Overview

Dataset statistics

Number of variables44
Number of observations182
Missing cells1853
Missing cells (%)23.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory67.3 KiB
Average record size in memory378.7 B

Variable types

Categorical20
Text6
DateTime4
Unsupported9
Numeric4
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
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-18042/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (81.8%)Imbalance
여성종사자수 is highly imbalanced (81.8%)Imbalance
총인원 is highly imbalanced (81.8%)Imbalance
공장사무직종업원수 is highly imbalanced (57.9%)Imbalance
공장판매직종업원수 is highly imbalanced (63.1%)Imbalance
공장생산직종업원수 is highly imbalanced (66.7%)Imbalance
보증액 is highly imbalanced (81.8%)Imbalance
월세액 is highly imbalanced (81.8%)Imbalance
시설총규모 is highly imbalanced (58.8%)Imbalance
인허가취소일자 has 182 (100.0%) missing valuesMissing
폐업일자 has 63 (34.6%) missing valuesMissing
휴업시작일자 has 182 (100.0%) missing valuesMissing
휴업종료일자 has 182 (100.0%) missing valuesMissing
재개업일자 has 182 (100.0%) missing valuesMissing
전화번호 has 59 (32.4%) missing valuesMissing
소재지면적 has 7 (3.8%) missing valuesMissing
도로명주소 has 23 (12.6%) missing valuesMissing
도로명우편번호 has 24 (13.2%) missing valuesMissing
영업장주변구분명 has 182 (100.0%) missing valuesMissing
등급구분명 has 182 (100.0%) missing valuesMissing
다중이용업소여부 has 37 (20.3%) missing valuesMissing
전통업소지정번호 has 182 (100.0%) missing valuesMissing
전통업소주된음식 has 182 (100.0%) missing valuesMissing
홈페이지 has 182 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 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

Reproduction

Analysis started2024-05-11 05:18:20.026070
Analysis finished2024-05-11 05:18:21.361839
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
3150000
182 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 182
100.0%

Length

2024-05-11T05:18:21.635159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:21.947001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 182
100.0%

관리번호
Text

UNIQUE 

Distinct182
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T05:18:22.334029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4004
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

Unique182 ?
Unique (%)100.0%

Sample

1st row3150000-122-2008-00001
2nd row3150000-122-2008-00002
3rd row3150000-122-2008-00003
4th row3150000-122-2008-00004
5th row3150000-122-2008-00005
ValueCountFrequency (%)
3150000-122-2008-00001 1
 
0.5%
3150000-122-2016-00004 1
 
0.5%
3150000-122-2016-00006 1
 
0.5%
3150000-122-2017-00001 1
 
0.5%
3150000-122-2017-00002 1
 
0.5%
3150000-122-2017-00003 1
 
0.5%
3150000-122-2017-00004 1
 
0.5%
3150000-122-2017-00005 1
 
0.5%
3150000-122-2017-00006 1
 
0.5%
3150000-122-2017-00007 1
 
0.5%
Other values (172) 172
94.5%
2024-05-11T05:18:23.101976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1662
41.5%
2 623
 
15.6%
1 572
 
14.3%
- 546
 
13.6%
3 227
 
5.7%
5 210
 
5.2%
8 49
 
1.2%
9 37
 
0.9%
4 29
 
0.7%
7 25
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3458
86.4%
Dash Punctuation 546
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1662
48.1%
2 623
 
18.0%
1 572
 
16.5%
3 227
 
6.6%
5 210
 
6.1%
8 49
 
1.4%
9 37
 
1.1%
4 29
 
0.8%
7 25
 
0.7%
6 24
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 546
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4004
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1662
41.5%
2 623
 
15.6%
1 572
 
14.3%
- 546
 
13.6%
3 227
 
5.7%
5 210
 
5.2%
8 49
 
1.2%
9 37
 
0.9%
4 29
 
0.7%
7 25
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4004
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1662
41.5%
2 623
 
15.6%
1 572
 
14.3%
- 546
 
13.6%
3 227
 
5.7%
5 210
 
5.2%
8 49
 
1.2%
9 37
 
0.9%
4 29
 
0.7%
7 25
 
0.6%

인허가일자
Date

Distinct168
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2008-03-19 00:00:00
Maximum2024-03-13 00:00:00
2024-05-11T05:18:23.465885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:18:23.876133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing182
Missing (%)100.0%
Memory size1.7 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
3
119 
1
63 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 119
65.4%
1 63
34.6%

Length

2024-05-11T05:18:24.226332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:24.491104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 119
65.4%
1 63
34.6%

영업상태명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
폐업
119 
영업/정상
63 

Length

Max length5
Median length2
Mean length3.0384615
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 119
65.4%
영업/정상 63
34.6%

Length

2024-05-11T05:18:24.825402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:25.148517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 119
65.4%
영업/정상 63
34.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2
119 
1
63 

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 (%)
2 119
65.4%
1 63
34.6%

Length

2024-05-11T05:18:25.702881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:26.009155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 119
65.4%
1 63
34.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
폐업
119 
영업
63 

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 (%)
폐업 119
65.4%
영업 63
34.6%

Length

2024-05-11T05:18:26.297246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:26.585317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 119
65.4%
영업 63
34.6%

폐업일자
Date

MISSING 

Distinct105
Distinct (%)88.2%
Missing63
Missing (%)34.6%
Memory size1.6 KiB
Minimum2009-01-20 00:00:00
Maximum2024-03-22 00:00:00
2024-05-11T05:18:26.886506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:18:27.322170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing182
Missing (%)100.0%
Memory size1.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing182
Missing (%)100.0%
Memory size1.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing182
Missing (%)100.0%
Memory size1.7 KiB

전화번호
Text

MISSING 

Distinct120
Distinct (%)97.6%
Missing59
Missing (%)32.4%
Memory size1.6 KiB
2024-05-11T05:18:27.974677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.650407
Min length8

Characters and Unicode

Total characters1310
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

Unique117 ?
Unique (%)95.1%

Sample

1st row02 26076263
2nd row0226049800
3rd row02 26409273
4th row02 26613913
5th row02 26699202
ValueCountFrequency (%)
02 48
 
26.1%
0226969000 2
 
1.1%
26635666 2
 
1.1%
031 2
 
1.1%
0226636262 2
 
1.1%
070 2
 
1.1%
26409273 2
 
1.1%
0226696000 1
 
0.5%
63962397 1
 
0.5%
26025900 1
 
0.5%
Other values (121) 121
65.8%
2024-05-11T05:18:29.195807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 259
19.8%
0 231
17.6%
6 196
15.0%
103
 
7.9%
4 96
 
7.3%
3 84
 
6.4%
7 82
 
6.3%
9 70
 
5.3%
1 67
 
5.1%
5 62
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1207
92.1%
Space Separator 103
 
7.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 259
21.5%
0 231
19.1%
6 196
16.2%
4 96
 
8.0%
3 84
 
7.0%
7 82
 
6.8%
9 70
 
5.8%
1 67
 
5.6%
5 62
 
5.1%
8 60
 
5.0%
Space Separator
ValueCountFrequency (%)
103
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 259
19.8%
0 231
17.6%
6 196
15.0%
103
 
7.9%
4 96
 
7.3%
3 84
 
6.4%
7 82
 
6.3%
9 70
 
5.3%
1 67
 
5.1%
5 62
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 259
19.8%
0 231
17.6%
6 196
15.0%
103
 
7.9%
4 96
 
7.3%
3 84
 
6.4%
7 82
 
6.3%
9 70
 
5.3%
1 67
 
5.1%
5 62
 
4.7%

소재지면적
Real number (ℝ)

MISSING 

Distinct126
Distinct (%)72.0%
Missing7
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean72.338
Minimum0
Maximum1081.52
Zeros1
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T05:18:29.712843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.6
Q128.28
median45
Q375.49
95-th percentile209.559
Maximum1081.52
Range1081.52
Interquartile range (IQR)47.21

Descriptive statistics

Standard deviation105.87754
Coefficient of variation (CV)1.4636503
Kurtosis50.546803
Mean72.338
Median Absolute Deviation (MAD)23.11
Skewness6.1252406
Sum12659.15
Variance11210.053
MonotonicityNot monotonic
2024-05-11T05:18:30.189986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40.0 6
 
3.3%
30.0 6
 
3.3%
21.0 5
 
2.7%
45.0 4
 
2.2%
33.0 4
 
2.2%
21.12 3
 
1.6%
66.0 3
 
1.6%
3.3 3
 
1.6%
28.0 3
 
1.6%
70.0 3
 
1.6%
Other values (116) 135
74.2%
(Missing) 7
 
3.8%
ValueCountFrequency (%)
0.0 1
 
0.5%
3.3 3
1.6%
4.0 1
 
0.5%
4.95 1
 
0.5%
5.0 2
1.1%
6.6 2
1.1%
7.2 2
1.1%
9.83 1
 
0.5%
11.0 1
 
0.5%
12.0 1
 
0.5%
ValueCountFrequency (%)
1081.52 1
0.5%
592.0 1
0.5%
352.0 1
0.5%
349.22 1
0.5%
315.0 1
0.5%
294.0 1
0.5%
264.0 1
0.5%
245.68 1
0.5%
216.16 1
0.5%
206.73 1
0.5%

소재지우편번호
Text

Distinct55
Distinct (%)30.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T05:18:30.829879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1483516
Min length6

Characters and Unicode

Total characters1119
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

Unique29 ?
Unique (%)15.9%

Sample

1st row157290
2nd row157801
3rd row157910
4th row157816
5th row157290
ValueCountFrequency (%)
157816 35
19.2%
157290 27
 
14.8%
157740 10
 
5.5%
157818 8
 
4.4%
157-210 6
 
3.3%
157836 6
 
3.3%
157210 6
 
3.3%
157815 5
 
2.7%
157-740 5
 
2.7%
157-816 5
 
2.7%
Other values (45) 69
37.9%
2024-05-11T05:18:32.188199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 269
24.0%
7 212
18.9%
5 198
17.7%
8 118
10.5%
0 74
 
6.6%
6 58
 
5.2%
9 55
 
4.9%
2 52
 
4.6%
4 32
 
2.9%
- 27
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1092
97.6%
Dash Punctuation 27
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 269
24.6%
7 212
19.4%
5 198
18.1%
8 118
10.8%
0 74
 
6.8%
6 58
 
5.3%
9 55
 
5.0%
2 52
 
4.8%
4 32
 
2.9%
3 24
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1119
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 269
24.0%
7 212
18.9%
5 198
17.7%
8 118
10.5%
0 74
 
6.6%
6 58
 
5.2%
9 55
 
4.9%
2 52
 
4.6%
4 32
 
2.9%
- 27
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1119
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 269
24.0%
7 212
18.9%
5 198
17.7%
8 118
10.5%
0 74
 
6.6%
6 58
 
5.2%
9 55
 
4.9%
2 52
 
4.6%
4 32
 
2.9%
- 27
 
2.4%

지번주소
Text

Distinct159
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T05:18:33.574623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length41
Mean length26.956044
Min length18

Characters and Unicode

Total characters4906
Distinct characters150
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

Unique146 ?
Unique (%)80.2%

Sample

1st row서울특별시 강서구 외발산동 424 외발산동 424번지 공판장동 3층
2nd row서울특별시 강서구 가양동 231-4
3rd row서울특별시 강서구 화곡동 933-12 (1,2층)
4th row서울특별시 강서구 공항동 1350-7 1층
5th row서울특별시 강서구 외발산동 427 청과물동 1층
ValueCountFrequency (%)
서울특별시 182
19.0%
강서구 182
19.0%
공항동 61
 
6.4%
외발산동 48
 
5.0%
1층 40
 
4.2%
427 34
 
3.5%
방화동 16
 
1.7%
강서농산물시장 15
 
1.6%
화곡동 14
 
1.5%
등촌동 14
 
1.5%
Other values (224) 354
36.9%
2024-05-11T05:18:36.534829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
904
18.4%
서 391
 
8.0%
1 243
 
5.0%
동 210
 
4.3%
시 209
 
4.3%
강 208
 
4.2%
특 183
 
3.7%
별 183
 
3.7%
울 183
 
3.7%
구 182
 
3.7%
Other values (140) 2010
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2782
56.7%
Decimal Number 1019
 
20.8%
Space Separator 904
 
18.4%
Dash Punctuation 145
 
3.0%
Close Punctuation 16
 
0.3%
Open Punctuation 16
 
0.3%
Uppercase Letter 13
 
0.3%
Other Punctuation 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 391
14.1%
동 210
 
7.5%
시 209
 
7.5%
강 208
 
7.5%
특 183
 
6.6%
별 183
 
6.6%
울 183
 
6.6%
구 182
 
6.5%
층 89
 
3.2%
산 83
 
3.0%
Other values (115) 861
30.9%
Decimal Number
ValueCountFrequency (%)
1 243
23.8%
4 128
12.6%
2 125
12.3%
3 105
10.3%
7 100
9.8%
6 86
 
8.4%
0 85
 
8.3%
5 73
 
7.2%
9 38
 
3.7%
8 36
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
A 4
30.8%
B 3
23.1%
D 2
15.4%
M 1
 
7.7%
J 1
 
7.7%
C 1
 
7.7%
T 1
 
7.7%
Close Punctuation
ValueCountFrequency (%)
) 13
81.2%
] 3
 
18.8%
Open Punctuation
ValueCountFrequency (%)
( 13
81.2%
[ 3
 
18.8%
Other Punctuation
ValueCountFrequency (%)
, 10
90.9%
. 1
 
9.1%
Space Separator
ValueCountFrequency (%)
904
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 145
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2782
56.7%
Common 2111
43.0%
Latin 13
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 391
14.1%
동 210
 
7.5%
시 209
 
7.5%
강 208
 
7.5%
특 183
 
6.6%
별 183
 
6.6%
울 183
 
6.6%
구 182
 
6.5%
층 89
 
3.2%
산 83
 
3.0%
Other values (115) 861
30.9%
Common
ValueCountFrequency (%)
904
42.8%
1 243
 
11.5%
- 145
 
6.9%
4 128
 
6.1%
2 125
 
5.9%
3 105
 
5.0%
7 100
 
4.7%
6 86
 
4.1%
0 85
 
4.0%
5 73
 
3.5%
Other values (8) 117
 
5.5%
Latin
ValueCountFrequency (%)
A 4
30.8%
B 3
23.1%
D 2
15.4%
M 1
 
7.7%
J 1
 
7.7%
C 1
 
7.7%
T 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2782
56.7%
ASCII 2124
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
904
42.6%
1 243
 
11.4%
- 145
 
6.8%
4 128
 
6.0%
2 125
 
5.9%
3 105
 
4.9%
7 100
 
4.7%
6 86
 
4.0%
0 85
 
4.0%
5 73
 
3.4%
Other values (15) 130
 
6.1%
Hangul
ValueCountFrequency (%)
서 391
14.1%
동 210
 
7.5%
시 209
 
7.5%
강 208
 
7.5%
특 183
 
6.6%
별 183
 
6.6%
울 183
 
6.6%
구 182
 
6.5%
층 89
 
3.2%
산 83
 
3.0%
Other values (115) 861
30.9%

도로명주소
Text

MISSING 

Distinct149
Distinct (%)93.7%
Missing23
Missing (%)12.6%
Memory size1.6 KiB
2024-05-11T05:18:37.501539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length48
Mean length35.698113
Min length23

Characters and Unicode

Total characters5676
Distinct characters171
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

Unique140 ?
Unique (%)88.1%

Sample

1st row서울특별시 강서구 양천로47나길 48-5 (가양동)
2nd row서울특별시 강서구 월정로14길 19 (화곡동,(1,2층))
3rd row서울특별시 강서구 개화동로13길 6-19 (개화동,1층)
4th row서울특별시 강서구 발산로 24 (외발산동,공판장 냉장창고동 1층, 지상6층)
5th row서울특별시 강서구 공항대로7길 35, 2층 (공항동)
ValueCountFrequency (%)
서울특별시 159
 
14.7%
강서구 159
 
14.7%
1층 50
 
4.6%
공항동 47
 
4.3%
발산로 41
 
3.8%
외발산동 39
 
3.6%
40 34
 
3.1%
강서농산물시장 14
 
1.3%
등촌동 14
 
1.3%
방화대로6다길 14
 
1.3%
Other values (276) 511
47.2%
2024-05-11T05:18:39.472396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
923
 
16.3%
서 350
 
6.2%
1 256
 
4.5%
동 212
 
3.7%
강 190
 
3.3%
시 188
 
3.3%
, 173
 
3.0%
) 163
 
2.9%
( 163
 
2.9%
로 161
 
2.8%
Other values (161) 2897
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3291
58.0%
Space Separator 923
 
16.3%
Decimal Number 879
 
15.5%
Other Punctuation 174
 
3.1%
Close Punctuation 164
 
2.9%
Open Punctuation 164
 
2.9%
Dash Punctuation 61
 
1.1%
Uppercase Letter 20
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 350
 
10.6%
동 212
 
6.4%
강 190
 
5.8%
시 188
 
5.7%
로 161
 
4.9%
별 160
 
4.9%
특 160
 
4.9%
울 160
 
4.9%
구 159
 
4.8%
층 122
 
3.7%
Other values (135) 1429
43.4%
Decimal Number
ValueCountFrequency (%)
1 256
29.1%
0 114
13.0%
2 102
 
11.6%
4 99
 
11.3%
6 85
 
9.7%
5 75
 
8.5%
3 57
 
6.5%
9 32
 
3.6%
7 30
 
3.4%
8 29
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
A 8
40.0%
B 4
20.0%
D 2
 
10.0%
J 2
 
10.0%
F 1
 
5.0%
M 1
 
5.0%
C 1
 
5.0%
T 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 173
99.4%
. 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 163
99.4%
] 1
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 163
99.4%
[ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
923
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3291
58.0%
Common 2365
41.7%
Latin 20
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 350
 
10.6%
동 212
 
6.4%
강 190
 
5.8%
시 188
 
5.7%
로 161
 
4.9%
별 160
 
4.9%
특 160
 
4.9%
울 160
 
4.9%
구 159
 
4.8%
층 122
 
3.7%
Other values (135) 1429
43.4%
Common
ValueCountFrequency (%)
923
39.0%
1 256
 
10.8%
, 173
 
7.3%
) 163
 
6.9%
( 163
 
6.9%
0 114
 
4.8%
2 102
 
4.3%
4 99
 
4.2%
6 85
 
3.6%
5 75
 
3.2%
Other values (8) 212
 
9.0%
Latin
ValueCountFrequency (%)
A 8
40.0%
B 4
20.0%
D 2
 
10.0%
J 2
 
10.0%
F 1
 
5.0%
M 1
 
5.0%
C 1
 
5.0%
T 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3291
58.0%
ASCII 2385
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
923
38.7%
1 256
 
10.7%
, 173
 
7.3%
) 163
 
6.8%
( 163
 
6.8%
0 114
 
4.8%
2 102
 
4.3%
4 99
 
4.2%
6 85
 
3.6%
5 75
 
3.1%
Other values (16) 232
 
9.7%
Hangul
ValueCountFrequency (%)
서 350
 
10.6%
동 212
 
6.4%
강 190
 
5.8%
시 188
 
5.7%
로 161
 
4.9%
별 160
 
4.9%
특 160
 
4.9%
울 160
 
4.9%
구 159
 
4.8%
층 122
 
3.7%
Other values (135) 1429
43.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct48
Distinct (%)30.4%
Missing24
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean7650.2152
Minimum7504
Maximum7808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T05:18:40.063236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7504
5-th percentile7548.15
Q17628
median7644
Q37645
95-th percentile7802
Maximum7808
Range304
Interquartile range (IQR)17

Descriptive statistics

Standard deviation62.526768
Coefficient of variation (CV)0.0081732038
Kurtosis1.6111225
Mean7650.2152
Median Absolute Deviation (MAD)7.5
Skewness0.77488924
Sum1208734
Variance3909.5967
MonotonicityNot monotonic
2024-05-11T05:18:40.570667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
7644 44
24.2%
7645 33
18.1%
7667 8
 
4.4%
7802 5
 
2.7%
7628 5
 
2.7%
7626 4
 
2.2%
7625 4
 
2.2%
7616 3
 
1.6%
7635 3
 
1.6%
7741 2
 
1.1%
Other values (38) 47
25.8%
(Missing) 24
13.2%
ValueCountFrequency (%)
7504 1
0.5%
7510 1
0.5%
7512 1
0.5%
7516 1
0.5%
7521 2
1.1%
7526 1
0.5%
7532 1
0.5%
7551 2
1.1%
7554 1
0.5%
7557 1
0.5%
ValueCountFrequency (%)
7808 1
 
0.5%
7807 1
 
0.5%
7806 2
 
1.1%
7803 1
 
0.5%
7802 5
2.7%
7788 1
 
0.5%
7787 2
 
1.1%
7785 1
 
0.5%
7780 1
 
0.5%
7770 1
 
0.5%

사업장명
Text

Distinct178
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T05:18:41.174772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length6.7802198
Min length2

Characters and Unicode

Total characters1234
Distinct characters220
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

Unique174 ?
Unique (%)95.6%

Sample

1st row창성유통냉장(주)
2nd row(주)마라식품
3rd row(주)하나푸드
4th row웰빙팝(주)
5th row(주)민수청과
ValueCountFrequency (%)
주식회사 14
 
6.4%
공공급식센터 8
 
3.7%
대양계란 2
 
0.9%
우리농산 2
 
0.9%
농업회사법인 2
 
0.9%
푸드 2
 
0.9%
금천구 2
 
0.9%
강화농산 2
 
0.9%
드림농산 1
 
0.5%
정다운푸드 1
 
0.5%
Other values (183) 183
83.6%
2024-05-11T05:18:42.416833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 66
 
5.3%
) 52
 
4.2%
( 50
 
4.1%
드 48
 
3.9%
푸 47
 
3.8%
식 38
 
3.1%
37
 
3.0%
산 30
 
2.4%
사 28
 
2.3%
회 25
 
2.0%
Other values (210) 813
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1077
87.3%
Close Punctuation 52
 
4.2%
Open Punctuation 50
 
4.1%
Space Separator 37
 
3.0%
Uppercase Letter 11
 
0.9%
Lowercase Letter 4
 
0.3%
Other Punctuation 2
 
0.2%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 66
 
6.1%
드 48
 
4.5%
푸 47
 
4.4%
식 38
 
3.5%
산 30
 
2.8%
사 28
 
2.6%
회 25
 
2.3%
유 22
 
2.0%
농 21
 
1.9%
서 21
 
1.9%
Other values (196) 731
67.9%
Uppercase Letter
ValueCountFrequency (%)
S 4
36.4%
F 3
27.3%
M 1
 
9.1%
H 1
 
9.1%
E 1
 
9.1%
R 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
o 2
50.0%
d 1
25.0%
f 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Space Separator
ValueCountFrequency (%)
37
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1077
87.3%
Common 142
 
11.5%
Latin 15
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 66
 
6.1%
드 48
 
4.5%
푸 47
 
4.4%
식 38
 
3.5%
산 30
 
2.8%
사 28
 
2.6%
회 25
 
2.3%
유 22
 
2.0%
농 21
 
1.9%
서 21
 
1.9%
Other values (196) 731
67.9%
Latin
ValueCountFrequency (%)
S 4
26.7%
F 3
20.0%
o 2
13.3%
M 1
 
6.7%
H 1
 
6.7%
E 1
 
6.7%
R 1
 
6.7%
d 1
 
6.7%
f 1
 
6.7%
Common
ValueCountFrequency (%)
) 52
36.6%
( 50
35.2%
37
26.1%
. 2
 
1.4%
4 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1077
87.3%
ASCII 157
 
12.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 66
 
6.1%
드 48
 
4.5%
푸 47
 
4.4%
식 38
 
3.5%
산 30
 
2.8%
사 28
 
2.6%
회 25
 
2.3%
유 22
 
2.0%
농 21
 
1.9%
서 21
 
1.9%
Other values (196) 731
67.9%
ASCII
ValueCountFrequency (%)
) 52
33.1%
( 50
31.8%
37
23.6%
S 4
 
2.5%
F 3
 
1.9%
o 2
 
1.3%
. 2
 
1.3%
4 1
 
0.6%
M 1
 
0.6%
H 1
 
0.6%
Other values (4) 4
 
2.5%

최종수정일자
Date

UNIQUE 

Distinct182
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2008-03-21 15:32:58
Maximum2024-03-22 15:26:15
2024-05-11T05:18:43.007742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:18:43.621908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
I
126 
U
56 

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 126
69.2%
U 56
30.8%

Length

2024-05-11T05:18:44.235131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:44.713318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 126
69.2%
u 56
30.8%

데이터갱신일자
Date

Distinct76
Distinct (%)41.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:01:00
2024-05-11T05:18:45.080336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:18:45.607460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
집단급식소 식품판매업
182 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
집단급식소 식품판매업 182
100.0%

Length

2024-05-11T05:18:46.093113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:46.518050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 182
50.0%
식품판매업 182
50.0%

좌표정보(X)
Real number (ℝ)

Distinct103
Distinct (%)56.9%
Missing1
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean184621.42
Minimum182418.86
Maximum189076.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T05:18:46.991027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182418.86
5-th percentile183355.07
Q1183813.86
median184148.57
Q3185078
95-th percentile187691.18
Maximum189076.27
Range6657.4127
Interquartile range (IQR)1264.1425

Descriptive statistics

Standard deviation1447.0423
Coefficient of variation (CV)0.0078378899
Kurtosis0.93962975
Mean184621.42
Median Absolute Deviation (MAD)379.10518
Skewness1.4333773
Sum33416476
Variance2093931.5
MonotonicityNot monotonic
2024-05-11T05:18:47.662252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
184148.571466974 36
 
19.8%
183914.938310002 10
 
5.5%
187691.18308347 8
 
4.4%
185127.285385035 4
 
2.2%
183936.52968661 3
 
1.6%
183839.867998243 3
 
1.6%
183837.653874925 3
 
1.6%
183857.47431994 3
 
1.6%
183872.535394441 3
 
1.6%
185826.642871475 2
 
1.1%
Other values (93) 106
58.2%
ValueCountFrequency (%)
182418.857873799 1
0.5%
182929.561795629 1
0.5%
182964.153168769 1
0.5%
183013.81000202 1
0.5%
183017.743573303 1
0.5%
183040.616465943 1
0.5%
183307.197874057 1
0.5%
183315.556652953 1
0.5%
183350.907355596 1
0.5%
183355.066772749 1
0.5%
ValueCountFrequency (%)
189076.27057948 1
 
0.5%
188835.402562736 1
 
0.5%
188783.060728518 1
 
0.5%
188258.372897956 1
 
0.5%
188059.139862631 1
 
0.5%
187833.011527618 1
 
0.5%
187727.758706201 2
 
1.1%
187691.18308347 8
4.4%
187640.861609067 1
 
0.5%
187590.605880475 1
 
0.5%

좌표정보(Y)
Real number (ℝ)

Distinct103
Distinct (%)56.9%
Missing1
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean450347.17
Minimum447473.57
Maximum452802.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T05:18:48.297806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447473.57
5-th percentile448402.04
Q1450147.24
median450273.25
Q3450552.51
95-th percentile452250.03
Maximum452802.57
Range5329.0061
Interquartile range (IQR)405.26862

Descriptive statistics

Standard deviation933.6808
Coefficient of variation (CV)0.0020732467
Kurtosis2.5241834
Mean450347.17
Median Absolute Deviation (MAD)195.73025
Skewness-0.37145324
Sum81512837
Variance871759.83
MonotonicityNot monotonic
2024-05-11T05:18:48.791900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450166.360534543 36
 
19.8%
450085.01457343 10
 
5.5%
449648.124125697 8
 
4.4%
450939.221091497 4
 
2.2%
450492.58534948 3
 
1.6%
450409.970470513 3
 
1.6%
450342.841043406 3
 
1.6%
450465.331949843 3
 
1.6%
450365.986631415 3
 
1.6%
452250.028523129 2
 
1.1%
Other values (93) 106
58.2%
ValueCountFrequency (%)
447473.568819772 1
0.5%
447489.593501713 1
0.5%
447557.680594 1
0.5%
447680.583138643 1
0.5%
447798.588072901 1
0.5%
447837.900698887 2
1.1%
447858.621309887 1
0.5%
448020.741865225 1
0.5%
448402.040509502 1
0.5%
448562.459056221 1
0.5%
ValueCountFrequency (%)
452802.574950725 1
0.5%
452774.340725738 1
0.5%
452726.015586166 1
0.5%
452526.699106933 1
0.5%
452376.948619318 1
0.5%
452306.142853035 1
0.5%
452293.455519022 1
0.5%
452260.798514601 1
0.5%
452250.028523129 2
1.1%
452204.165533971 1
0.5%

위생업태명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
집단급식소 식품판매업
145 
<NA>
37 

Length

Max length11
Median length11
Mean length9.5769231
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
집단급식소 식품판매업 145
79.7%
<NA> 37
 
20.3%

Length

2024-05-11T05:18:49.215217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:49.790383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 145
44.3%
식품판매업 145
44.3%
na 37
 
11.3%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
177 
0
 
5

Length

Max length4
Median length4
Mean length3.9175824
Min length1

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> 177
97.3%
0 5
 
2.7%

Length

2024-05-11T05:18:50.117218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:50.484628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
97.3%
0 5
 
2.7%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
177 
0
 
5

Length

Max length4
Median length4
Mean length3.9175824
Min length1

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> 177
97.3%
0 5
 
2.7%

Length

2024-05-11T05:18:50.974787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:51.388809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
97.3%
0 5
 
2.7%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing182
Missing (%)100.0%
Memory size1.7 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing182
Missing (%)100.0%
Memory size1.7 KiB

급수시설구분명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
140 
상수도전용
42 

Length

Max length5
Median length4
Mean length4.2307692
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 140
76.9%
상수도전용 42
 
23.1%

Length

2024-05-11T05:18:52.168569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:52.754500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 140
76.9%
상수도전용 42
 
23.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
177 
0
 
5

Length

Max length4
Median length4
Mean length3.9175824
Min length1

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> 177
97.3%
0 5
 
2.7%

Length

2024-05-11T05:18:53.465489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:53.897516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
97.3%
0 5
 
2.7%

본사종업원수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
153 
0
29 

Length

Max length4
Median length4
Mean length3.521978
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 153
84.1%
0 29
 
15.9%

Length

2024-05-11T05:18:54.289679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:54.835988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 153
84.1%
0 29
 
15.9%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
153 
0
28 
12
 
1

Length

Max length4
Median length4
Mean length3.5274725
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 153
84.1%
0 28
 
15.4%
12 1
 
0.5%

Length

2024-05-11T05:18:55.334756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:55.744594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 153
84.1%
0 28
 
15.4%
12 1
 
0.5%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
152 
0
27 
2
 
2
1
 
1

Length

Max length4
Median length4
Mean length3.5054945
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
83.5%
0 27
 
14.8%
2 2
 
1.1%
1 1
 
0.5%

Length

2024-05-11T05:18:56.453142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:56.949720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
83.5%
0 27
 
14.8%
2 2
 
1.1%
1 1
 
0.5%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
152 
0
26 
2
 
2
1
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.5054945
Min length1

Unique

Unique2 ?
Unique (%)1.1%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row2
5th row2

Common Values

ValueCountFrequency (%)
<NA> 152
83.5%
0 26
 
14.3%
2 2
 
1.1%
1 1
 
0.5%
3 1
 
0.5%

Length

2024-05-11T05:18:57.378993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:57.856013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
83.5%
0 26
 
14.3%
2 2
 
1.1%
1 1
 
0.5%
3 1
 
0.5%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
90 
임대
65 
자가
27 

Length

Max length4
Median length2
Mean length2.989011
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 90
49.5%
임대 65
35.7%
자가 27
 
14.8%

Length

2024-05-11T05:18:58.286558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:58.650827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 90
49.5%
임대 65
35.7%
자가 27
 
14.8%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
177 
0
 
5

Length

Max length4
Median length4
Mean length3.9175824
Min length1

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> 177
97.3%
0 5
 
2.7%

Length

2024-05-11T05:18:59.147074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:18:59.628596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
97.3%
0 5
 
2.7%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
177 
0
 
5

Length

Max length4
Median length4
Mean length3.9175824
Min length1

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> 177
97.3%
0 5
 
2.7%

Length

2024-05-11T05:19:00.077682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:19:00.428267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
97.3%
0 5
 
2.7%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.7%
Missing37
Missing (%)20.3%
Memory size496.0 B
False
145 
(Missing)
37 
ValueCountFrequency (%)
False 145
79.7%
(Missing) 37
 
20.3%
2024-05-11T05:19:00.770440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
0.0
143 
<NA>
37 
75.98
 
1
75.0
 
1

Length

Max length5
Median length3
Mean length3.2197802
Min length3

Unique

Unique2 ?
Unique (%)1.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 143
78.6%
<NA> 37
 
20.3%
75.98 1
 
0.5%
75.0 1
 
0.5%

Length

2024-05-11T05:19:01.210879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:19:01.632751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 143
78.6%
na 37
 
20.3%
75.98 1
 
0.5%
75.0 1
 
0.5%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing182
Missing (%)100.0%
Memory size1.7 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing182
Missing (%)100.0%
Memory size1.7 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing182
Missing (%)100.0%
Memory size1.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031500003150000-122-2008-0000120080319<NA>3폐업2폐업20091230<NA><NA><NA><NA>33.0157290서울특별시 강서구 외발산동 424 외발산동 424번지 공판장동 3층<NA><NA>창성유통냉장(주)2009-01-19 16:54:29I2018-08-31 23:59:59.0집단급식소 식품판매업183914.93831450085.014573집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA>0001임대<NA><NA>N0.0<NA><NA><NA>
131500003150000-122-2008-0000220080320<NA>3폐업2폐업20170329<NA><NA><NA>02 26076263<NA>157801서울특별시 강서구 가양동 231-4서울특별시 강서구 양천로47나길 48-5 (가양동)7521(주)마라식품2017-03-28 15:31:26I2018-08-31 23:59:59.0집단급식소 식품판매업185826.642871452250.028523집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231500003150000-122-2008-0000320080321<NA>3폐업2폐업20150306<NA><NA><NA>0226049800245.68157910서울특별시 강서구 화곡동 933-12 (1,2층)서울특별시 강서구 월정로14길 19 (화곡동,(1,2층))7780(주)하나푸드2008-03-21 15:32:58I2018-08-31 23:59:59.0집단급식소 식품판매업185956.388117447557.680594집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
331500003150000-122-2008-0000420080324<NA>3폐업2폐업20100330<NA><NA><NA><NA>60.0157816서울특별시 강서구 공항동 1350-7 1층<NA><NA>웰빙팝(주)2010-01-18 10:14:53I2018-08-31 23:59:59.0집단급식소 식품판매업183872.535394450365.986631집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA>2임대<NA><NA>N0.0<NA><NA><NA>
431500003150000-122-2008-0000520080324<NA>3폐업2폐업20120716<NA><NA><NA>02 26409273122.0157290서울특별시 강서구 외발산동 427 청과물동 1층<NA><NA>(주)민수청과2012-07-12 15:22:50I2018-08-31 23:59:59.0집단급식소 식품판매업184148.571467450166.360535집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA>0002임대<NA><NA>N0.0<NA><NA><NA>
531500003150000-122-2008-0000620080415<NA>3폐업2폐업20100224<NA><NA><NA>02 26613913592.0157847서울특별시 강서구 방화동 273-5<NA><NA>(주)대동식품2008-04-15 14:10:15I2018-08-31 23:59:59.0집단급식소 식품판매업<NA><NA>집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA>2<NA>임대<NA><NA>N0.0<NA><NA><NA>
631500003150000-122-2008-0000720080424<NA>3폐업2폐업20150114<NA><NA><NA><NA>172.0157230서울특별시 강서구 개화동 552-4 1층서울특별시 강서구 개화동로13길 6-19 (개화동,1층)7504철원농협잡곡서울영업소2015-01-15 08:46:39I2018-08-31 23:59:59.0집단급식소 식품판매업182418.857874452774.340726집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA>0010임대<NA><NA>N0.0<NA><NA><NA>
731500003150000-122-2008-0000820080501<NA>3폐업2폐업20140307<NA><NA><NA>02 26699202171.4157290서울특별시 강서구 외발산동 424 공판장 냉장창고동 1층, 지상6층서울특별시 강서구 발산로 24 (외발산동,공판장 냉장창고동 1층, 지상6층)7644수산업협동조합중앙회(수협단체급식사업단)2012-07-12 15:24:46I2018-08-31 23:59:59.0집단급식소 식품판매업183914.93831450085.014573집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA>0003임대<NA><NA>N0.0<NA><NA><NA>
831500003150000-122-2008-0000920080502<NA>3폐업2폐업20090401<NA><NA><NA>02 3664821390.0157864서울특별시 강서구 염창동 282-26 3층<NA><NA>용원 인스타 푸드2008-05-02 16:38:59I2018-08-31 23:59:59.0집단급식소 식품판매업188783.060729449449.350136집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA>0020임대<NA><NA>N0.0<NA><NA><NA>
931500003150000-122-2008-0001020080508<NA>3폐업2폐업20190612<NA><NA><NA>02 2658147492.13157811서울특별시 강서구 공항동 21-17 2층서울특별시 강서구 공항대로7길 35, 2층 (공항동)7619삼경유통2019-06-12 15:34:56U2019-06-14 02:40:00.0집단급식소 식품판매업183424.67291451177.270182집단급식소 식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
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17331500003150000-122-2023-000022023-03-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>102.25157-810서울특별시 강서구 가양동 1488 가양프라자 4층 406호서울특별시 강서구 허준로 198, 가양프라자 4층 406호 (가양동)7532스파클주식회사2023-03-22 10:32:56I2022-12-02 22:04:00.0집단급식소 식품판매업187582.851732451006.669082<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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17531500003150000-122-2023-000042023-04-27<NA>1영업/정상1영업<NA><NA><NA><NA>022661905531.85157-816서울특별시 강서구 공항동 1347-3 1층 101호서울특별시 강서구 방화대로6바길 15-19, 1층 101호 (공항동)7645케이푸드2023-04-27 14:44:32I2022-12-03 22:09:00.0집단급식소 식품판매업183971.676444450430.529935<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17631500003150000-122-2023-000052023-04-27<NA>1영업/정상1영업<NA><NA><NA><NA>022663605927.44157-816서울특별시 강서구 공항동 1347-3 1층 102호서울특별시 강서구 방화대로6바길 15-19, 1층 102호 (공항동)7645현이푸드2023-04-27 14:53:55I2022-12-03 22:09:00.0집단급식소 식품판매업183971.676444450430.529935<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17731500003150000-122-2023-000062023-07-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.0157-210서울특별시 강서구 마곡동 772-5 리더스퀘어마곡 A동 6층 609-C9호서울특별시 강서구 마곡중앙6로 45, 리더스퀘어마곡 A동 6층 609-C9호 (마곡동)7802시오코리아2023-07-07 14:19:55I2022-12-07 00:09:00.0집단급식소 식품판매업185127.285385450939.221091<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17831500003150000-122-2023-000072023-08-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3157-210서울특별시 강서구 마곡동 797-7 퀸즈파크텐 B동 916(A05)호서울특별시 강서구 마곡중앙6로 66, 퀸즈파크텐 B동 916(A05)호 (마곡동)7803새봄푸드2023-08-08 15:33:25I2022-12-07 23:00:00.0집단급식소 식품판매업185292.766644450863.026924<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17931500003150000-122-2023-000082023-09-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.0157-210서울특별시 강서구 마곡동 772-5 리더스퀘어마곡 612-A15호서울특별시 강서구 마곡중앙6로 45, 리더스퀘어마곡 A동 6층 612-A15호 (마곡동)7802서울통상2023-09-22 10:25:02I2022-12-08 22:04:00.0집단급식소 식품판매업185127.285385450939.221091<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18031500003150000-122-2024-000012024-02-01<NA>1영업/정상1영업<NA><NA><NA><NA>026958935040.17157-930서울특별시 강서구 등촌동 696 세신그린코아빌딩서울특별시 강서구 공항대로41길 51, 세신그린코아빌딩 2층 218호 (등촌동)7586썬에이블2024-02-01 16:48:29I2023-12-02 00:03:00.0집단급식소 식품판매업186301.87554450896.992533<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18131500003150000-122-2024-000022024-03-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>7.2157-210서울특별시 강서구 마곡동 772-5 리더스퀘어마곡서울특별시 강서구 마곡중앙6로 45, 리더스퀘어마곡 A동 6층 602-A29호 (마곡동)7802동원강서양천지점2024-03-13 09:43:33I2023-12-02 23:06:00.0집단급식소 식품판매업185127.285385450939.221091<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>