Overview

Dataset statistics

Number of variables17
Number of observations84
Missing cells9
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 KiB
Average record size in memory141.6 B

Variable types

Categorical5
Text7
Numeric4
DateTime1

Alerts

운영법인분류(소) is highly overall correlated with 운영법인분류(대)High correlation
운영법인분류(대) is highly overall correlated with 운영법인분류(소)High correlation
정제우편번호 is highly overall correlated with 정제WGS84위도 and 1 other fieldsHigh correlation
정제WGS84위도 is highly overall correlated with 정제우편번호 and 1 other fieldsHigh correlation
정제WGS84경도 is highly overall correlated with 시군구High correlation
시군구 is highly overall correlated with 정제우편번호 and 2 other fieldsHigh correlation
신고구분 is highly imbalanced (62.9%)Imbalance
정제도로명주소 has 6 (7.1%) missing valuesMissing
정제우편번호 has 1 (1.2%) missing valuesMissing
정제WGS84위도 has 1 (1.2%) missing valuesMissing
정제WGS84경도 has 1 (1.2%) missing valuesMissing
사업장명 has unique valuesUnique
담당자 has unique valuesUnique

Reproduction

Analysis started2024-03-12 23:36:24.795399
Analysis finished2024-03-12 23:36:27.515048
Duration2.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Memory size804.0 B
화성시
8 
이천시
 
5
용인시
 
5
고양시
 
5
수원시
 
5
Other values (25)
56 

Length

Max length4
Median length3
Mean length3.047619
Min length3

Unique

Unique10 ?
Unique (%)11.9%

Sample

1st row가평군
2nd row고양시
3rd row고양시
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
화성시 8
 
9.5%
이천시 5
 
6.0%
용인시 5
 
6.0%
고양시 5
 
6.0%
수원시 5
 
6.0%
평택시 5
 
6.0%
안양시 4
 
4.8%
안산시 4
 
4.8%
안성시 4
 
4.8%
부천시 4
 
4.8%
Other values (20) 35
41.7%

Length

2024-03-13T08:36:27.565027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화성시 8
 
9.5%
용인시 5
 
6.0%
고양시 5
 
6.0%
수원시 5
 
6.0%
평택시 5
 
6.0%
이천시 5
 
6.0%
부천시 4
 
4.8%
안성시 4
 
4.8%
안산시 4
 
4.8%
안양시 4
 
4.8%
Other values (20) 35
41.7%

형태
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
푸드뱅크
69 
푸드마켓
15 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row푸드뱅크
2nd row푸드마켓
3rd row푸드뱅크
4th row푸드뱅크
5th row푸드뱅크

Common Values

ValueCountFrequency (%)
푸드뱅크 69
82.1%
푸드마켓 15
 
17.9%

Length

2024-03-13T08:36:27.653711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:36:27.731734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
푸드뱅크 69
82.1%
푸드마켓 15
 
17.9%

사업장명
Text

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-03-13T08:36:27.894198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.7619048
Min length6

Characters and Unicode

Total characters736
Distinct characters132
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)100.0%

Sample

1st row가평군푸드뱅크
2nd row고양시한아름푸드마켓
3rd row고양시흰돌기초푸드뱅크
4th row덕양행신기초푸드뱅크
5th row고양시문촌7푸드뱅크
ValueCountFrequency (%)
가평군푸드뱅크 1
 
1.2%
아름다운동행 1
 
1.2%
이천시선양푸드뱅크 1
 
1.2%
사랑나눔이천푸드마켓 1
 
1.2%
나누리푸드뱅크 1
 
1.2%
의정부푸드뱅크마켓 1
 
1.2%
의왕시푸드뱅크 1
 
1.2%
용인사랑나눔푸드뱅크 1
 
1.2%
희망나눔푸드뱅크 1
 
1.2%
푸드뱅크 1
 
1.2%
Other values (75) 75
88.2%
2024-03-13T08:36:28.212346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
푸 85
 
11.5%
드 85
 
11.5%
뱅 74
 
10.1%
크 74
 
10.1%
시 33
 
4.5%
마 17
 
2.3%
켓 16
 
2.2%
나 15
 
2.0%
양 13
 
1.8%
눔 12
 
1.6%
Other values (122) 312
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 729
99.0%
Decimal Number 4
 
0.5%
Other Punctuation 2
 
0.3%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
푸 85
 
11.7%
드 85
 
11.7%
뱅 74
 
10.2%
크 74
 
10.2%
시 33
 
4.5%
마 17
 
2.3%
켓 16
 
2.2%
나 15
 
2.1%
양 13
 
1.8%
눔 12
 
1.6%
Other values (115) 305
41.8%
Decimal Number
ValueCountFrequency (%)
1 1
25.0%
2 1
25.0%
9 1
25.0%
7 1
25.0%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 729
99.0%
Common 7
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
푸 85
 
11.7%
드 85
 
11.7%
뱅 74
 
10.2%
크 74
 
10.2%
시 33
 
4.5%
마 17
 
2.3%
켓 16
 
2.2%
나 15
 
2.1%
양 13
 
1.8%
눔 12
 
1.6%
Other values (115) 305
41.8%
Common
ValueCountFrequency (%)
1
14.3%
1 1
14.3%
2 1
14.3%
& 1
14.3%
9 1
14.3%
7 1
14.3%
· 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 729
99.0%
ASCII 6
 
0.8%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
푸 85
 
11.7%
드 85
 
11.7%
뱅 74
 
10.2%
크 74
 
10.2%
시 33
 
4.5%
마 17
 
2.3%
켓 16
 
2.2%
나 15
 
2.1%
양 13
 
1.8%
눔 12
 
1.6%
Other values (115) 305
41.8%
ASCII
ValueCountFrequency (%)
1
16.7%
1 1
16.7%
2 1
16.7%
& 1
16.7%
9 1
16.7%
7 1
16.7%
None
ValueCountFrequency (%)
· 1
100.0%

사업자등록번호
Real number (ℝ)

Distinct78
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1613051 × 109
Minimum1.1482688 × 109
Maximum7.2582 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-03-13T08:36:28.322025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1482688 × 109
5-th percentile1.2482189 × 109
Q11.2780097 × 109
median1.353118 × 109
Q32.2907617 × 109
95-th percentile5.9492768 × 109
Maximum7.2582 × 109
Range6.1099312 × 109
Interquartile range (IQR)1.012752 × 109

Descriptive statistics

Standard deviation1.5817596 × 109
Coefficient of variation (CV)0.73185392
Kurtosis2.4576596
Mean2.1613051 × 109
Median Absolute Deviation (MAD)85109176
Skewness1.8717254
Sum1.8154963 × 1011
Variance2.5019635 × 1018
MonotonicityNot monotonic
2024-03-13T08:36:28.434671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1258269599 2
 
2.4%
1428201731 2
 
2.4%
4058263491 2
 
2.4%
1288205046 2
 
2.4%
1308207969 2
 
2.4%
1418262695 2
 
2.4%
1268262454 1
 
1.2%
5218200385 1
 
1.2%
2438000458 1
 
1.2%
1328202242 1
 
1.2%
Other values (68) 68
81.0%
ValueCountFrequency (%)
1148268834 1
1.2%
1238208091 1
1.2%
1238209673 1
1.2%
1238209921 1
1.2%
1248208454 1
1.2%
1248277801 1
1.2%
1258209698 1
1.2%
1258265593 1
1.2%
1258267999 1
1.2%
1258269599 2
2.4%
ValueCountFrequency (%)
7258200027 1
1.2%
7078200067 1
1.2%
6858000934 1
1.2%
6278001617 1
1.2%
6078290314 1
1.2%
5218200385 1
1.2%
5148289698 1
1.2%
4968002268 1
1.2%
4878200203 1
1.2%
4488200232 1
1.2%

신고구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
당연신고
78 
임의신고
 
6

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row당연신고
2nd row임의신고
3rd row당연신고
4th row당연신고
5th row당연신고

Common Values

ValueCountFrequency (%)
당연신고 78
92.9%
임의신고 6
 
7.1%

Length

2024-03-13T08:36:28.544540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:36:28.623236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
당연신고 78
92.9%
임의신고 6
 
7.1%

운영단체명
Text

Distinct77
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-03-13T08:36:28.787724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length9.6428571
Min length3

Characters and Unicode

Total characters810
Distinct characters164
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)83.3%

Sample

1st row가평푸드뱅크
2nd row고양시흰돌종합사회복지관
3rd row고양시흰돌종합사회복지관
4th row고양시 덕양행신종합사회복지관
5th row고양시문촌7종합사회복지관
ValueCountFrequency (%)
사단법인 8
 
7.1%
희망나눔터 2
 
1.8%
사회복지법인 2
 
1.8%
대한예수교장로회 2
 
1.8%
여럿이 2
 
1.8%
나눔 2
 
1.8%
평택푸드뱅크 2
 
1.8%
사회적협동조합 2
 
1.8%
심곡동종합사회복지관 2
 
1.8%
수원시우만종합사회복지관 2
 
1.8%
Other values (84) 87
77.0%
2024-03-13T08:36:29.091471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 47
 
5.8%
회 41
 
5.1%
지 32
 
4.0%
복 32
 
4.0%
푸 30
 
3.7%
29
 
3.6%
드 29
 
3.6%
크 28
 
3.5%
뱅 28
 
3.5%
시 19
 
2.3%
Other values (154) 495
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 766
94.6%
Space Separator 29
 
3.6%
Decimal Number 7
 
0.9%
Open Punctuation 4
 
0.5%
Close Punctuation 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 47
 
6.1%
회 41
 
5.4%
지 32
 
4.2%
복 32
 
4.2%
푸 30
 
3.9%
드 29
 
3.8%
크 28
 
3.7%
뱅 28
 
3.7%
시 19
 
2.5%
합 18
 
2.3%
Other values (145) 462
60.3%
Decimal Number
ValueCountFrequency (%)
6 2
28.6%
2 1
14.3%
5 1
14.3%
0 1
14.3%
9 1
14.3%
7 1
14.3%
Space Separator
ValueCountFrequency (%)
29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 766
94.6%
Common 44
 
5.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 47
 
6.1%
회 41
 
5.4%
지 32
 
4.2%
복 32
 
4.2%
푸 30
 
3.9%
드 29
 
3.8%
크 28
 
3.7%
뱅 28
 
3.7%
시 19
 
2.5%
합 18
 
2.3%
Other values (145) 462
60.3%
Common
ValueCountFrequency (%)
29
65.9%
( 4
 
9.1%
) 4
 
9.1%
6 2
 
4.5%
2 1
 
2.3%
5 1
 
2.3%
0 1
 
2.3%
9 1
 
2.3%
7 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 766
94.6%
ASCII 44
 
5.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 47
 
6.1%
회 41
 
5.4%
지 32
 
4.2%
복 32
 
4.2%
푸 30
 
3.9%
드 29
 
3.8%
크 28
 
3.7%
뱅 28
 
3.7%
시 19
 
2.5%
합 18
 
2.3%
Other values (145) 462
60.3%
ASCII
ValueCountFrequency (%)
29
65.9%
( 4
 
9.1%
) 4
 
9.1%
6 2
 
4.5%
2 1
 
2.3%
5 1
 
2.3%
0 1
 
2.3%
9 1
 
2.3%
7 1
 
2.3%

운영법인분류(대)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
개인 운영
30 
기타
29 
법인 운영
25 

Length

Max length5
Median length5
Mean length3.9642857
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 운영 30
35.7%
기타 29
34.5%
법인 운영 25
29.8%

Length

2024-03-13T08:36:29.201640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:36:29.285285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영 55
39.6%
개인 30
21.6%
기타 29
20.9%
법인 25
18.0%

운영법인분류(소)
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size804.0 B
비영리 민간 단체·시설
29 
푸드뱅크·마켓 자체신고운영
19 
사단법인
17 
종교시설·단체
11 
사회복지법인
7 

Length

Max length14
Median length12
Mean length9.5833333
Min length4

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st row종교시설·단체
2nd row비영리 민간 단체·시설
3rd row비영리 민간 단체·시설
4th row비영리 민간 단체·시설
5th row비영리 민간 단체·시설

Common Values

ValueCountFrequency (%)
비영리 민간 단체·시설 29
34.5%
푸드뱅크·마켓 자체신고운영 19
22.6%
사단법인 17
20.2%
종교시설·단체 11
 
13.1%
사회복지법인 7
 
8.3%
종교법인 1
 
1.2%

Length

2024-03-13T08:36:29.381418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:36:29.479028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비영리 29
18.0%
민간 29
18.0%
단체·시설 29
18.0%
푸드뱅크·마켓 19
11.8%
자체신고운영 19
11.8%
사단법인 17
10.6%
종교시설·단체 11
 
6.8%
사회복지법인 7
 
4.3%
종교법인 1
 
0.6%

대표자명
Text

Distinct76
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-03-13T08:36:29.708288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0357143
Min length2

Characters and Unicode

Total characters255
Distinct characters90
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)81.0%

Sample

1st row정현주
2nd row심재경
3rd row심재경
4th row김진우
5th row윤영
ValueCountFrequency (%)
심재경 2
 
2.4%
연정준 2
 
2.4%
윤상형 2
 
2.4%
최명성 2
 
2.4%
차현아 2
 
2.4%
정영호 2
 
2.4%
이대영 2
 
2.4%
황재경 2
 
2.4%
강동연 1
 
1.2%
이성관 1
 
1.2%
Other values (67) 67
78.8%
2024-03-13T08:36:30.053221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 14
 
5.5%
이 14
 
5.5%
재 13
 
5.1%
정 11
 
4.3%
성 10
 
3.9%
경 8
 
3.1%
영 7
 
2.7%
박 7
 
2.7%
윤 7
 
2.7%
호 7
 
2.7%
Other values (80) 157
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 254
99.6%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 14
 
5.5%
이 14
 
5.5%
재 13
 
5.1%
정 11
 
4.3%
성 10
 
3.9%
경 8
 
3.1%
영 7
 
2.8%
박 7
 
2.8%
윤 7
 
2.8%
호 7
 
2.8%
Other values (79) 156
61.4%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 254
99.6%
Common 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 14
 
5.5%
이 14
 
5.5%
재 13
 
5.1%
정 11
 
4.3%
성 10
 
3.9%
경 8
 
3.1%
영 7
 
2.8%
박 7
 
2.8%
윤 7
 
2.8%
호 7
 
2.8%
Other values (79) 156
61.4%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 254
99.6%
ASCII 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 14
 
5.5%
이 14
 
5.5%
재 13
 
5.1%
정 11
 
4.3%
성 10
 
3.9%
경 8
 
3.1%
영 7
 
2.8%
박 7
 
2.8%
윤 7
 
2.8%
호 7
 
2.8%
Other values (79) 156
61.4%
ASCII
ValueCountFrequency (%)
1
100.0%

센터전화번호
Text

Distinct82
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-03-13T08:36:30.302326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.107143
Min length12

Characters and Unicode

Total characters1017
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

Unique80 ?
Unique (%)95.2%

Sample

1st row031-581-2727
2nd row031-902-1377
3rd row031-905-3400
4th row031-839-6000
5th row031-916-4071
ValueCountFrequency (%)
031-8059-1677 2
 
2.4%
031-618-1877 2
 
2.4%
031-631-1377 1
 
1.2%
031-322-1377 1
 
1.2%
031-581-2727 1
 
1.2%
031-378-1377 1
 
1.2%
031-829-6114 1
 
1.2%
031-458-3027 1
 
1.2%
031-281-1377 1
 
1.2%
031-333-4646 1
 
1.2%
Other values (72) 72
85.7%
2024-03-13T08:36:30.616566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 168
16.5%
1 159
15.6%
3 149
14.7%
0 143
14.1%
7 113
11.1%
6 57
 
5.6%
8 55
 
5.4%
2 47
 
4.6%
5 46
 
4.5%
4 45
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 849
83.5%
Dash Punctuation 168
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 159
18.7%
3 149
17.6%
0 143
16.8%
7 113
13.3%
6 57
 
6.7%
8 55
 
6.5%
2 47
 
5.5%
5 46
 
5.4%
4 45
 
5.3%
9 35
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1017
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 168
16.5%
1 159
15.6%
3 149
14.7%
0 143
14.1%
7 113
11.1%
6 57
 
5.6%
8 55
 
5.4%
2 47
 
4.6%
5 46
 
4.5%
4 45
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1017
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 168
16.5%
1 159
15.6%
3 149
14.7%
0 143
14.1%
7 113
11.1%
6 57
 
5.6%
8 55
 
5.4%
2 47
 
4.6%
5 46
 
4.5%
4 45
 
4.4%

담당자
Text

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-03-13T08:36:30.849568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters252
Distinct characters94
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)100.0%

Sample

1st row강성수
2nd row구동훈
3rd row김나연
4th row조형연
5th row윤형석
ValueCountFrequency (%)
강성수 1
 
1.2%
윤상국 1
 
1.2%
송상섭 1
 
1.2%
한정현 1
 
1.2%
김영수 1
 
1.2%
한보라 1
 
1.2%
조은호 1
 
1.2%
이선옥 1
 
1.2%
강정희 1
 
1.2%
김종임 1
 
1.2%
Other values (74) 74
88.1%
2024-03-13T08:36:31.181529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 17
 
6.7%
정 9
 
3.6%
이 8
 
3.2%
박 8
 
3.2%
현 8
 
3.2%
재 8
 
3.2%
성 7
 
2.8%
윤 6
 
2.4%
경 6
 
2.4%
영 5
 
2.0%
Other values (84) 170
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 17
 
6.7%
정 9
 
3.6%
이 8
 
3.2%
박 8
 
3.2%
현 8
 
3.2%
재 8
 
3.2%
성 7
 
2.8%
윤 6
 
2.4%
경 6
 
2.4%
영 5
 
2.0%
Other values (84) 170
67.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 17
 
6.7%
정 9
 
3.6%
이 8
 
3.2%
박 8
 
3.2%
현 8
 
3.2%
재 8
 
3.2%
성 7
 
2.8%
윤 6
 
2.4%
경 6
 
2.4%
영 5
 
2.0%
Other values (84) 170
67.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 252
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 17
 
6.7%
정 9
 
3.6%
이 8
 
3.2%
박 8
 
3.2%
현 8
 
3.2%
재 8
 
3.2%
성 7
 
2.8%
윤 6
 
2.4%
경 6
 
2.4%
영 5
 
2.0%
Other values (84) 170
67.5%

정제지번주소
Text

Distinct78
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-03-13T08:36:31.408520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length27
Mean length22.190476
Min length15

Characters and Unicode

Total characters1864
Distinct characters143
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)85.7%

Sample

1st row경기도 가평군 가평읍 달전리 336-28번지
2nd row경기도 고양시 일산동구 백석동 1343번지 흰돌마을4단지아파트
3rd row경기도 고양시 일산동구 백석동 1343번지 흰돌마을4단지아파트
4th row경기도 고양시 덕양구 행신동 1064-1번지
5th row경기도 고양시 일산서구 주엽동 14번지 문촌마을7단지아파트
ValueCountFrequency (%)
경기도 84
 
21.3%
화성시 8
 
2.0%
이천시 5
 
1.3%
고양시 5
 
1.3%
용인시 5
 
1.3%
수원시 5
 
1.3%
평택시 5
 
1.3%
안산시 4
 
1.0%
안양시 4
 
1.0%
안성시 4
 
1.0%
Other values (211) 265
67.3%
2024-03-13T08:36:31.782729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
310
 
16.6%
지 90
 
4.8%
기 86
 
4.6%
도 85
 
4.6%
경 84
 
4.5%
번 84
 
4.5%
시 83
 
4.5%
- 69
 
3.7%
1 64
 
3.4%
동 62
 
3.3%
Other values (133) 847
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1135
60.9%
Decimal Number 350
 
18.8%
Space Separator 310
 
16.6%
Dash Punctuation 69
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 90
 
7.9%
기 86
 
7.6%
도 85
 
7.5%
경 84
 
7.4%
번 84
 
7.4%
시 83
 
7.3%
동 62
 
5.5%
구 32
 
2.8%
리 27
 
2.4%
안 21
 
1.9%
Other values (121) 481
42.4%
Decimal Number
ValueCountFrequency (%)
1 64
18.3%
3 47
13.4%
4 37
10.6%
2 34
9.7%
5 33
9.4%
7 31
8.9%
8 29
8.3%
6 28
8.0%
9 26
7.4%
0 21
 
6.0%
Space Separator
ValueCountFrequency (%)
310
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1135
60.9%
Common 729
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 90
 
7.9%
기 86
 
7.6%
도 85
 
7.5%
경 84
 
7.4%
번 84
 
7.4%
시 83
 
7.3%
동 62
 
5.5%
구 32
 
2.8%
리 27
 
2.4%
안 21
 
1.9%
Other values (121) 481
42.4%
Common
ValueCountFrequency (%)
310
42.5%
- 69
 
9.5%
1 64
 
8.8%
3 47
 
6.4%
4 37
 
5.1%
2 34
 
4.7%
5 33
 
4.5%
7 31
 
4.3%
8 29
 
4.0%
6 28
 
3.8%
Other values (2) 47
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1135
60.9%
ASCII 729
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
310
42.5%
- 69
 
9.5%
1 64
 
8.8%
3 47
 
6.4%
4 37
 
5.1%
2 34
 
4.7%
5 33
 
4.5%
7 31
 
4.3%
8 29
 
4.0%
6 28
 
3.8%
Other values (2) 47
 
6.4%
Hangul
ValueCountFrequency (%)
지 90
 
7.9%
기 86
 
7.6%
도 85
 
7.5%
경 84
 
7.4%
번 84
 
7.4%
시 83
 
7.3%
동 62
 
5.5%
구 32
 
2.8%
리 27
 
2.4%
안 21
 
1.9%
Other values (121) 481
42.4%

정제도로명주소
Text

MISSING 

Distinct73
Distinct (%)93.6%
Missing6
Missing (%)7.1%
Memory size804.0 B
2024-03-13T08:36:32.016964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length19.089744
Min length13

Characters and Unicode

Total characters1489
Distinct characters146
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)87.2%

Sample

1st row경기도 가평군 가평읍 달전로 44
2nd row경기도 고양시 덕양구 서정마을2로 13
3rd row경기도 광명시 광삼로 9
4th row경기도 광주시 곤지암읍 곤지암로11번길 8
5th row경기도 광주시 광주대로 11-3
ValueCountFrequency (%)
경기도 78
 
21.7%
화성시 8
 
2.2%
수원시 5
 
1.4%
이천시 5
 
1.4%
평택시 5
 
1.4%
용인시 5
 
1.4%
안산시 4
 
1.1%
부천시 4
 
1.1%
안양시 4
 
1.1%
안성시 4
 
1.1%
Other values (194) 237
66.0%
2024-03-13T08:36:32.614873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
281
18.9%
경 81
 
5.4%
기 81
 
5.4%
도 80
 
5.4%
시 77
 
5.2%
로 66
 
4.4%
1 57
 
3.8%
길 42
 
2.8%
3 35
 
2.4%
2 30
 
2.0%
Other values (136) 659
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 932
62.6%
Space Separator 281
 
18.9%
Decimal Number 260
 
17.5%
Dash Punctuation 16
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 81
 
8.7%
기 81
 
8.7%
도 80
 
8.6%
시 77
 
8.3%
로 66
 
7.1%
길 42
 
4.5%
구 26
 
2.8%
번 26
 
2.8%
안 23
 
2.5%
천 16
 
1.7%
Other values (124) 414
44.4%
Decimal Number
ValueCountFrequency (%)
1 57
21.9%
3 35
13.5%
2 30
11.5%
6 25
9.6%
4 22
 
8.5%
5 21
 
8.1%
8 19
 
7.3%
7 19
 
7.3%
9 16
 
6.2%
0 16
 
6.2%
Space Separator
ValueCountFrequency (%)
281
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 932
62.6%
Common 557
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 81
 
8.7%
기 81
 
8.7%
도 80
 
8.6%
시 77
 
8.3%
로 66
 
7.1%
길 42
 
4.5%
구 26
 
2.8%
번 26
 
2.8%
안 23
 
2.5%
천 16
 
1.7%
Other values (124) 414
44.4%
Common
ValueCountFrequency (%)
281
50.4%
1 57
 
10.2%
3 35
 
6.3%
2 30
 
5.4%
6 25
 
4.5%
4 22
 
3.9%
5 21
 
3.8%
8 19
 
3.4%
7 19
 
3.4%
- 16
 
2.9%
Other values (2) 32
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 932
62.6%
ASCII 557
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
281
50.4%
1 57
 
10.2%
3 35
 
6.3%
2 30
 
5.4%
6 25
 
4.5%
4 22
 
3.9%
5 21
 
3.8%
8 19
 
3.4%
7 19
 
3.4%
- 16
 
2.9%
Other values (2) 32
 
5.7%
Hangul
ValueCountFrequency (%)
경 81
 
8.7%
기 81
 
8.7%
도 80
 
8.6%
시 77
 
8.3%
로 66
 
7.1%
길 42
 
4.5%
구 26
 
2.8%
번 26
 
2.8%
안 23
 
2.5%
천 16
 
1.7%
Other values (124) 414
44.4%

등록일자
Date

Distinct82
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
Minimum1998-01-02 00:00:00
Maximum2022-02-17 00:00:00
2024-03-13T08:36:32.732234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:32.839040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

정제우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct77
Distinct (%)92.8%
Missing1
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean14639.663
Minimum10012
Maximum18598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-03-13T08:36:32.952962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10012
5-th percentile10394
Q112090
median14750
Q317370.5
95-th percentile18426
Maximum18598
Range8586
Interquartile range (IQR)5280.5

Descriptive statistics

Standard deviation2800.7617
Coefficient of variation (CV)0.19131327
Kurtosis-1.4239023
Mean14639.663
Median Absolute Deviation (MAD)2626
Skewness-0.15031812
Sum1215092
Variance7844265.9
MonotonicityNot monotonic
2024-03-13T08:36:33.067522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10448 2
 
2.4%
17919 2
 
2.4%
14535 2
 
2.4%
10879 2
 
2.4%
16464 2
 
2.4%
18598 2
 
2.4%
12661 1
 
1.2%
17376 1
 
1.2%
11659 1
 
1.2%
11788 1
 
1.2%
Other values (67) 67
79.8%
ValueCountFrequency (%)
10012 1
1.2%
10057 1
1.2%
10106 1
1.2%
10378 1
1.2%
10388 1
1.2%
10448 2
2.4%
10486 1
1.2%
10836 1
1.2%
10879 2
2.4%
11031 1
1.2%
ValueCountFrequency (%)
18598 2
2.4%
18553 1
1.2%
18428 1
1.2%
18427 1
1.2%
18417 1
1.2%
18332 1
1.2%
18329 1
1.2%
18130 1
1.2%
17941 1
1.2%
17919 2
2.4%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct77
Distinct (%)92.8%
Missing1
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean37.402231
Minimum36.983366
Maximum38.017151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-03-13T08:36:33.183492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.983366
5-th percentile37.012222
Q137.242615
median37.352342
Q337.606466
95-th percentile37.835226
Maximum38.017151
Range1.0337845
Interquartile range (IQR)0.36385093

Descriptive statistics

Standard deviation0.24769895
Coefficient of variation (CV)0.0066225716
Kurtosis-0.55558547
Mean37.402231
Median Absolute Deviation (MAD)0.15284329
Skewness0.41170179
Sum3104.3852
Variance0.06135477
MonotonicityNot monotonic
2024-03-13T08:36:33.313901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.642720602 2
 
2.4%
36.9877931746 2
 
2.4%
37.5081027851 2
 
2.4%
37.7277792721 2
 
2.4%
37.2699161031 2
 
2.4%
37.1304643221 2
 
2.4%
37.2124295724 1
 
1.2%
37.2774933223 1
 
1.2%
37.74586916 1
 
1.2%
37.7375215964 1
 
1.2%
Other values (67) 67
79.8%
ValueCountFrequency (%)
36.983366348 1
1.2%
36.9877931746 2
2.4%
36.990982806 1
1.2%
37.0068544283 1
1.2%
37.0605258399 1
1.2%
37.0608771929 1
1.2%
37.0741755428 1
1.2%
37.0751007637 1
1.2%
37.1304643221 2
2.4%
37.148891479 1
1.2%
ValueCountFrequency (%)
38.017150804 1
1.2%
37.9047627073 1
1.2%
37.8944758309 1
1.2%
37.8379350959 1
1.2%
37.836408075 1
1.2%
37.8245830793 1
1.2%
37.8143298785 1
1.2%
37.772772741 1
1.2%
37.74586916 1
1.2%
37.7375215964 1
1.2%

정제WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct77
Distinct (%)92.8%
Missing1
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean127.05201
Minimum126.6237
Maximum127.64022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-03-13T08:36:33.426077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.6237
5-th percentile126.70616
Q1126.85927
median127.04434
Q3127.20405
95-th percentile127.51695
Maximum127.64022
Range1.0165203
Interquartile range (IQR)0.34478111

Descriptive statistics

Standard deviation0.24797795
Coefficient of variation (CV)0.001951783
Kurtosis-0.24098088
Mean127.05201
Median Absolute Deviation (MAD)0.16185342
Skewness0.55862198
Sum10545.316
Variance0.061493062
MonotonicityNot monotonic
2024-03-13T08:36:33.555870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7845561602 2
 
2.4%
127.0867649252 2
 
2.4%
126.7737025428 2
 
2.4%
126.7058927445 2
 
2.4%
127.010449178 2
 
2.4%
126.9195390742 2
 
2.4%
127.560589742 1
 
1.2%
127.4400011737 1
 
1.2%
127.0305318572 1
 
1.2%
127.0880354938 1
 
1.2%
Other values (67) 67
79.8%
ValueCountFrequency (%)
126.6237028334 1
1.2%
126.639222291 1
1.2%
126.6788153223 1
1.2%
126.7058927445 2
2.4%
126.7086149375 1
1.2%
126.7468089481 1
1.2%
126.7564125494 1
1.2%
126.7622484517 1
1.2%
126.7737025428 2
2.4%
126.783750324 1
1.2%
ValueCountFrequency (%)
127.6402231432 1
1.2%
127.6383689142 1
1.2%
127.5892402505 1
1.2%
127.560589742 1
1.2%
127.5181780851 1
1.2%
127.5059344951 1
1.2%
127.4754121227 1
1.2%
127.4440184031 1
1.2%
127.4424453443 1
1.2%
127.4400011737 1
1.2%

Interactions

2024-03-13T08:36:26.835841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:25.982240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.272001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.543000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.903926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.052638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.350171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.624914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.984237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.128621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.407408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.691183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:27.072223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.197994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.476139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:36:26.759676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:36:33.645129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구형태사업장명사업자등록번호신고구분운영단체명운영법인분류(대)운영법인분류(소)대표자명센터전화번호담당자정제지번주소정제도로명주소등록일자정제우편번호정제WGS84위도정제WGS84경도
시군구1.0000.0001.0000.0000.0000.9990.4640.0000.9991.0001.0001.0001.0000.9891.0000.9860.948
형태0.0001.0001.0000.0000.4170.0000.1060.2960.0000.0001.0000.0000.0001.0000.0000.0000.052
사업장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사업자등록번호0.0000.0001.0001.0000.0000.9270.2800.1960.6991.0001.0000.8990.6760.9240.1520.0000.000
신고구분0.0000.4171.0000.0001.0000.0000.0000.2530.0000.0001.0000.0000.0001.0000.4500.0440.000
운영단체명0.9990.0001.0000.9270.0001.0001.0001.0001.0001.0001.0001.0001.0000.9930.9981.0000.997
운영법인분류(대)0.4640.1061.0000.2800.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.2060.3360.000
운영법인분류(소)0.0000.2961.0000.1960.2531.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.0000.352
대표자명0.9990.0001.0000.6990.0001.0001.0001.0001.0001.0001.0001.0001.0000.9920.9981.0000.998
센터전화번호1.0000.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0000.9961.0001.0001.000
담당자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
정제지번주소1.0000.0001.0000.8990.0001.0001.0001.0001.0001.0001.0001.0001.0000.9931.0001.0001.000
정제도로명주소1.0000.0001.0000.6760.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
등록일자0.9891.0001.0000.9241.0000.9931.0001.0000.9920.9961.0000.9931.0001.0000.9370.9270.973
정제우편번호1.0000.0001.0000.1520.4500.9980.2060.0000.9981.0001.0001.0001.0000.9371.0000.9170.882
정제WGS84위도0.9860.0001.0000.0000.0441.0000.3360.0001.0001.0001.0001.0001.0000.9270.9171.0000.643
정제WGS84경도0.9480.0521.0000.0000.0000.9970.0000.3520.9981.0001.0001.0001.0000.9730.8820.6431.000
2024-03-13T08:36:33.773046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구운영법인분류(소)형태신고구분운영법인분류(대)
시군구1.0000.0000.0000.0000.189
운영법인분류(소)0.0001.0000.2060.1760.981
형태0.0000.2061.0000.2730.173
신고구분0.0000.1760.2731.0000.000
운영법인분류(대)0.1890.9810.1730.0001.000
2024-03-13T08:36:33.860864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업자등록번호정제우편번호정제WGS84위도정제WGS84경도시군구형태신고구분운영법인분류(대)운영법인분류(소)
사업자등록번호1.0000.089-0.072-0.0080.0000.0000.0000.1110.090
정제우편번호0.0891.000-0.9040.2200.8310.0000.3140.0720.000
정제WGS84위도-0.072-0.9041.000-0.2880.6920.0000.0000.2010.000
정제WGS84경도-0.0080.220-0.2881.0000.5610.0090.0000.0000.185
시군구0.0000.8310.6920.5611.0000.0000.0000.1890.000
형태0.0000.0000.0000.0090.0001.0000.2730.1730.206
신고구분0.0000.3140.0000.0000.0000.2731.0000.0000.176
운영법인분류(대)0.1110.0720.2010.0000.1890.1730.0001.0000.981
운영법인분류(소)0.0900.0000.0000.1850.0000.2060.1760.9811.000

Missing values

2024-03-13T08:36:27.180602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:36:27.344217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-03-13T08:36:27.455742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군구형태사업장명사업자등록번호신고구분운영단체명운영법인분류(대)운영법인분류(소)대표자명센터전화번호담당자정제지번주소정제도로명주소등록일자정제우편번호정제WGS84위도정제WGS84경도
0가평군푸드뱅크가평군푸드뱅크1268209105당연신고가평푸드뱅크개인 운영종교시설·단체정현주031-581-2727강성수경기도 가평군 가평읍 달전리 336-28번지경기도 가평군 가평읍 달전로 442008-10-141242237.81433127.518178
1고양시푸드마켓고양시한아름푸드마켓4058263491임의신고고양시흰돌종합사회복지관기타비영리 민간 단체·시설심재경031-902-1377구동훈경기도 고양시 일산동구 백석동 1343번지 흰돌마을4단지아파트<NA>2009-11-031044837.642721126.784556
2고양시푸드뱅크고양시흰돌기초푸드뱅크4058263491당연신고고양시흰돌종합사회복지관기타비영리 민간 단체·시설심재경031-905-3400김나연경기도 고양시 일산동구 백석동 1343번지 흰돌마을4단지아파트<NA>2002-01-011044837.642721126.784556
3고양시푸드뱅크덕양행신기초푸드뱅크1148268834당연신고고양시 덕양행신종합사회복지관기타비영리 민간 단체·시설김진우031-839-6000조형연경기도 고양시 덕양구 행신동 1064-1번지경기도 고양시 덕양구 서정마을2로 132019-05-311048637.621379126.847119
4고양시푸드뱅크고양시문촌7푸드뱅크1428201731당연신고고양시문촌7종합사회복지관기타비영리 민간 단체·시설윤영031-916-4071윤형석경기도 고양시 일산서구 주엽동 14번지 문촌마을7단지아파트<NA>2002-01-011037837.674462126.756413
5고양시푸드뱅크고양시문촌9푸드뱅크1248277801임의신고문촌9사회복지관기타비영리 민간 단체·시설김신실031-917-0202김광문경기도 고양시 일산서구 주엽동 23번지 문촌마을9단지아파트<NA>2001-01-171038837.672579126.762248
6광명시푸드마켓광명시푸드뱅크마켓센터1428201731당연신고광명시푸드뱅크마켓센터개인 운영푸드뱅크·마켓 자체신고운영이광수02-2688-1377임영란경기도 광명시 광명동 34-19번지경기도 광명시 광삼로 92009-06-121421737.478182126.860118
7광주시푸드뱅크늘만나푸드뱅크1348032433당연신고늘만나푸드뱅크개인 운영푸드뱅크·마켓 자체신고운영이배영031-764-0091김창욱경기도 광주시 곤지암읍 곤지암리 343-38번지경기도 광주시 곤지암읍 곤지암로11번길 82018-11-301280437.348383127.344866
8광주시푸드뱅크광주시참사랑푸드뱅크6858000934당연신고참사랑푸드뱅크개인 운영푸드뱅크·마켓 자체신고운영박병근031-8028-8906홍대연경기도 광주시 역동 27-13번지경기도 광주시 광주대로 11-32010-06-251275837.407571127.26037
9광주시푸드뱅크광주시중앙푸드뱅크&푸드마켓1348033989당연신고광주시기독교복지문화원개인 운영종교시설·단체소양호 목사031-766-1377박홍규경기도 광주시 중대동 28-70번지경기도 광주시 고불로 40-112005-05-161276837.39436127.232744
시군구형태사업장명사업자등록번호신고구분운영단체명운영법인분류(대)운영법인분류(소)대표자명센터전화번호담당자정제지번주소정제도로명주소등록일자정제우편번호정제WGS84위도정제WGS84경도
74포천시푸드뱅크솔모루푸드뱅크1258269599당연신고솔모루푸드뱅크개인 운영푸드뱅크·마켓 자체신고운영오승현031-543-1377오승현경기도 포천시 소흘읍 송우리 589-5번지경기도 포천시 소흘읍 송우로132번길 562018-12-261117137.836408127.132524
75하남시푸드뱅크하남시푸드뱅크1288270979당연신고하남시사회복지협의회법인 운영사회복지법인유희선031-793-6920송영광경기도 하남시 덕풍동 220-7번지경기도 하남시 덕풍로81번길 182001-11-011293237.551075127.203657
76화성시푸드뱅크봉담아리푸드뱅크1298211347임의신고봉담아리푸드뱅크개인 운영푸드뱅크·마켓 자체신고운영방성남000-0000-0000방성남경기도 화성시 봉담읍 분천리 56-5번지경기도 화성시 봉담읍 동화길 1742022-02-101832937.210052126.960099
77화성시푸드뱅크사랑푸드뱅크4078268380당연신고사랑푸드뱅크후원회개인 운영푸드뱅크·마켓 자체신고운영주경선031-225-1377주경선경기도 화성시 능동 677-2번지경기도 화성시 병점중앙로 5-62019-04-021841737.199499127.044338
78화성시푸드뱅크화성여럿이함께푸드뱅크1408265665당연신고사단법인 여럿이 함께법인 운영사단법인윤상형031-613-1907장창훈경기도 화성시 능동 1158-3번지경기도 화성시 남여울3길 9-102019-06-201842837.198554127.054259
79화성시푸드뱅크화성은혜푸드뱅크1728001607당연신고은혜로교회개인 운영종교시설·단체강명우031-297-6004최경화경기도 화성시 봉담읍 왕림리 211번지경기도 화성시 봉담읍 독정길 302016-05-101833237.194961126.936612
80화성시푸드마켓화성시행복나눔푸드마켓1748261658임의신고화성시남부종합사회복지관기타비영리 민간 단체·시설정영호031-8059-1677문진우경기도 화성시 향남읍 행정리 437-3번지경기도 화성시 향남읍 행정서로3길 502012-06-131859837.130464126.919539
81화성시푸드뱅크비전푸드뱅크1298207334당연신고비전푸드뱅크개인 운영푸드뱅크·마켓 자체신고운영박재윤031-355-1277박재윤경기도 화성시 서신면 장외리 73-1번지경기도 화성시 서신면 수풀오얏길 65-112019-05-201855337.178825126.678815
82화성시푸드마켓화성시나래울푸드마켓1468000986임의신고나래울종합사회복지관법인 운영사회복지법인김정희031-8015-7400박소연경기도 화성시 능동 1130번지경기도 화성시 여울로2길 332011-11-211842737.205169127.051572
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