3항에따른경우
 
72

Length

Max length14
Median length13
Mean length9.9782207
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2009년11월법개정전자료
2nd row2009년11월법개정전자료
3rd row2009년11월법개정전자료
4th row2009년11월법개정전자료
5th row제7조의3제2항에따른경우

Common Values

ValueCountFrequency (%)
<NA> 1016
37.5%
2009년11월법개정전자료 958
35.4%
제7조의3제2항에따른경우 663
24.5%
제7조의3제3항에따른경우 72
 
2.7%

Length

2024-04-06T22:26:41.827690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:26:41.947371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1016
37.5%
2009년11월법개정전자료 958
35.4%
제7조의3제2항에따른경우 663
24.5%
제7조의3제3항에따른경우 72
 
2.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자민원종류명
0312000031200930560069519941210<NA>3폐업2폐업처리200412102004070120040730<NA>02 3728763<NA><NA>서울특별시 서대문구 남가좌동 171번지 2호서울특별시 서대문구 거북골로12길 18 (남가좌동)<NA>혜천상회2019-09-23 16:13:35U2019-09-25 02:40:00.0<NA>192626.482692452588.74544199412102009년11월법개정전자료
1312000031201190560075920091119<NA>3폐업2폐업처리20091119<NA><NA><NA><NA><NA>120121서울특별시 서대문구 남가좌1동 155번지 209호<NA><NA>남양슈퍼2009-11-19 15:52:34I2018-08-31 23:59:59.0<NA><NA><NA>200911192009년11월법개정전자료
2312000031201190560095419900101<NA>3폐업2폐업처리20080826<NA><NA><NA><NA><NA>120130서울특별시 서대문구 북가좌동 126번지 3호<NA><NA>삼우식품2008-08-26 11:22:39I2018-08-31 23:59:59.0<NA><NA><NA>199001012009년11월법개정전자료
3312000031201190560147420090511200905074취소/말소/만료/정지/중지3직권취소<NA><NA><NA><NA><NA><NA>120132서울특별시 서대문구 북가좌2동 3번지 40호서울특별시 서대문구 증가로24바길 71 (북가좌동)<NA>진성유통할인매장2009-05-11 15:17:43I2018-08-31 23:59:59.0<NA>192804.548667453432.251936200905112009년11월법개정전자료
4312000031201450560000019900101<NA>3폐업2폐업처리20121015<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 세검정로 61-22 (홍제동)120857친절상회2012-10-15 16:51:33I2018-08-31 23:59:59.0<NA>195218.183024454495.14029319900101제7조의3제2항에따른경우
5312000031201450560089420000131<NA>3폐업2폐업처리20160405<NA><NA><NA>372-8420<NA>120807서울특별시 서대문구 남가좌2동 341번지 9호서울특별시 서대문구 증가로10길 6 (남가좌동)<NA>기쁨주는 반찬가게2016-04-05 16:07:04I2018-08-31 23:59:59.0<NA>193154.300895452834.506364200001312009년11월법개정전자료
631200008431200750560072520000721<NA>3폐업2폐업처리20011029<NA><NA><NA>02 3724120<NA><NA>서울특별시 서대문구 남가좌동 5번지 74호서울특별시 서대문구 명지대3길 42-1 (남가좌동)<NA>빙그레슈퍼2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>192980.419124453297.284652<NA><NA>
731200008431200750560148620001103<NA>3폐업2폐업처리20011030<NA><NA><NA>02 3957609<NA><NA>서울특별시 서대문구 홍은동 48번지 80호서울특별시 서대문구 세검정로1길 98 (홍은동)<NA>훼미리마트2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>195173.480512454692.683753<NA><NA>
8312000023931201070561607419971104200711134취소/말소/만료/정지/중지5지정취소<NA><NA><NA><NA>391-6074<NA>120090서울특별시 서대문구 홍제동 267번지 48호서울특별시 서대문구 세무서8길 21 (홍제동)<NA>한솔마트2019-09-24 16:16:31U2019-09-26 02:40:00.0<NA>195333.49723454261.463018199711042009년11월법개정전자료
93120000198031201190560100519800701<NA>3폐업2폐업처리20091112<NA><NA><NA><NA><NA>120101서울특별시 서대문구 홍은1동 9번지 343호서울특별시 서대문구 홍은중앙로9길 1 (홍은동)<NA>현대인테리아2009-11-12 15:41:30I2018-08-31 23:59:59.0<NA>195334.5473455231.168466198007012009년11월법개정전자료
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자민원종류명
2699312000020243120219056000032024-02-06<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 냉천동 40-1서울특별시 서대문구 독립문로14길 8, 1층 (냉천동)03745씨유 서대문센트레빌점2024-02-06 12:44:03I2023-12-02 00:08:00.0<NA>196715.080209451647.000739<NA><NA>
2700312000020243120219056000042024-02-07<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 남가좌동 385 DMC파크뷰자이서울특별시 서대문구 가재울미래로 2, 상가203동 101호 (남가좌동, DMC파크뷰자이)03711지에스25 DMC가재울점2024-02-07 10:19:00I2023-12-01 23:01:00.0<NA>192672.067513452221.960661<NA><NA>
2701312000020243120219056000052024-02-16<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 연희동 122-7 (주)나임하우스서울특별시 서대문구 증가로 21-1, (주)나임하우스 1층 (연희동)03703지에스25 연희점2024-02-16 10:47:02I2023-12-01 23:08:00.0<NA>193802.960707451983.12224<NA><NA>
2702312000020243120219056000062024-02-22<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 대현동 144 신촌럭키아파트서울특별시 서대문구 이화여대길 50-12, 상가동 1층 101호 (대현동, 신촌럭키아파트)03764지에스 더프레시 신촌이대역점2024-02-22 13:01:14I2023-12-01 22:04:00.0<NA>195332.12338450806.058445<NA><NA>
2703312000020243120219056000072024-02-23<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 북가좌동 329-8서울특별시 서대문구 증가로 243, 1층 (북가좌동)03678씨유 서대문센터점2024-02-23 13:13:05I2023-12-01 22:05:00.0<NA>192208.019965453383.290789<NA><NA>
2704312000020243120219056000082024-02-23<NA>1영업/정상0정상영업<NA><NA><NA><NA>02-313-6279<NA><NA>서울특별시 서대문구 북아현동 1011 신촌푸르지오서울특별시 서대문구 북아현로1길 50, 상가2동 212호 (북아현동, 신촌푸르지오)03770초록마을 북아현점2024-02-24 08:55:03I2023-12-01 22:06:00.0<NA>195698.78128450882.103643<NA><NA>
2705312000020243120219056000092024-02-27<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 남가좌동 50-3 명지대학교서울특별시 서대문구 거북골로 34, 명지대학교(학생회관) 3층 (남가좌동)03674이마트24 명지대학생회관점2024-02-27 17:39:26I2023-12-01 22:09:00.0<NA>193139.523944453106.002592<NA><NA>
2706312000020243120219056000102024-03-05<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 홍제동 172-11서울특별시 서대문구 통일로37길 3 (홍제동)03646세븐일레븐 홍제동일점2024-03-13 13:02:55U2023-12-02 23:05:00.0<NA>195041.810063453960.704932<NA><NA>
2707312000020243120219056000112024-03-07<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 연희동 165-14서울특별시 서대문구 연희로36길 10, 101,102호 (연희동)03718지에스25 서대문구청점2024-04-02 14:43:38U2023-12-04 00:04:00.0<NA>194337.001304452923.136705<NA><NA>
2708312000020243120219056000122024-04-03<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 창천동 46-12 우석빌딩서울특별시 서대문구 연세로12길 20, 우석빌딩 1층 (창천동)03776지에스25 신촌창천점2024-04-03 17:55:07I2023-12-04 00:05:00.0<NA>194463.414639450737.013392<NA><NA>