Overview

Dataset statistics

Number of variables44
Number of observations313
Missing cells3047
Missing cells (%)22.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory114.8 KiB
Average record size in memory375.4 B

Variable types

Categorical19
Text7
DateTime4
Unsupported7
Numeric6
Boolean1

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),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-18021/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (55.5%)Imbalance
영업장주변구분명 is highly imbalanced (59.5%)Imbalance
총인원 is highly imbalanced (72.2%)Imbalance
공장사무직종업원수 is highly imbalanced (72.2%)Imbalance
공장판매직종업원수 is highly imbalanced (72.2%)Imbalance
공장생산직종업원수 is highly imbalanced (72.2%)Imbalance
건물소유구분명 is highly imbalanced (90.3%)Imbalance
인허가취소일자 has 313 (100.0%) missing valuesMissing
폐업일자 has 192 (61.3%) missing valuesMissing
휴업시작일자 has 313 (100.0%) missing valuesMissing
휴업종료일자 has 313 (100.0%) missing valuesMissing
재개업일자 has 313 (100.0%) missing valuesMissing
전화번호 has 27 (8.6%) missing valuesMissing
소재지면적 has 10 (3.2%) missing valuesMissing
소재지우편번호 has 4 (1.3%) missing valuesMissing
지번주소 has 4 (1.3%) missing valuesMissing
도로명주소 has 46 (14.7%) missing valuesMissing
도로명우편번호 has 49 (15.7%) missing valuesMissing
좌표정보(X) has 10 (3.2%) missing valuesMissing
좌표정보(Y) has 10 (3.2%) missing valuesMissing
여성종사자수 has 230 (73.5%) missing valuesMissing
본사종업원수 has 142 (45.4%) missing valuesMissing
다중이용업소여부 has 66 (21.1%) missing valuesMissing
시설총규모 has 66 (21.1%) missing valuesMissing
전통업소지정번호 has 313 (100.0%) missing valuesMissing
전통업소주된음식 has 313 (100.0%) missing valuesMissing
홈페이지 has 313 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
여성종사자수 has 68 (21.7%) zerosZeros
본사종업원수 has 149 (47.6%) zerosZeros
시설총규모 has 18 (5.8%) zerosZeros

Reproduction

Analysis started2024-05-11 08:22:32.319276
Analysis finished2024-05-11 08:22:33.186341
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
3190000
313 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 313
100.0%

Length

2024-05-11T17:22:33.236968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:33.323237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 313
100.0%

관리번호
Text

UNIQUE 

Distinct313
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-11T17:22:33.481075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6886
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

Unique313 ?
Unique (%)100.0%

Sample

1st row3190000-105-1980-00009
2nd row3190000-105-1981-00007
3rd row3190000-105-1981-00008
4th row3190000-105-1985-00011
5th row3190000-105-1985-00014
ValueCountFrequency (%)
3190000-105-1980-00009 1
 
0.3%
3190000-105-2010-00002 1
 
0.3%
3190000-105-2011-00004 1
 
0.3%
3190000-105-2011-00003 1
 
0.3%
3190000-105-2011-00002 1
 
0.3%
3190000-105-2011-00001 1
 
0.3%
3190000-105-2010-00005 1
 
0.3%
3190000-105-2010-00004 1
 
0.3%
3190000-105-2011-00010 1
 
0.3%
3190000-105-2010-00001 1
 
0.3%
Other values (303) 303
96.8%
2024-05-11T17:22:33.788141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3089
44.9%
- 939
 
13.6%
1 899
 
13.1%
9 493
 
7.2%
5 453
 
6.6%
3 411
 
6.0%
2 359
 
5.2%
4 75
 
1.1%
6 60
 
0.9%
8 58
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5947
86.4%
Dash Punctuation 939
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3089
51.9%
1 899
 
15.1%
9 493
 
8.3%
5 453
 
7.6%
3 411
 
6.9%
2 359
 
6.0%
4 75
 
1.3%
6 60
 
1.0%
8 58
 
1.0%
7 50
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 939
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6886
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3089
44.9%
- 939
 
13.6%
1 899
 
13.1%
9 493
 
7.2%
5 453
 
6.6%
3 411
 
6.0%
2 359
 
5.2%
4 75
 
1.1%
6 60
 
0.9%
8 58
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3089
44.9%
- 939
 
13.6%
1 899
 
13.1%
9 493
 
7.2%
5 453
 
6.6%
3 411
 
6.0%
2 359
 
5.2%
4 75
 
1.1%
6 60
 
0.9%
8 58
 
0.8%
Distinct258
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum1980-04-01 00:00:00
Maximum2024-04-04 00:00:00
2024-05-11T17:22:33.928230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:22:34.057740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
1
192 
3
121 

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 (%)
1 192
61.3%
3 121
38.7%

Length

2024-05-11T17:22:34.186065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:34.268758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 192
61.3%
3 121
38.7%

영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
영업/정상
192 
폐업
121 

Length

Max length5
Median length5
Mean length3.8402556
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 192
61.3%
폐업 121
38.7%

Length

2024-05-11T17:22:34.358831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:34.464249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 192
61.3%
폐업 121
38.7%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
1
192 
2
121 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 192
61.3%
2 121
38.7%

Length

2024-05-11T17:22:34.561864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:34.648705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 192
61.3%
2 121
38.7%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
영업
192 
폐업
121 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 192
61.3%
폐업 121
38.7%

Length

2024-05-11T17:22:34.737900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:34.824255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 192
61.3%
폐업 121
38.7%

폐업일자
Date

MISSING 

Distinct107
Distinct (%)88.4%
Missing192
Missing (%)61.3%
Memory size2.6 KiB
Minimum1995-04-27 00:00:00
Maximum2024-02-22 00:00:00
2024-05-11T17:22:34.926979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:22:35.051428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB

전화번호
Text

MISSING 

Distinct278
Distinct (%)97.2%
Missing27
Missing (%)8.6%
Memory size2.6 KiB
2024-05-11T17:22:35.313853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.199301
Min length7

Characters and Unicode

Total characters2917
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

Unique270 ?
Unique (%)94.4%

Sample

1st row02 8143921
2nd row02 5996141
3rd row02 5376107
4th row02 8121927
5th row02 8327641
ValueCountFrequency (%)
02 211
37.3%
812 5
 
0.9%
815 4
 
0.7%
02822 3
 
0.5%
822 3
 
0.5%
821 3
 
0.5%
817 2
 
0.4%
823 2
 
0.4%
825 2
 
0.4%
826 2
 
0.4%
Other values (313) 328
58.1%
2024-05-11T17:22:35.675593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 540
18.5%
0 463
15.9%
343
11.8%
8 334
11.5%
1 246
8.4%
5 202
 
6.9%
3 195
 
6.7%
4 179
 
6.1%
7 161
 
5.5%
6 146
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2574
88.2%
Space Separator 343
 
11.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 540
21.0%
0 463
18.0%
8 334
13.0%
1 246
9.6%
5 202
 
7.8%
3 195
 
7.6%
4 179
 
7.0%
7 161
 
6.3%
6 146
 
5.7%
9 108
 
4.2%
Space Separator
ValueCountFrequency (%)
343
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2917
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 540
18.5%
0 463
15.9%
343
11.8%
8 334
11.5%
1 246
8.4%
5 202
 
6.9%
3 195
 
6.7%
4 179
 
6.1%
7 161
 
5.5%
6 146
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2917
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 540
18.5%
0 463
15.9%
343
11.8%
8 334
11.5%
1 246
8.4%
5 202
 
6.9%
3 195
 
6.7%
4 179
 
6.1%
7 161
 
5.5%
6 146
 
5.0%

소재지면적
Text

MISSING 

Distinct259
Distinct (%)85.5%
Missing10
Missing (%)3.2%
Memory size2.6 KiB
2024-05-11T17:22:36.007926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0330033
Min length3

Characters and Unicode

Total characters1525
Distinct characters12
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

Unique239 ?
Unique (%)78.9%

Sample

1st row41.20
2nd row60.00
3rd row30.96
4th row36.00
5th row40.00
ValueCountFrequency (%)
00 14
 
4.6%
0.00 8
 
2.6%
12.90 5
 
1.7%
180.00 3
 
1.0%
26.40 3
 
1.0%
9.90 3
 
1.0%
100.00 2
 
0.7%
10.50 2
 
0.7%
77.64 2
 
0.7%
10.00 2
 
0.7%
Other values (249) 259
85.5%
2024-05-11T17:22:36.486114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 303
19.9%
0 277
18.2%
1 201
13.2%
2 106
 
7.0%
6 100
 
6.6%
5 100
 
6.6%
9 97
 
6.4%
4 97
 
6.4%
8 90
 
5.9%
3 86
 
5.6%
Other values (2) 68
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1220
80.0%
Other Punctuation 305
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 277
22.7%
1 201
16.5%
2 106
 
8.7%
6 100
 
8.2%
5 100
 
8.2%
9 97
 
8.0%
4 97
 
8.0%
8 90
 
7.4%
3 86
 
7.0%
7 66
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 303
99.3%
, 2
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1525
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 303
19.9%
0 277
18.2%
1 201
13.2%
2 106
 
7.0%
6 100
 
6.6%
5 100
 
6.6%
9 97
 
6.4%
4 97
 
6.4%
8 90
 
5.9%
3 86
 
5.6%
Other values (2) 68
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1525
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 303
19.9%
0 277
18.2%
1 201
13.2%
2 106
 
7.0%
6 100
 
6.6%
5 100
 
6.6%
9 97
 
6.4%
4 97
 
6.4%
8 90
 
5.9%
3 86
 
5.6%
Other values (2) 68
 
4.5%

소재지우편번호
Text

MISSING 

Distinct100
Distinct (%)32.4%
Missing4
Missing (%)1.3%
Memory size2.6 KiB
2024-05-11T17:22:36.753898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1488673
Min length6

Characters and Unicode

Total characters1900
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

Unique37 ?
Unique (%)12.0%

Sample

1st row156810
2nd row156814
3rd row156090
4th row156808
5th row156854
ValueCountFrequency (%)
156030 26
 
8.4%
156849 15
 
4.9%
156861 12
 
3.9%
156807 11
 
3.6%
156800 9
 
2.9%
156811 8
 
2.6%
156090 8
 
2.6%
156840 7
 
2.3%
156830 6
 
1.9%
156080 6
 
1.9%
Other values (90) 201
65.0%
2024-05-11T17:22:37.100856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 384
20.2%
5 361
19.0%
6 346
18.2%
8 270
14.2%
0 194
10.2%
3 77
 
4.1%
4 71
 
3.7%
7 53
 
2.8%
2 50
 
2.6%
9 48
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1854
97.6%
Dash Punctuation 46
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 384
20.7%
5 361
19.5%
6 346
18.7%
8 270
14.6%
0 194
10.5%
3 77
 
4.2%
4 71
 
3.8%
7 53
 
2.9%
2 50
 
2.7%
9 48
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1900
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 384
20.2%
5 361
19.0%
6 346
18.2%
8 270
14.2%
0 194
10.2%
3 77
 
4.1%
4 71
 
3.7%
7 53
 
2.8%
2 50
 
2.6%
9 48
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 384
20.2%
5 361
19.0%
6 346
18.2%
8 270
14.2%
0 194
10.2%
3 77
 
4.1%
4 71
 
3.7%
7 53
 
2.8%
2 50
 
2.6%
9 48
 
2.5%

지번주소
Text

MISSING 

Distinct290
Distinct (%)93.9%
Missing4
Missing (%)1.3%
Memory size2.6 KiB
2024-05-11T17:22:37.337095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length23.605178
Min length17

Characters and Unicode

Total characters7294
Distinct characters162
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique275 ?
Unique (%)89.0%

Sample

1st row서울특별시 동작구 대방동 390-5번지
2nd row서울특별시 동작구 사당동 68-2
3rd row서울특별시 동작구 사당동 산 31-3번지
4th row서울특별시 동작구 대방동 345-1번지
5th row서울특별시 동작구 신대방동 656-9번지
ValueCountFrequency (%)
서울특별시 309
22.5%
동작구 309
22.5%
상도동 73
 
5.3%
사당동 58
 
4.2%
신대방동 54
 
3.9%
흑석동 39
 
2.8%
대방동 36
 
2.6%
노량진동 26
 
1.9%
1층 19
 
1.4%
상도1동 10
 
0.7%
Other values (353) 440
32.0%
2024-05-11T17:22:37.688572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1306
17.9%
643
 
8.8%
319
 
4.4%
317
 
4.3%
1 317
 
4.3%
317
 
4.3%
314
 
4.3%
311
 
4.3%
310
 
4.3%
310
 
4.3%
Other values (152) 2830
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4340
59.5%
Decimal Number 1375
 
18.9%
Space Separator 1306
 
17.9%
Dash Punctuation 254
 
3.5%
Lowercase Letter 7
 
0.1%
Other Punctuation 5
 
0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
643
14.8%
319
 
7.4%
317
 
7.3%
317
 
7.3%
314
 
7.2%
311
 
7.2%
310
 
7.1%
310
 
7.1%
198
 
4.6%
179
 
4.1%
Other values (130) 1122
25.9%
Decimal Number
ValueCountFrequency (%)
1 317
23.1%
2 205
14.9%
3 173
12.6%
4 129
9.4%
0 129
9.4%
5 107
 
7.8%
6 101
 
7.3%
9 79
 
5.7%
8 68
 
4.9%
7 67
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
l 2
28.6%
e 1
14.3%
i 1
14.3%
s 1
14.3%
h 1
14.3%
v 1
14.3%
Space Separator
ValueCountFrequency (%)
1306
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 254
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4340
59.5%
Common 2946
40.4%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
643
14.8%
319
 
7.4%
317
 
7.3%
317
 
7.3%
314
 
7.2%
311
 
7.2%
310
 
7.1%
310
 
7.1%
198
 
4.6%
179
 
4.1%
Other values (130) 1122
25.9%
Common
ValueCountFrequency (%)
1306
44.3%
1 317
 
10.8%
- 254
 
8.6%
2 205
 
7.0%
3 173
 
5.9%
4 129
 
4.4%
0 129
 
4.4%
5 107
 
3.6%
6 101
 
3.4%
9 79
 
2.7%
Other values (5) 146
 
5.0%
Latin
ValueCountFrequency (%)
l 2
25.0%
e 1
12.5%
B 1
12.5%
i 1
12.5%
s 1
12.5%
h 1
12.5%
v 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4340
59.5%
ASCII 2954
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1306
44.2%
1 317
 
10.7%
- 254
 
8.6%
2 205
 
6.9%
3 173
 
5.9%
4 129
 
4.4%
0 129
 
4.4%
5 107
 
3.6%
6 101
 
3.4%
9 79
 
2.7%
Other values (12) 154
 
5.2%
Hangul
ValueCountFrequency (%)
643
14.8%
319
 
7.4%
317
 
7.3%
317
 
7.3%
314
 
7.2%
311
 
7.2%
310
 
7.1%
310
 
7.1%
198
 
4.6%
179
 
4.1%
Other values (130) 1122
25.9%

도로명주소
Text

MISSING 

Distinct249
Distinct (%)93.3%
Missing46
Missing (%)14.7%
Memory size2.6 KiB
2024-05-11T17:22:37.972296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length43
Mean length28.434457
Min length21

Characters and Unicode

Total characters7592
Distinct characters175
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique233 ?
Unique (%)87.3%

Sample

1st row서울특별시 동작구 동작대로35길 43 (사당동)
2nd row서울특별시 동작구 양녕로30길 19-4, 서울삼성농아원 (상도동)
3rd row서울특별시 동작구 노량진로 74 (대방동,유한양행빌딩 지하2층)
4th row서울특별시 동작구 시흥대로 670 (신대방동)
5th row서울특별시 동작구 여의대방로20나길 40, 서울시립남부장애인종합복지관 (신대방동)
ValueCountFrequency (%)
서울특별시 267
 
18.2%
동작구 267
 
18.2%
상도동 62
 
4.2%
사당동 52
 
3.5%
신대방동 39
 
2.7%
흑석동 33
 
2.2%
대방동 29
 
2.0%
1층 22
 
1.5%
노량진동 20
 
1.4%
관리동 11
 
0.7%
Other values (357) 668
45.4%
2024-05-11T17:22:38.455428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1203
 
15.8%
594
 
7.8%
298
 
3.9%
286
 
3.8%
275
 
3.6%
274
 
3.6%
271
 
3.6%
( 269
 
3.5%
) 269
 
3.5%
268
 
3.5%
Other values (165) 3585
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4722
62.2%
Space Separator 1203
 
15.8%
Decimal Number 987
 
13.0%
Open Punctuation 269
 
3.5%
Close Punctuation 269
 
3.5%
Other Punctuation 111
 
1.5%
Dash Punctuation 23
 
0.3%
Lowercase Letter 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
594
 
12.6%
298
 
6.3%
286
 
6.1%
275
 
5.8%
274
 
5.8%
271
 
5.7%
268
 
5.7%
268
 
5.7%
247
 
5.2%
176
 
3.7%
Other values (143) 1765
37.4%
Decimal Number
ValueCountFrequency (%)
1 240
24.3%
2 161
16.3%
4 110
11.1%
3 106
10.7%
6 83
 
8.4%
5 68
 
6.9%
0 62
 
6.3%
7 61
 
6.2%
9 54
 
5.5%
8 42
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
l 2
25.0%
s 1
12.5%
h 1
12.5%
v 1
12.5%
i 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 110
99.1%
. 1
 
0.9%
Space Separator
ValueCountFrequency (%)
1203
100.0%
Open Punctuation
ValueCountFrequency (%)
( 269
100.0%
Close Punctuation
ValueCountFrequency (%)
) 269
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4722
62.2%
Common 2862
37.7%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
594
 
12.6%
298
 
6.3%
286
 
6.1%
275
 
5.8%
274
 
5.8%
271
 
5.7%
268
 
5.7%
268
 
5.7%
247
 
5.2%
176
 
3.7%
Other values (143) 1765
37.4%
Common
ValueCountFrequency (%)
1203
42.0%
( 269
 
9.4%
) 269
 
9.4%
1 240
 
8.4%
2 161
 
5.6%
, 110
 
3.8%
4 110
 
3.8%
3 106
 
3.7%
6 83
 
2.9%
5 68
 
2.4%
Other values (6) 243
 
8.5%
Latin
ValueCountFrequency (%)
e 2
25.0%
l 2
25.0%
s 1
12.5%
h 1
12.5%
v 1
12.5%
i 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4722
62.2%
ASCII 2870
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1203
41.9%
( 269
 
9.4%
) 269
 
9.4%
1 240
 
8.4%
2 161
 
5.6%
, 110
 
3.8%
4 110
 
3.8%
3 106
 
3.7%
6 83
 
2.9%
5 68
 
2.4%
Other values (12) 251
 
8.7%
Hangul
ValueCountFrequency (%)
594
 
12.6%
298
 
6.3%
286
 
6.1%
275
 
5.8%
274
 
5.8%
271
 
5.7%
268
 
5.7%
268
 
5.7%
247
 
5.2%
176
 
3.7%
Other values (143) 1765
37.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct128
Distinct (%)48.5%
Missing49
Missing (%)15.7%
Infinite0
Infinite (%)0.0%
Mean6988.7576
Minimum6900
Maximum7075
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:22:38.578720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6900
5-th percentile6909.15
Q16947.5
median6981
Q37033.25
95-th percentile7066
Maximum7075
Range175
Interquartile range (IQR)85.75

Descriptive statistics

Standard deviation51.688762
Coefficient of variation (CV)0.0073959872
Kurtosis-1.2030189
Mean6988.7576
Median Absolute Deviation (MAD)44
Skewness0.03323463
Sum1845032
Variance2671.7281
MonotonicityNot monotonic
2024-05-11T17:22:38.706599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7062 10
 
3.2%
6974 7
 
2.2%
6973 6
 
1.9%
6968 5
 
1.6%
7043 5
 
1.6%
7055 5
 
1.6%
6978 5
 
1.6%
6942 5
 
1.6%
7013 4
 
1.3%
6961 4
 
1.3%
Other values (118) 208
66.5%
(Missing) 49
 
15.7%
ValueCountFrequency (%)
6900 1
 
0.3%
6901 1
 
0.3%
6902 2
0.6%
6904 3
1.0%
6905 1
 
0.3%
6907 1
 
0.3%
6908 3
1.0%
6909 2
0.6%
6910 4
1.3%
6911 1
 
0.3%
ValueCountFrequency (%)
7075 1
 
0.3%
7074 2
0.6%
7073 1
 
0.3%
7072 2
0.6%
7071 2
0.6%
7069 1
 
0.3%
7068 3
1.0%
7067 1
 
0.3%
7066 3
1.0%
7065 2
0.6%
Distinct298
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-11T17:22:38.958080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length8.0702875
Min length2

Characters and Unicode

Total characters2526
Distinct characters305
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique283 ?
Unique (%)90.4%

Sample

1st row서울기계공고
2nd row건영섬유구내식당
3rd row총신대기숙사
4th row시립부녀보호소
5th row태평양화학서울센터
ValueCountFrequency (%)
어린이집 11
 
3.0%
중앙대학교 9
 
2.4%
구립 5
 
1.4%
숭실대학교 4
 
1.1%
주식회사 3
 
0.8%
영석어린이집 2
 
0.5%
상도복지관어린이집 2
 
0.5%
유치원 2
 
0.5%
강남유치원 2
 
0.5%
송림유치원 2
 
0.5%
Other values (313) 326
88.6%
2024-05-11T17:22:39.333999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
140
 
5.5%
126
 
5.0%
124
 
4.9%
123
 
4.9%
83
 
3.3%
72
 
2.9%
67
 
2.7%
63
 
2.5%
55
 
2.2%
52
 
2.1%
Other values (295) 1621
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2390
94.6%
Space Separator 55
 
2.2%
Open Punctuation 24
 
1.0%
Close Punctuation 24
 
1.0%
Lowercase Letter 15
 
0.6%
Uppercase Letter 12
 
0.5%
Decimal Number 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
140
 
5.9%
126
 
5.3%
124
 
5.2%
123
 
5.1%
83
 
3.5%
72
 
3.0%
67
 
2.8%
63
 
2.6%
52
 
2.2%
42
 
1.8%
Other values (267) 1498
62.7%
Lowercase Letter
ValueCountFrequency (%)
t 2
13.3%
e 2
13.3%
i 2
13.3%
h 1
6.7%
b 1
6.7%
u 1
6.7%
l 1
6.7%
y 1
6.7%
s 1
6.7%
r 1
6.7%
Other values (2) 2
13.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
16.7%
S 2
16.7%
K 2
16.7%
D 1
8.3%
I 1
8.3%
U 1
8.3%
A 1
8.3%
W 1
8.3%
Y 1
8.3%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
4 2
33.3%
1 1
16.7%
3 1
16.7%
Space Separator
ValueCountFrequency (%)
55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2390
94.6%
Common 109
 
4.3%
Latin 27
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
140
 
5.9%
126
 
5.3%
124
 
5.2%
123
 
5.1%
83
 
3.5%
72
 
3.0%
67
 
2.8%
63
 
2.6%
52
 
2.2%
42
 
1.8%
Other values (267) 1498
62.7%
Latin
ValueCountFrequency (%)
C 2
 
7.4%
S 2
 
7.4%
K 2
 
7.4%
t 2
 
7.4%
e 2
 
7.4%
i 2
 
7.4%
D 1
 
3.7%
I 1
 
3.7%
h 1
 
3.7%
b 1
 
3.7%
Other values (11) 11
40.7%
Common
ValueCountFrequency (%)
55
50.5%
( 24
22.0%
) 24
22.0%
2 2
 
1.8%
4 2
 
1.8%
1 1
 
0.9%
3 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2390
94.6%
ASCII 136
 
5.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
140
 
5.9%
126
 
5.3%
124
 
5.2%
123
 
5.1%
83
 
3.5%
72
 
3.0%
67
 
2.8%
63
 
2.6%
52
 
2.2%
42
 
1.8%
Other values (267) 1498
62.7%
ASCII
ValueCountFrequency (%)
55
40.4%
( 24
17.6%
) 24
17.6%
2 2
 
1.5%
C 2
 
1.5%
S 2
 
1.5%
K 2
 
1.5%
4 2
 
1.5%
t 2
 
1.5%
e 2
 
1.5%
Other values (18) 19
 
14.0%
Distinct299
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum1999-06-05 00:00:00
Maximum2024-05-07 14:58:45
2024-05-11T17:22:39.466485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:22:39.606646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
I
169 
U
144 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 169
54.0%
U 144
46.0%

Length

2024-05-11T17:22:39.733589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:39.821406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 169
54.0%
u 144
46.0%
Distinct124
Distinct (%)39.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T17:22:39.912985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:22:40.030754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct9
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
어린이집
134 
집단급식소
61 
학교
56 
산업체
16 
사회복지시설
16 
Other values (4)
30 

Length

Max length8
Median length6
Mean length3.8722045
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row집단급식소
2nd row산업체
3rd row집단급식소
4th row집단급식소
5th row집단급식소

Common Values

ValueCountFrequency (%)
어린이집 134
42.8%
집단급식소 61
19.5%
학교 56
17.9%
산업체 16
 
5.1%
사회복지시설 16
 
5.1%
병원 11
 
3.5%
공공기관 11
 
3.5%
기타 집단급식소 5
 
1.6%
기숙사 3
 
1.0%

Length

2024-05-11T17:22:40.162346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:40.273637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 134
42.1%
집단급식소 66
20.8%
학교 56
17.6%
산업체 16
 
5.0%
사회복지시설 16
 
5.0%
병원 11
 
3.5%
공공기관 11
 
3.5%
기타 5
 
1.6%
기숙사 3
 
0.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct244
Distinct (%)80.5%
Missing10
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean195134.63
Minimum191481.82
Maximum198428.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:22:40.413237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191481.82
5-th percentile192175.23
Q1193745.22
median195045.19
Q3196525.25
95-th percentile198125.5
Maximum198428.61
Range6946.7945
Interquartile range (IQR)2780.0338

Descriptive statistics

Standard deviation1838.31
Coefficient of variation (CV)0.0094207268
Kurtosis-1.0094983
Mean195134.63
Median Absolute Deviation (MAD)1417.3303
Skewness0.027077109
Sum59125792
Variance3379383.7
MonotonicityNot monotonic
2024-05-11T17:22:40.780340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196122.678608319 8
 
2.6%
193204.782207917 5
 
1.6%
192842.808605 5
 
1.6%
196147.389253733 4
 
1.3%
194063.079433996 3
 
1.0%
192917.428244737 3
 
1.0%
193472.446409343 3
 
1.0%
195474.381153608 2
 
0.6%
197884.419059004 2
 
0.6%
194387.717307135 2
 
0.6%
Other values (234) 266
85.0%
(Missing) 10
 
3.2%
ValueCountFrequency (%)
191481.81674639 1
0.3%
191555.354381759 1
0.3%
191585.298671366 1
0.3%
191677.374890384 1
0.3%
191691.678396263 1
0.3%
191735.667959747 1
0.3%
191872.217512299 1
0.3%
191898.699615214 1
0.3%
191974.78009646 1
0.3%
192030.377867 1
0.3%
ValueCountFrequency (%)
198428.611275 1
0.3%
198322.000995831 2
0.6%
198311.909398305 1
0.3%
198303.527071078 1
0.3%
198293.772263493 1
0.3%
198290.516043124 1
0.3%
198259.338355351 1
0.3%
198225.798157866 1
0.3%
198225.621987757 1
0.3%
198222.442875611 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct244
Distinct (%)80.5%
Missing10
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean444036.16
Minimum441645.99
Maximum445901.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:22:40.912852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441645.99
5-th percentile442239.92
Q1443312.6
median444102.65
Q3444854.35
95-th percentile445496.52
Maximum445901.41
Range4255.4271
Interquartile range (IQR)1541.749

Descriptive statistics

Standard deviation1013.1279
Coefficient of variation (CV)0.0022816339
Kurtosis-0.76994641
Mean444036.16
Median Absolute Deviation (MAD)758.27903
Skewness-0.32722072
Sum1.3454296 × 108
Variance1026428.2
MonotonicityNot monotonic
2024-05-11T17:22:41.040863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444705.530165147 8
 
2.6%
443168.51356024 5
 
1.6%
443406.511358 5
 
1.6%
443795.142708592 4
 
1.3%
445114.476412647 3
 
1.0%
444070.185727072 3
 
1.0%
444721.806084185 3
 
1.0%
444475.822156272 2
 
0.6%
443202.796249226 2
 
0.6%
444184.396009195 2
 
0.6%
Other values (234) 266
85.0%
(Missing) 10
 
3.2%
ValueCountFrequency (%)
441645.986301894 1
0.3%
441764.373955278 1
0.3%
441769.380294367 1
0.3%
441849.891828263 1
0.3%
441853.785415773 1
0.3%
441968.446721504 1
0.3%
442007.667678366 1
0.3%
442014.640731 1
0.3%
442054.457678128 1
0.3%
442054.92127907 1
0.3%
ValueCountFrequency (%)
445901.413432497 1
0.3%
445820.883711428 1
0.3%
445764.45259219 2
0.6%
445754.430464912 1
0.3%
445659.386592439 1
0.3%
445642.991660362 1
0.3%
445637.957918936 1
0.3%
445611.486175435 1
0.3%
445610.919894144 1
0.3%
445602.959212756 1
0.3%

위생업태명
Categorical

Distinct10
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
어린이집
90 
<NA>
66 
집단급식소
61 
학교
55 
사회복지시설
11 
Other values (5)
30 

Length

Max length8
Median length4
Mean length3.8466454
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row집단급식소
2nd row산업체
3rd row집단급식소
4th row집단급식소
5th row집단급식소

Common Values

ValueCountFrequency (%)
어린이집 90
28.8%
<NA> 66
21.1%
집단급식소 61
19.5%
학교 55
17.6%
사회복지시설 11
 
3.5%
병원 9
 
2.9%
산업체 8
 
2.6%
공공기관 8
 
2.6%
기숙사 3
 
1.0%
기타 집단급식소 2
 
0.6%

Length

2024-05-11T17:22:41.164982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:41.292323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 90
28.6%
na 66
21.0%
집단급식소 63
20.0%
학교 55
17.5%
사회복지시설 11
 
3.5%
병원 9
 
2.9%
산업체 8
 
2.5%
공공기관 8
 
2.5%
기숙사 3
 
1.0%
기타 2
 
0.6%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
229 
0
82 
3
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.1948882
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 229
73.2%
0 82
 
26.2%
3 1
 
0.3%
2 1
 
0.3%

Length

2024-05-11T17:22:41.415253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:41.505825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 229
73.2%
0 82
 
26.2%
3 1
 
0.3%
2 1
 
0.3%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)10.8%
Missing230
Missing (%)73.5%
Infinite0
Infinite (%)0.0%
Mean1.1686747
Minimum0
Maximum15
Zeros68
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:22:41.583765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.1461137
Coefficient of variation (CV)2.6920354
Kurtosis9.9922586
Mean1.1686747
Median Absolute Deviation (MAD)0
Skewness3.1609014
Sum97
Variance9.8980311
MonotonicityNot monotonic
2024-05-11T17:22:41.682272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 68
 
21.7%
5 3
 
1.0%
4 3
 
1.0%
1 2
 
0.6%
14 2
 
0.6%
7 2
 
0.6%
9 1
 
0.3%
15 1
 
0.3%
2 1
 
0.3%
(Missing) 230
73.5%
ValueCountFrequency (%)
0 68
21.7%
1 2
 
0.6%
2 1
 
0.3%
4 3
 
1.0%
5 3
 
1.0%
7 2
 
0.6%
9 1
 
0.3%
14 2
 
0.6%
15 1
 
0.3%
ValueCountFrequency (%)
15 1
 
0.3%
14 2
 
0.6%
9 1
 
0.3%
7 2
 
0.6%
5 3
 
1.0%
4 3
 
1.0%
2 1
 
0.3%
1 2
 
0.6%
0 68
21.7%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
237 
기타
61 
학교정화(절대)
 
9
주택가주변
 
3
학교정화(상대)
 
2

Length

Max length8
Median length4
Mean length3.7635783
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 237
75.7%
기타 61
 
19.5%
학교정화(절대) 9
 
2.9%
주택가주변 3
 
1.0%
학교정화(상대) 2
 
0.6%
아파트지역 1
 
0.3%

Length

2024-05-11T17:22:41.801662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:41.895621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 237
75.7%
기타 61
 
19.5%
학교정화(절대 9
 
2.9%
주택가주변 3
 
1.0%
학교정화(상대 2
 
0.6%
아파트지역 1
 
0.3%

등급구분명
Categorical

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
237 
기타
59 
자율
 
17

Length

Max length4
Median length4
Mean length3.514377
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 237
75.7%
기타 59
 
18.8%
자율 17
 
5.4%

Length

2024-05-11T17:22:42.023972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:42.122544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 237
75.7%
기타 59
 
18.8%
자율 17
 
5.4%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
상수도전용
211 
<NA>
102 

Length

Max length5
Median length5
Mean length4.6741214
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 211
67.4%
<NA> 102
32.6%

Length

2024-05-11T17:22:42.212541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:42.310031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 211
67.4%
na 102
32.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
298 
0
 
15

Length

Max length4
Median length4
Mean length3.85623
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 298
95.2%
0 15
 
4.8%

Length

2024-05-11T17:22:42.422167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:42.523149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 298
95.2%
0 15
 
4.8%

본사종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)3.5%
Missing142
Missing (%)45.4%
Infinite0
Infinite (%)0.0%
Mean0.3625731
Minimum0
Maximum16
Zeros149
Zeros (%)47.6%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:22:42.606105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum16
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.6547978
Coefficient of variation (CV)4.564039
Kurtosis57.232838
Mean0.3625731
Median Absolute Deviation (MAD)0
Skewness7.1368223
Sum62
Variance2.7383557
MonotonicityNot monotonic
2024-05-11T17:22:42.709526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 149
47.6%
1 15
 
4.8%
3 4
 
1.3%
10 1
 
0.3%
9 1
 
0.3%
16 1
 
0.3%
(Missing) 142
45.4%
ValueCountFrequency (%)
0 149
47.6%
1 15
 
4.8%
3 4
 
1.3%
9 1
 
0.3%
10 1
 
0.3%
16 1
 
0.3%
ValueCountFrequency (%)
16 1
 
0.3%
10 1
 
0.3%
9 1
 
0.3%
3 4
 
1.3%
1 15
 
4.8%
0 149
47.6%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
298 
0
 
15

Length

Max length4
Median length4
Mean length3.85623
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 298
95.2%
0 15
 
4.8%

Length

2024-05-11T17:22:42.825612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:42.924683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 298
95.2%
0 15
 
4.8%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
298 
0
 
15

Length

Max length4
Median length4
Mean length3.85623
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 298
95.2%
0 15
 
4.8%

Length

2024-05-11T17:22:43.019230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:43.108923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 298
95.2%
0 15
 
4.8%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
298 
0
 
15

Length

Max length4
Median length4
Mean length3.85623
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 298
95.2%
0 15
 
4.8%

Length

2024-05-11T17:22:43.203044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:43.293416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 298
95.2%
0 15
 
4.8%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
307 
자가
 
4
임대
 
2

Length

Max length4
Median length4
Mean length3.9616613
Min length2

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> 307
98.1%
자가 4
 
1.3%
임대 2
 
0.6%

Length

2024-05-11T17:22:43.388801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:43.489801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 307
98.1%
자가 4
 
1.3%
임대 2
 
0.6%

보증액
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
269 
0
44 

Length

Max length4
Median length4
Mean length3.5782748
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 269
85.9%
0 44
 
14.1%

Length

2024-05-11T17:22:43.583757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:43.673398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 269
85.9%
0 44
 
14.1%

월세액
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
269 
0
44 

Length

Max length4
Median length4
Mean length3.5782748
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 269
85.9%
0 44
 
14.1%

Length

2024-05-11T17:22:43.766903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:22:43.866508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 269
85.9%
0 44
 
14.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing66
Missing (%)21.1%
Memory size758.0 B
False
247 
(Missing)
66 
ValueCountFrequency (%)
False 247
78.9%
(Missing) 66
 
21.1%
2024-05-11T17:22:43.950589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct216
Distinct (%)87.4%
Missing66
Missing (%)21.1%
Infinite0
Infinite (%)0.0%
Mean147.34478
Minimum0
Maximum2738.3
Zeros18
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:22:44.041131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111.715
median31.9
Q3184.765
95-th percentile625.875
Maximum2738.3
Range2738.3
Interquartile range (IQR)173.05

Descriptive statistics

Standard deviation263.18149
Coefficient of variation (CV)1.786161
Kurtosis38.681725
Mean147.34478
Median Absolute Deviation (MAD)25.1
Skewness4.8422862
Sum36394.16
Variance69264.498
MonotonicityNot monotonic
2024-05-11T17:22:44.167273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 18
 
5.8%
12.9 3
 
1.0%
7.5 2
 
0.6%
37.92 2
 
0.6%
9.9 2
 
0.6%
180.0 2
 
0.6%
135.0 2
 
0.6%
19.2 2
 
0.6%
162.0 2
 
0.6%
27.04 2
 
0.6%
Other values (206) 210
67.1%
(Missing) 66
 
21.1%
ValueCountFrequency (%)
0.0 18
5.8%
2.61 1
 
0.3%
3.3 1
 
0.3%
4.76 1
 
0.3%
5.44 1
 
0.3%
5.8 1
 
0.3%
6.14 1
 
0.3%
6.24 1
 
0.3%
6.8 1
 
0.3%
6.9 2
 
0.6%
ValueCountFrequency (%)
2738.3 1
0.3%
1040.44 1
0.3%
966.78 1
0.3%
937.0 1
0.3%
925.3 1
0.3%
744.0 1
0.3%
738.15 1
0.3%
735.0 1
0.3%
708.4 1
0.3%
708.22 1
0.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031900003190000-105-1980-0000919800401<NA>3폐업2폐업19970909<NA><NA><NA>02 814392141.20156810서울특별시 동작구 대방동 390-5번지<NA><NA>서울기계공고2001-09-29 00:00:00I2018-08-31 23:59:59.0집단급식소193088.6211444354.810726집단급식소00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N338.2<NA><NA><NA>
131900003190000-105-1981-0000719810403<NA>3폐업2폐업20211231<NA><NA><NA>02 599614160.00156814서울특별시 동작구 사당동 68-2서울특별시 동작구 동작대로35길 43 (사당동)6996건영섬유구내식당2021-12-31 15:33:23U2022-01-02 02:40:00.0산업체198126.84422443266.064046산업체00기타기타상수도전용00000<NA>00N298.31<NA><NA><NA>
231900003190000-105-1981-0000819810403<NA>3폐업2폐업20101123<NA><NA><NA>02 537610730.96156090서울특별시 동작구 사당동 산 31-3번지<NA><NA>총신대기숙사2010-11-23 10:51:04I2018-08-31 23:59:59.0집단급식소197023.002371443174.006805집단급식소00기타기타상수도전용<NA>0<NA><NA><NA><NA><NA><NA>N226.34<NA><NA><NA>
331900003190000-105-1985-0001119850701<NA>3폐업2폐업19981120<NA><NA><NA>02 812192736.00156808서울특별시 동작구 대방동 345-1번지<NA><NA>시립부녀보호소2001-09-29 00:00:00I2018-08-31 23:59:59.0집단급식소193488.803914445486.444327집단급식소00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N240.0<NA><NA><NA>
431900003190000-105-1985-0001419850501<NA>3폐업2폐업19980114<NA><NA><NA>02 832764140.00156854서울특별시 동작구 신대방동 656-9번지<NA><NA>태평양화학서울센터2001-09-29 00:00:00I2018-08-31 23:59:59.0집단급식소<NA><NA>집단급식소00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N735.0<NA><NA><NA>
531900003190000-105-1986-0000219861201<NA>3폐업2폐업20021009<NA><NA><NA>02 816377239.99156831서울특별시 동작구 상도동 22-3번지<NA><NA>한국투자신탁(주)직원합숙소2002-10-09 00:00:00I2018-08-31 23:59:59.0집단급식소195203.055454444955.316316집단급식소00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N211.68<NA><NA><NA>
631900003190000-105-1990-0000119900330<NA>3폐업2폐업19950427<NA><NA><NA>02 8145151<NA>156800서울특별시 동작구 노량진동 27-2번지<NA><NA>(주)동아지기2002-08-16 00:00:00I2018-08-31 23:59:59.0집단급식소194360.477037445637.957919집단급식소3<NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731900003190000-105-1990-0000319900330<NA>1영업/정상1영업<NA><NA><NA><NA>02 8123212157.76156841서울특별시 동작구 상도동 212-128 서울삼성학교서울특별시 동작구 양녕로30길 19-4, 서울삼성농아원 (상도동)7035삼성농아원원아식당2021-04-30 09:39:52U2021-05-02 02:40:00.0사회복지시설195149.040648444102.652553사회복지시설00기타기타상수도전용<NA>0<NA><NA><NA><NA><NA><NA>N73.98<NA><NA><NA>
831900003190000-105-1990-0000419900330<NA>3폐업2폐업19970909<NA><NA><NA>02 8151833100.00156030서울특별시 동작구 상도동 500-1번지<NA><NA>강남국민학교식당2001-09-29 00:00:00I2018-08-31 23:59:59.0집단급식소195971.630768443656.259547집단급식소00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N140.0<NA><NA><NA>
931900003190000-105-1990-0000519900330<NA>3폐업2폐업19990701<NA><NA><NA>02 8205162194.50156030서울특별시 동작구 상도동 1-1번지<NA><NA>숭실대구내식당1999-07-02 00:00:00I2018-08-31 23:59:59.0집단급식소195698.672295445023.450185집단급식소00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N937.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
30331900003190000-105-2021-000052021-08-11<NA>3폐업2폐업2023-10-30<NA><NA><NA>02 815 9440<NA>156-846서울특별시 동작구 상도동 299-76서울특별시 동작구 국사봉길 86-6 (상도동)7052산들어린이집2023-10-30 16:09:01U2022-11-01 00:01:00.0어린이집193800.826405443787.810713<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30431900003190000-105-2021-0000620211129<NA>1영업/정상1영업<NA><NA><NA><NA>02 820 0079.00156030서울특별시 동작구 상도동 511 숭실대학교 전산관서울특별시 동작구 상도로 369, 숭실대학교 전산관 지하1층 (상도동)6978숭실대학교 전산관식당2021-11-29 17:45:08I2021-12-01 00:22:43.0학교196147.389254443795.142709학교00<NA><NA>상수도전용03000자가00N0.0<NA><NA><NA>
30531900003190000-105-2022-0000120220225<NA>1영업/정상1영업<NA><NA><NA><NA>02 823 9447.00156855서울특별시 동작구 신대방동 724 보라매자이 더 포레스트서울특별시 동작구 여의대방로22길 121, 관리동 1층 (신대방동, 보라매자이 더 포레스트)7056구립숲속자이어린이집2022-02-25 16:25:10I2022-02-27 00:22:37.0어린이집193441.38929444008.60048어린이집00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
30631900003190000-105-2023-000012023-02-20<NA>1영업/정상1영업<NA><NA><NA><NA>02 81515160.00156-070서울특별시 동작구 흑석동 340-1서울특별시 동작구 서달로 129, 1,2층 (흑석동)6973구립까망돌어린이집2023-02-20 17:30:16I2022-12-01 22:02:00.0어린이집196441.820616444764.864025<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30731900003190000-105-2023-000022023-03-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00156-862서울특별시 동작구 흑석동 245-1 서울은로유치원서울특별시 동작구 서달로 115, 서울은로유치원 2층 (흑석동)6973서울은로유치원2023-03-16 17:33:39I2022-12-02 23:08:00.0기타 집단급식소196399.42901444572.520846<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30831900003190000-105-2023-000032023-03-27<NA>1영업/정상1영업<NA><NA><NA><NA>02 81212630.00156-862서울특별시 동작구 흑석동 253-89 흑석자이아파트 관리동 3층 어린이집서울특별시 동작구 서달로 90, 3층 (흑석동, 흑석자이아파트)6987구립곰돌이어린이집2023-03-27 16:20:31I2022-12-02 22:09:00.0어린이집196462.523668444234.444496<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30931900003190000-105-2023-000042023-07-04<NA>1영업/정상1영업<NA><NA><NA><NA>023477260399.84156-090서울특별시 동작구 사당동 1160 사당 롯데캐슬 골든포레서울특별시 동작구 사당로 90, 사랑손동 2층 (사당동, 사당 롯데캐슬 골든포레)7075사랑손직업적응훈련시설2023-07-04 14:00:27I2022-12-07 00:06:00.0사회복지시설196594.019078443280.825807<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31031900003190000-105-2023-000052023-10-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00156-070서울특별시 동작구 흑석동 339 흑석한강센트레빌2차서울특별시 동작구 서달로 91, 107동관리동 (흑석동, 흑석한강센트레빌2차)6975한강어린이집2023-10-20 17:27:14I2022-10-30 22:02:00.0어린이집196267.514996444443.755756<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31131900003190000-105-2024-000012024-02-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00156-807서울특별시 동작구 대방동 20-52 구립꿈빛하나어린이집서울특별시 동작구 등용로9길 5, 구립꿈빛하나어린이집 3층 (대방동)6942구립꿈빛하나어린이집2024-02-26 11:54:50I2023-12-01 22:08:00.0어린이집193890.284736445248.43037<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31231900003190000-105-2024-000022024-04-04<NA>1영업/정상1영업<NA><NA><NA><NA>02 845727248.67156-852서울특별시 동작구 신대방동 565 우성아파트 교육연구동서울특별시 동작구 여의대방로 22, 1층 (신대방동, 우성아파트)7065에이씨에이동작2024-04-04 14:35:27I2023-12-04 00:06:00.0기타 집단급식소192113.200601443344.373525<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>