Overview

Dataset statistics

Number of variables44
Number of observations203
Missing cells2242
Missing cells (%)25.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory74.7 KiB
Average record size in memory376.7 B

Variable types

Categorical18
Text7
DateTime4
Unsupported8
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
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-17990/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
영업장주변구분명 is highly imbalanced (64.7%)Imbalance
총인원 is highly imbalanced (73.8%)Imbalance
본사종업원수 is highly imbalanced (71.7%)Imbalance
공장사무직종업원수 is highly imbalanced (71.7%)Imbalance
공장판매직종업원수 is highly imbalanced (71.7%)Imbalance
공장생산직종업원수 is highly imbalanced (71.7%)Imbalance
보증액 is highly imbalanced (71.7%)Imbalance
월세액 is highly imbalanced (71.7%)Imbalance
다중이용업소여부 is highly imbalanced (94.6%)Imbalance
인허가취소일자 has 203 (100.0%) missing valuesMissing
폐업일자 has 51 (25.1%) missing valuesMissing
휴업시작일자 has 203 (100.0%) missing valuesMissing
휴업종료일자 has 203 (100.0%) missing valuesMissing
재개업일자 has 203 (100.0%) missing valuesMissing
전화번호 has 79 (38.9%) missing valuesMissing
소재지면적 has 6 (3.0%) missing valuesMissing
도로명주소 has 58 (28.6%) missing valuesMissing
도로명우편번호 has 58 (28.6%) missing valuesMissing
좌표정보(X) has 11 (5.4%) missing valuesMissing
좌표정보(Y) has 11 (5.4%) missing valuesMissing
남성종사자수 has 136 (67.0%) missing valuesMissing
여성종사자수 has 130 (64.0%) missing valuesMissing
건물소유구분명 has 203 (100.0%) missing valuesMissing
다중이용업소여부 has 39 (19.2%) missing valuesMissing
시설총규모 has 39 (19.2%) missing valuesMissing
전통업소지정번호 has 203 (100.0%) missing valuesMissing
전통업소주된음식 has 203 (100.0%) missing valuesMissing
홈페이지 has 203 (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
건물소유구분명 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
남성종사자수 has 47 (23.2%) zerosZeros
여성종사자수 has 38 (18.7%) zerosZeros
시설총규모 has 5 (2.5%) zerosZeros

Reproduction

Analysis started2024-05-11 04:31:59.858233
Analysis finished2024-05-11 04:32:01.373569
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3130000
203 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 203
100.0%

Length

2024-05-11T04:32:01.534971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:01.882648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 203
100.0%

관리번호
Text

UNIQUE 

Distinct203
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-11T04:32:02.404694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4466
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

Unique203 ?
Unique (%)100.0%

Sample

1st row3130000-120-2003-00001
2nd row3130000-120-2003-00002
3rd row3130000-120-2003-00003
4th row3130000-120-2003-00004
5th row3130000-120-2003-00005
ValueCountFrequency (%)
3130000-120-2003-00001 1
 
0.5%
3130000-120-2017-00005 1
 
0.5%
3130000-120-2018-00010 1
 
0.5%
3130000-120-2016-00008 1
 
0.5%
3130000-120-2016-00009 1
 
0.5%
3130000-120-2016-00010 1
 
0.5%
3130000-120-2016-00011 1
 
0.5%
3130000-120-2016-00012 1
 
0.5%
3130000-120-2017-00001 1
 
0.5%
3130000-120-2017-00002 1
 
0.5%
Other values (193) 193
95.1%
2024-05-11T04:32:03.328014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2086
46.7%
- 609
 
13.6%
1 572
 
12.8%
2 499
 
11.2%
3 479
 
10.7%
6 41
 
0.9%
4 40
 
0.9%
8 39
 
0.9%
5 37
 
0.8%
7 32
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3857
86.4%
Dash Punctuation 609
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2086
54.1%
1 572
 
14.8%
2 499
 
12.9%
3 479
 
12.4%
6 41
 
1.1%
4 40
 
1.0%
8 39
 
1.0%
5 37
 
1.0%
7 32
 
0.8%
9 32
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 609
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4466
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2086
46.7%
- 609
 
13.6%
1 572
 
12.8%
2 499
 
11.2%
3 479
 
10.7%
6 41
 
0.9%
4 40
 
0.9%
8 39
 
0.9%
5 37
 
0.8%
7 32
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4466
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2086
46.7%
- 609
 
13.6%
1 572
 
12.8%
2 499
 
11.2%
3 479
 
10.7%
6 41
 
0.9%
4 40
 
0.9%
8 39
 
0.9%
5 37
 
0.8%
7 32
 
0.7%

인허가일자
Date

Distinct178
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2003-06-19 00:00:00
Maximum2024-03-21 00:00:00
2024-05-11T04:32:03.783571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:32:04.267832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3
152 
1
51 

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 (%)
3 152
74.9%
1 51
 
25.1%

Length

2024-05-11T04:32:04.674966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:05.021299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 152
74.9%
1 51
 
25.1%

영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
152 
영업/정상
51 

Length

Max length5
Median length2
Mean length2.7536946
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 152
74.9%
영업/정상 51
 
25.1%

Length

2024-05-11T04:32:05.326964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:05.672724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 152
74.9%
영업/정상 51
 
25.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2
152 
1
51 

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 (%)
2 152
74.9%
1 51
 
25.1%

Length

2024-05-11T04:32:06.024441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:06.341248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 152
74.9%
1 51
 
25.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
152 
영업
51 

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 152
74.9%
영업 51
 
25.1%

Length

2024-05-11T04:32:06.709564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:07.027638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 152
74.9%
영업 51
 
25.1%

폐업일자
Date

MISSING 

Distinct131
Distinct (%)86.2%
Missing51
Missing (%)25.1%
Memory size1.7 KiB
Minimum2004-05-06 00:00:00
Maximum2024-03-04 00:00:00
2024-05-11T04:32:07.360623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:32:07.775001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

전화번호
Text

MISSING 

Distinct114
Distinct (%)91.9%
Missing79
Missing (%)38.9%
Memory size1.7 KiB
2024-05-11T04:32:08.447670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.4919355
Min length7

Characters and Unicode

Total characters1177
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

Unique105 ?
Unique (%)84.7%

Sample

1st row02 7104946
2nd row02 7040856
3rd row7101999
4th row02 3639274
5th row7039163
ValueCountFrequency (%)
02 54
27.0%
2955 3
 
1.5%
753 3
 
1.5%
33920455 3
 
1.5%
031 3
 
1.5%
3730065 2
 
1.0%
7101999 2
 
1.0%
3257611 2
 
1.0%
419 2
 
1.0%
7127330 2
 
1.0%
Other values (118) 124
62.0%
2024-05-11T04:32:09.618061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 202
17.2%
2 173
14.7%
3 141
12.0%
7 112
9.5%
107
9.1%
1 103
8.8%
5 98
8.3%
6 69
 
5.9%
9 65
 
5.5%
4 57
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1070
90.9%
Space Separator 107
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 202
18.9%
2 173
16.2%
3 141
13.2%
7 112
10.5%
1 103
9.6%
5 98
9.2%
6 69
 
6.4%
9 65
 
6.1%
4 57
 
5.3%
8 50
 
4.7%
Space Separator
ValueCountFrequency (%)
107
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1177
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 202
17.2%
2 173
14.7%
3 141
12.0%
7 112
9.5%
107
9.1%
1 103
8.8%
5 98
8.3%
6 69
 
5.9%
9 65
 
5.5%
4 57
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1177
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 202
17.2%
2 173
14.7%
3 141
12.0%
7 112
9.5%
107
9.1%
1 103
8.8%
5 98
8.3%
6 69
 
5.9%
9 65
 
5.5%
4 57
 
4.8%

소재지면적
Text

MISSING 

Distinct149
Distinct (%)75.6%
Missing6
Missing (%)3.0%
Memory size1.7 KiB
2024-05-11T04:32:10.446775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.0659898
Min length3

Characters and Unicode

Total characters1195
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

Unique113 ?
Unique (%)57.4%

Sample

1st row583.00
2nd row155.64
3rd row565.00
4th row413.77
5th row215.00
ValueCountFrequency (%)
324.00 5
 
2.5%
641.00 4
 
2.0%
140.40 4
 
2.0%
129.60 3
 
1.5%
177.98 3
 
1.5%
132.00 3
 
1.5%
695.92 3
 
1.5%
267.93 3
 
1.5%
193.34 2
 
1.0%
150.72 2
 
1.0%
Other values (139) 165
83.8%
2024-05-11T04:32:11.694820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 224
18.7%
. 197
16.5%
1 122
10.2%
4 99
8.3%
2 90
7.5%
3 87
 
7.3%
8 75
 
6.3%
9 73
 
6.1%
5 72
 
6.0%
7 69
 
5.8%
Other values (2) 87
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 977
81.8%
Other Punctuation 218
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 224
22.9%
1 122
12.5%
4 99
10.1%
2 90
9.2%
3 87
 
8.9%
8 75
 
7.7%
9 73
 
7.5%
5 72
 
7.4%
7 69
 
7.1%
6 66
 
6.8%
Other Punctuation
ValueCountFrequency (%)
. 197
90.4%
, 21
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1195
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 224
18.7%
. 197
16.5%
1 122
10.2%
4 99
8.3%
2 90
7.5%
3 87
 
7.3%
8 75
 
6.3%
9 73
 
6.1%
5 72
 
6.0%
7 69
 
5.8%
Other values (2) 87
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 224
18.7%
. 197
16.5%
1 122
10.2%
4 99
8.3%
2 90
7.5%
3 87
 
7.3%
8 75
 
6.3%
9 73
 
6.1%
5 72
 
6.0%
7 69
 
5.8%
Other values (2) 87
 
7.3%

소재지우편번호
Text

Distinct67
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-11T04:32:12.717004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1182266
Min length6

Characters and Unicode

Total characters1242
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 (%)14.3%

Sample

1st row121803
2nd row121856
3rd row121873
4th row121872
5th row121859
ValueCountFrequency (%)
121835 14
 
6.9%
121828 13
 
6.4%
121872 12
 
5.9%
121854 10
 
4.9%
121904 9
 
4.4%
121859 7
 
3.4%
121805 6
 
3.0%
121801 6
 
3.0%
121270 5
 
2.5%
121010 5
 
2.5%
Other values (57) 116
57.1%
2024-05-11T04:32:14.095650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 449
36.2%
2 257
20.7%
8 188
15.1%
0 78
 
6.3%
5 61
 
4.9%
7 46
 
3.7%
4 45
 
3.6%
9 42
 
3.4%
3 34
 
2.7%
- 24
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1218
98.1%
Dash Punctuation 24
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 449
36.9%
2 257
21.1%
8 188
15.4%
0 78
 
6.4%
5 61
 
5.0%
7 46
 
3.8%
4 45
 
3.7%
9 42
 
3.4%
3 34
 
2.8%
6 18
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1242
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 449
36.2%
2 257
20.7%
8 188
15.1%
0 78
 
6.3%
5 61
 
4.9%
7 46
 
3.7%
4 45
 
3.6%
9 42
 
3.4%
3 34
 
2.7%
- 24
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1242
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 449
36.2%
2 257
20.7%
8 188
15.1%
0 78
 
6.3%
5 61
 
4.9%
7 46
 
3.7%
4 45
 
3.6%
9 42
 
3.4%
3 34
 
2.7%
- 24
 
1.9%

지번주소
Text

Distinct173
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-11T04:32:14.736668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length37
Mean length27.477833
Min length18

Characters and Unicode

Total characters5578
Distinct characters236
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)73.9%

Sample

1st row서울특별시 마포구 공덕동 254-5번지 (신용보증기금)
2nd row서울특별시 마포구 신수동 371-1번지 신수중학교
3rd row서울특별시 마포구 염리동 150번지 동도중고등학교
4th row서울특별시 마포구 염리동 85-2번지
5th row서울특별시 마포구 아현동 267-1번지 아현중학교
ValueCountFrequency (%)
서울특별시 203
19.7%
마포구 203
19.7%
상암동 35
 
3.4%
공덕동 28
 
2.7%
상수동 19
 
1.8%
아현동 19
 
1.8%
신수동 17
 
1.7%
염리동 17
 
1.7%
72-1번지 15
 
1.5%
성산동 14
 
1.4%
Other values (256) 459
44.6%
2024-05-11T04:32:15.870584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
992
 
17.8%
서 248
 
4.4%
1 241
 
4.3%
울 222
 
4.0%
포 219
 
3.9%
마 217
 
3.9%
동 217
 
3.9%
시 206
 
3.7%
구 205
 
3.7%
별 203
 
3.6%
Other values (226) 2608
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3551
63.7%
Space Separator 992
 
17.8%
Decimal Number 803
 
14.4%
Dash Punctuation 127
 
2.3%
Uppercase Letter 64
 
1.1%
Lowercase Letter 12
 
0.2%
Other Punctuation 11
 
0.2%
Close Punctuation 8
 
0.1%
Open Punctuation 8
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 248
 
7.0%
울 222
 
6.3%
포 219
 
6.2%
마 217
 
6.1%
동 217
 
6.1%
시 206
 
5.8%
구 205
 
5.8%
별 203
 
5.7%
특 203
 
5.7%
지 203
 
5.7%
Other values (184) 1408
39.7%
Uppercase Letter
ValueCountFrequency (%)
L 8
12.5%
D 8
12.5%
C 5
 
7.8%
S 5
 
7.8%
T 5
 
7.8%
K 4
 
6.2%
I 4
 
6.2%
M 4
 
6.2%
N 4
 
6.2%
O 3
 
4.7%
Other values (7) 14
21.9%
Decimal Number
ValueCountFrequency (%)
1 241
30.0%
2 101
12.6%
5 96
 
12.0%
7 76
 
9.5%
8 54
 
6.7%
6 53
 
6.6%
4 53
 
6.6%
3 49
 
6.1%
0 49
 
6.1%
9 31
 
3.9%
Lowercase Letter
ValueCountFrequency (%)
e 3
25.0%
w 3
25.0%
o 3
25.0%
r 3
25.0%
Other Punctuation
ValueCountFrequency (%)
, 7
63.6%
& 2
 
18.2%
. 2
 
18.2%
Close Punctuation
ValueCountFrequency (%)
) 7
87.5%
] 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 7
87.5%
[ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
992
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 127
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3551
63.7%
Common 1951
35.0%
Latin 76
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 248
 
7.0%
울 222
 
6.3%
포 219
 
6.2%
마 217
 
6.1%
동 217
 
6.1%
시 206
 
5.8%
구 205
 
5.8%
별 203
 
5.7%
특 203
 
5.7%
지 203
 
5.7%
Other values (184) 1408
39.7%
Common
ValueCountFrequency (%)
992
50.8%
1 241
 
12.4%
- 127
 
6.5%
2 101
 
5.2%
5 96
 
4.9%
7 76
 
3.9%
8 54
 
2.8%
6 53
 
2.7%
4 53
 
2.7%
3 49
 
2.5%
Other values (11) 109
 
5.6%
Latin
ValueCountFrequency (%)
L 8
 
10.5%
D 8
 
10.5%
C 5
 
6.6%
S 5
 
6.6%
T 5
 
6.6%
K 4
 
5.3%
I 4
 
5.3%
M 4
 
5.3%
N 4
 
5.3%
e 3
 
3.9%
Other values (11) 26
34.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3551
63.7%
ASCII 2027
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
992
48.9%
1 241
 
11.9%
- 127
 
6.3%
2 101
 
5.0%
5 96
 
4.7%
7 76
 
3.7%
8 54
 
2.7%
6 53
 
2.6%
4 53
 
2.6%
3 49
 
2.4%
Other values (32) 185
 
9.1%
Hangul
ValueCountFrequency (%)
서 248
 
7.0%
울 222
 
6.3%
포 219
 
6.2%
마 217
 
6.1%
동 217
 
6.1%
시 206
 
5.8%
구 205
 
5.8%
별 203
 
5.7%
특 203
 
5.7%
지 203
 
5.7%
Other values (184) 1408
39.7%

도로명주소
Text

MISSING 

Distinct130
Distinct (%)89.7%
Missing58
Missing (%)28.6%
Memory size1.7 KiB
2024-05-11T04:32:16.499028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length43
Mean length35.848276
Min length23

Characters and Unicode

Total characters5198
Distinct characters241
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

Unique117 ?
Unique (%)80.7%

Sample

1st row서울특별시 마포구 백범로31길 21 (공덕동, 4층)
2nd row서울특별시 마포구 와우산로 94 (상수동, 지하2층)
3rd row서울특별시 마포구 마포대로 155 (공덕동)
4th row서울특별시 마포구 서강대길 18 (신수동, 지하1층)
5th row서울특별시 마포구 독막로 281 (염리동)
ValueCountFrequency (%)
서울특별시 145
 
14.8%
마포구 145
 
14.8%
지하1층 32
 
3.3%
마포대로 31
 
3.2%
상암동 26
 
2.7%
공덕동 19
 
1.9%
양화로 16
 
1.6%
상수동 13
 
1.3%
와우산로 13
 
1.3%
아현동 12
 
1.2%
Other values (231) 526
53.8%
2024-05-11T04:32:17.854483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
834
 
16.0%
마 195
 
3.8%
포 195
 
3.8%
서 185
 
3.6%
1 171
 
3.3%
울 158
 
3.0%
동 157
 
3.0%
, 151
 
2.9%
( 150
 
2.9%
) 150
 
2.9%
Other values (231) 2852
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3249
62.5%
Space Separator 834
 
16.0%
Decimal Number 574
 
11.0%
Other Punctuation 154
 
3.0%
Open Punctuation 151
 
2.9%
Close Punctuation 151
 
2.9%
Uppercase Letter 68
 
1.3%
Lowercase Letter 12
 
0.2%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 195
 
6.0%
포 195
 
6.0%
서 185
 
5.7%
울 158
 
4.9%
동 157
 
4.8%
구 148
 
4.6%
시 146
 
4.5%
별 145
 
4.5%
특 145
 
4.5%
로 144
 
4.4%
Other values (190) 1631
50.2%
Uppercase Letter
ValueCountFrequency (%)
D 9
13.2%
L 8
11.8%
C 6
 
8.8%
K 5
 
7.4%
T 5
 
7.4%
M 5
 
7.4%
S 5
 
7.4%
I 4
 
5.9%
O 3
 
4.4%
N 3
 
4.4%
Other values (8) 15
22.1%
Decimal Number
ValueCountFrequency (%)
1 171
29.8%
2 80
13.9%
4 72
12.5%
3 63
 
11.0%
5 43
 
7.5%
9 36
 
6.3%
0 30
 
5.2%
8 29
 
5.1%
6 28
 
4.9%
7 22
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
o 3
25.0%
r 3
25.0%
e 3
25.0%
w 3
25.0%
Other Punctuation
ValueCountFrequency (%)
, 151
98.1%
& 2
 
1.3%
. 1
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 150
99.3%
[ 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 150
99.3%
] 1
 
0.7%
Space Separator
ValueCountFrequency (%)
834
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3249
62.5%
Common 1869
36.0%
Latin 80
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 195
 
6.0%
포 195
 
6.0%
서 185
 
5.7%
울 158
 
4.9%
동 157
 
4.8%
구 148
 
4.6%
시 146
 
4.5%
별 145
 
4.5%
특 145
 
4.5%
로 144
 
4.4%
Other values (190) 1631
50.2%
Latin
ValueCountFrequency (%)
D 9
 
11.2%
L 8
 
10.0%
C 6
 
7.5%
K 5
 
6.2%
T 5
 
6.2%
M 5
 
6.2%
S 5
 
6.2%
I 4
 
5.0%
O 3
 
3.8%
N 3
 
3.8%
Other values (12) 27
33.8%
Common
ValueCountFrequency (%)
834
44.6%
1 171
 
9.1%
, 151
 
8.1%
( 150
 
8.0%
) 150
 
8.0%
2 80
 
4.3%
4 72
 
3.9%
3 63
 
3.4%
5 43
 
2.3%
9 36
 
1.9%
Other values (9) 119
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3249
62.5%
ASCII 1949
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
834
42.8%
1 171
 
8.8%
, 151
 
7.7%
( 150
 
7.7%
) 150
 
7.7%
2 80
 
4.1%
4 72
 
3.7%
3 63
 
3.2%
5 43
 
2.2%
9 36
 
1.8%
Other values (31) 199
 
10.2%
Hangul
ValueCountFrequency (%)
마 195
 
6.0%
포 195
 
6.0%
서 185
 
5.7%
울 158
 
4.9%
동 157
 
4.8%
구 148
 
4.6%
시 146
 
4.5%
별 145
 
4.5%
특 145
 
4.5%
로 144
 
4.4%
Other values (190) 1631
50.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct58
Distinct (%)40.0%
Missing58
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean4055.2276
Minimum3900
Maximum4213
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:32:18.481709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3900
5-th percentile3912.4
Q13939
median4066
Q34137
95-th percentile4198.4
Maximum4213
Range313
Interquartile range (IQR)198

Descriptive statistics

Standard deviation96.02602
Coefficient of variation (CV)0.023679564
Kurtosis-1.2968538
Mean4055.2276
Median Absolute Deviation (MAD)74
Skewness-0.21757241
Sum588008
Variance9220.9965
MonotonicityNot monotonic
2024-05-11T04:32:19.134204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4066 12
 
5.9%
4107 9
 
4.4%
4117 7
 
3.4%
4140 7
 
3.4%
3922 6
 
3.0%
4129 5
 
2.5%
4036 5
 
2.5%
4130 5
 
2.5%
3923 4
 
2.0%
4207 4
 
2.0%
Other values (48) 81
39.9%
(Missing) 58
28.6%
ValueCountFrequency (%)
3900 1
 
0.5%
3903 1
 
0.5%
3906 1
 
0.5%
3909 3
1.5%
3911 2
 
1.0%
3918 1
 
0.5%
3919 2
 
1.0%
3920 3
1.5%
3921 1
 
0.5%
3922 6
3.0%
ValueCountFrequency (%)
4213 3
1.5%
4207 4
2.0%
4199 1
 
0.5%
4196 2
1.0%
4178 1
 
0.5%
4176 1
 
0.5%
4168 2
1.0%
4167 2
1.0%
4158 3
1.5%
4156 1
 
0.5%

사업장명
Text

Distinct199
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-11T04:32:19.884552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length13.591133
Min length2

Characters and Unicode

Total characters2759
Distinct characters270
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique195 ?
Unique (%)96.1%

Sample

1st row(주)이씨엠디 신용보증기금
2nd row(주)델리푸드서비스신수중학교점
3rd row대원유통
4th row신세계푸드 케이티솔루션지원센터
5th row한화호텔앤드리조트(주)아현중
ValueCountFrequency (%)
주)아워홈 7
 
2.4%
본우리집밥 6
 
2.1%
주)엘에스씨푸드 5
 
1.7%
아현산업정보학교 4
 
1.4%
이조케터링 4
 
1.4%
서울여자고등학교 3
 
1.0%
주)웰스팜 3
 
1.0%
마포점 3
 
1.0%
홈플러스 2
 
0.7%
주)동원홈푸드 2
 
0.7%
Other values (237) 248
86.4%
2024-05-11T04:32:21.082214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 131
 
4.7%
) 129
 
4.7%
주 129
 
4.7%
85
 
3.1%
드 83
 
3.0%
스 79
 
2.9%
점 74
 
2.7%
푸 65
 
2.4%
이 53
 
1.9%
학 51
 
1.8%
Other values (260) 1880
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2358
85.5%
Open Punctuation 131
 
4.7%
Close Punctuation 129
 
4.7%
Space Separator 85
 
3.1%
Uppercase Letter 40
 
1.4%
Decimal Number 10
 
0.4%
Dash Punctuation 3
 
0.1%
Other Punctuation 1
 
< 0.1%
Modifier Symbol 1
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 129
 
5.5%
드 83
 
3.5%
스 79
 
3.4%
점 74
 
3.1%
푸 65
 
2.8%
이 53
 
2.2%
학 51
 
2.2%
서 49
 
2.1%
에 43
 
1.8%
마 41
 
1.7%
Other values (235) 1691
71.7%
Uppercase Letter
ValueCountFrequency (%)
B 6
15.0%
C 5
12.5%
S 5
12.5%
K 4
10.0%
D 4
10.0%
L 4
10.0%
M 3
7.5%
O 2
 
5.0%
J 2
 
5.0%
F 1
 
2.5%
Other values (4) 4
10.0%
Decimal Number
ValueCountFrequency (%)
2 4
40.0%
7 3
30.0%
1 2
20.0%
3 1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 131
100.0%
Close Punctuation
ValueCountFrequency (%)
) 129
100.0%
Space Separator
ValueCountFrequency (%)
85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2359
85.5%
Common 360
 
13.0%
Latin 40
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 129
 
5.5%
드 83
 
3.5%
스 79
 
3.3%
점 74
 
3.1%
푸 65
 
2.8%
이 53
 
2.2%
학 51
 
2.2%
서 49
 
2.1%
에 43
 
1.8%
마 41
 
1.7%
Other values (236) 1692
71.7%
Latin
ValueCountFrequency (%)
B 6
15.0%
C 5
12.5%
S 5
12.5%
K 4
10.0%
D 4
10.0%
L 4
10.0%
M 3
7.5%
O 2
 
5.0%
J 2
 
5.0%
F 1
 
2.5%
Other values (4) 4
10.0%
Common
ValueCountFrequency (%)
( 131
36.4%
) 129
35.8%
85
23.6%
2 4
 
1.1%
7 3
 
0.8%
- 3
 
0.8%
1 2
 
0.6%
3 1
 
0.3%
& 1
 
0.3%
` 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2358
85.5%
ASCII 400
 
14.5%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 131
32.8%
) 129
32.2%
85
21.2%
B 6
 
1.5%
C 5
 
1.2%
S 5
 
1.2%
K 4
 
1.0%
D 4
 
1.0%
2 4
 
1.0%
L 4
 
1.0%
Other values (14) 23
 
5.8%
Hangul
ValueCountFrequency (%)
주 129
 
5.5%
드 83
 
3.5%
스 79
 
3.4%
점 74
 
3.1%
푸 65
 
2.8%
이 53
 
2.2%
학 51
 
2.2%
서 49
 
2.1%
에 43
 
1.8%
마 41
 
1.7%
Other values (235) 1691
71.7%
None
ValueCountFrequency (%)
㈜ 1
100.0%

최종수정일자
Date

Distinct195
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2003-06-19 00:00:00
Maximum2024-04-11 17:09:56
2024-05-11T04:32:21.598172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:32:22.198615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
I
135 
U
68 

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 135
66.5%
U 68
33.5%

Length

2024-05-11T04:32:22.732179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:23.126671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 135
66.5%
u 68
33.5%

데이터갱신일자
Date

Distinct75
Distinct (%)36.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-05-11T04:32:23.472357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:32:24.360260image/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 size1.7 KiB
위탁급식영업
203 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 203
100.0%

Length

2024-05-11T04:32:24.897501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:25.243610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 203
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct76
Distinct (%)39.6%
Missing11
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean193625.3
Minimum189192.41
Maximum196413.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:32:25.766050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189192.41
5-th percentile189885.08
Q1192303.2
median193962.73
Q3195523.28
95-th percentile196135.58
Maximum196413.14
Range7220.7247
Interquartile range (IQR)3220.0792

Descriptive statistics

Standard deviation2081.5167
Coefficient of variation (CV)0.010750231
Kurtosis-0.95469178
Mean193625.3
Median Absolute Deviation (MAD)1651.0876
Skewness-0.5460994
Sum37176057
Variance4332711.8
MonotonicityNot monotonic
2024-05-11T04:32:26.387480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193359.27190055 18
 
8.9%
195369.300032763 10
 
4.9%
194564.277152493 9
 
4.4%
196135.577338679 7
 
3.4%
195865.102384839 7
 
3.4%
195997.415918035 6
 
3.0%
195734.571727895 6
 
3.0%
195692.259461225 5
 
2.5%
192311.642580307 5
 
2.5%
192814.652923234 5
 
2.5%
Other values (66) 114
56.2%
(Missing) 11
 
5.4%
ValueCountFrequency (%)
189192.411433557 1
 
0.5%
189380.882932147 1
 
0.5%
189554.950644 1
 
0.5%
189658.337330066 1
 
0.5%
189761.756945497 2
1.0%
189855.433985731 3
1.5%
189857.576601267 1
 
0.5%
189907.583184796 1
 
0.5%
189919.550051873 4
2.0%
189965.528022741 1
 
0.5%
ValueCountFrequency (%)
196413.136098141 2
 
1.0%
196140.049195966 2
 
1.0%
196135.577338679 7
3.4%
196078.108047045 1
 
0.5%
195997.415918035 6
3.0%
195888.418398524 1
 
0.5%
195865.102384839 7
3.4%
195829.154836156 1
 
0.5%
195808.904523588 2
 
1.0%
195734.571727895 6
3.0%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct76
Distinct (%)39.6%
Missing11
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean450416.25
Minimum448116.64
Maximum453614.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:32:26.883393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448116.64
5-th percentile448882.59
Q1449516.01
median449855.64
Q3451205.05
95-th percentile453367.52
Maximum453614.58
Range5497.9435
Interquartile range (IQR)1689.0405

Descriptive statistics

Standard deviation1400.2417
Coefficient of variation (CV)0.0031087726
Kurtosis0.031889418
Mean450416.25
Median Absolute Deviation (MAD)618.5222
Skewness1.0227761
Sum86479921
Variance1960676.8
MonotonicityNot monotonic
2024-05-11T04:32:27.341941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449831.533270543 18
 
8.9%
449516.005660992 10
 
4.9%
449886.700377146 9
 
4.4%
450493.296797583 7
 
3.4%
449639.100661944 7
 
3.4%
449687.009632648 6
 
3.0%
449230.050577651 6
 
3.0%
449946.778190249 5
 
2.5%
449855.643910445 5
 
2.5%
451205.04612648 5
 
2.5%
Other values (66) 114
56.2%
(Missing) 11
 
5.4%
ValueCountFrequency (%)
448116.639953919 3
1.5%
448161.548233627 1
 
0.5%
448332.967337527 1
 
0.5%
448575.956518546 1
 
0.5%
448689.206203195 1
 
0.5%
448848.191602645 3
1.5%
448910.741283532 2
1.0%
448973.867131637 2
1.0%
449000.384905405 1
 
0.5%
449090.557637606 1
 
0.5%
ValueCountFrequency (%)
453614.583448105 3
1.5%
453602.289975077 1
 
0.5%
453543.978296468 2
1.0%
453460.99884432 1
 
0.5%
453407.061357665 1
 
0.5%
453390.246056 1
 
0.5%
453367.521771928 4
2.0%
453342.222208599 4
2.0%
453297.986643563 1
 
0.5%
453238.544463302 1
 
0.5%

위생업태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
위탁급식영업
164 
<NA>
39 

Length

Max length6
Median length6
Mean length5.6157635
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 164
80.8%
<NA> 39
 
19.2%

Length

2024-05-11T04:32:27.929136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:28.278644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 164
80.8%
na 39
 
19.2%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)10.4%
Missing136
Missing (%)67.0%
Infinite0
Infinite (%)0.0%
Mean0.80597015
Minimum0
Maximum12
Zeros47
Zeros (%)23.2%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:32:28.555798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum12
Range12
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8687121
Coefficient of variation (CV)2.3185873
Kurtosis19.831734
Mean0.80597015
Median Absolute Deviation (MAD)0
Skewness3.9528269
Sum54
Variance3.492085
MonotonicityNot monotonic
2024-05-11T04:32:28.937884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 47
 
23.2%
1 8
 
3.9%
3 5
 
2.5%
2 4
 
2.0%
12 1
 
0.5%
6 1
 
0.5%
5 1
 
0.5%
(Missing) 136
67.0%
ValueCountFrequency (%)
0 47
23.2%
1 8
 
3.9%
2 4
 
2.0%
3 5
 
2.5%
5 1
 
0.5%
6 1
 
0.5%
12 1
 
0.5%
ValueCountFrequency (%)
12 1
 
0.5%
6 1
 
0.5%
5 1
 
0.5%
3 5
 
2.5%
2 4
 
2.0%
1 8
 
3.9%
0 47
23.2%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)13.7%
Missing130
Missing (%)64.0%
Infinite0
Infinite (%)0.0%
Mean2.3835616
Minimum0
Maximum23
Zeros38
Zeros (%)18.7%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:32:29.261149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile8
Maximum23
Range23
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.6041263
Coefficient of variation (CV)1.512076
Kurtosis13.871125
Mean2.3835616
Median Absolute Deviation (MAD)0
Skewness2.9659455
Sum174
Variance12.989726
MonotonicityNot monotonic
2024-05-11T04:32:29.726177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 38
 
18.7%
3 11
 
5.4%
2 5
 
2.5%
4 5
 
2.5%
6 4
 
2.0%
5 3
 
1.5%
8 3
 
1.5%
9 2
 
1.0%
7 1
 
0.5%
23 1
 
0.5%
(Missing) 130
64.0%
ValueCountFrequency (%)
0 38
18.7%
2 5
 
2.5%
3 11
 
5.4%
4 5
 
2.5%
5 3
 
1.5%
6 4
 
2.0%
7 1
 
0.5%
8 3
 
1.5%
9 2
 
1.0%
23 1
 
0.5%
ValueCountFrequency (%)
23 1
 
0.5%
9 2
 
1.0%
8 3
 
1.5%
7 1
 
0.5%
6 4
 
2.0%
5 3
 
1.5%
4 5
 
2.5%
3 11
 
5.4%
2 5
 
2.5%
0 38
18.7%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
171 
주택가주변
 
16
학교정화(절대)
 
9
기타
 
4
아파트지역
 
2

Length

Max length8
Median length4
Mean length4.2463054
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row학교정화(절대)
3rd row주택가주변
4th row주택가주변
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 171
84.2%
주택가주변 16
 
7.9%
학교정화(절대) 9
 
4.4%
기타 4
 
2.0%
아파트지역 2
 
1.0%
학교정화(상대) 1
 
0.5%

Length

2024-05-11T04:32:30.210705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:30.596216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 171
84.2%
주택가주변 16
 
7.9%
학교정화(절대 9
 
4.4%
기타 4
 
2.0%
아파트지역 2
 
1.0%
학교정화(상대 1
 
0.5%

등급구분명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
179 
자율
24 

Length

Max length4
Median length4
Mean length3.7635468
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 179
88.2%
자율 24
 
11.8%

Length

2024-05-11T04:32:31.043693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:31.419207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 179
88.2%
자율 24
 
11.8%

급수시설구분명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
152 
상수도전용
51 

Length

Max length5
Median length4
Mean length4.2512315
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
74.9%
상수도전용 51
 
25.1%

Length

2024-05-11T04:32:31.809077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:32.179378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
74.9%
상수도전용 51
 
25.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
194 
0
 
9

Length

Max length4
Median length4
Mean length3.8669951
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> 194
95.6%
0 9
 
4.4%

Length

2024-05-11T04:32:32.690769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:33.137873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 194
95.6%
0 9
 
4.4%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
193 
0
 
10

Length

Max length4
Median length4
Mean length3.8522167
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> 193
95.1%
0 10
 
4.9%

Length

2024-05-11T04:32:33.469748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:33.804947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 193
95.1%
0 10
 
4.9%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
193 
0
 
10

Length

Max length4
Median length4
Mean length3.8522167
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> 193
95.1%
0 10
 
4.9%

Length

2024-05-11T04:32:34.564155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:35.019629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 193
95.1%
0 10
 
4.9%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
193 
0
 
10

Length

Max length4
Median length4
Mean length3.8522167
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> 193
95.1%
0 10
 
4.9%

Length

2024-05-11T04:32:35.450139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:35.822778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 193
95.1%
0 10
 
4.9%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
193 
0
 
10

Length

Max length4
Median length4
Mean length3.8522167
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> 193
95.1%
0 10
 
4.9%

Length

2024-05-11T04:32:36.198534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:36.636762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 193
95.1%
0 10
 
4.9%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
193 
0
 
10

Length

Max length4
Median length4
Mean length3.8522167
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> 193
95.1%
0 10
 
4.9%

Length

2024-05-11T04:32:37.062676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:37.384251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 193
95.1%
0 10
 
4.9%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
193 
0
 
10

Length

Max length4
Median length4
Mean length3.8522167
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> 193
95.1%
0 10
 
4.9%

Length

2024-05-11T04:32:37.792353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:38.108591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 193
95.1%
0 10
 
4.9%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.2%
Missing39
Missing (%)19.2%
Memory size538.0 B
False
163 
True
 
1
(Missing)
39 
ValueCountFrequency (%)
False 163
80.3%
True 1
 
0.5%
(Missing) 39
 
19.2%
2024-05-11T04:32:38.461763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct127
Distinct (%)77.4%
Missing39
Missing (%)19.2%
Infinite0
Infinite (%)0.0%
Mean436.2811
Minimum0
Maximum1516
Zeros5
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:32:38.921449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile25.975
Q1144
median297
Q3644.075
95-th percentile1211.935
Maximum1516
Range1516
Interquartile range (IQR)500.075

Descriptive statistics

Standard deviation386.33673
Coefficient of variation (CV)0.8855225
Kurtosis0.26505444
Mean436.2811
Median Absolute Deviation (MAD)200.055
Skewness1.0891217
Sum71550.1
Variance149256.07
MonotonicityNot monotonic
2024-05-11T04:32:39.491200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
324.0 5
 
2.5%
0.0 5
 
2.5%
132.0 3
 
1.5%
140.4 3
 
1.5%
267.93 3
 
1.5%
695.92 3
 
1.5%
177.98 3
 
1.5%
150.72 2
 
1.0%
1303.61 2
 
1.0%
170.0 2
 
1.0%
Other values (117) 133
65.5%
(Missing) 39
 
19.2%
ValueCountFrequency (%)
0.0 5
2.5%
6.6 1
 
0.5%
10.54 1
 
0.5%
23.64 1
 
0.5%
25.9 1
 
0.5%
26.4 2
 
1.0%
28.8 1
 
0.5%
29.68 1
 
0.5%
32.26 1
 
0.5%
38.87 1
 
0.5%
ValueCountFrequency (%)
1516.0 1
0.5%
1496.0 2
1.0%
1388.5 1
0.5%
1356.5 1
0.5%
1303.61 2
1.0%
1303.59 1
0.5%
1213.0 1
0.5%
1205.9 1
0.5%
1197.3 2
1.0%
1193.44 2
1.0%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031300003130000-120-2003-0000120030619<NA>3폐업2폐업20040827<NA><NA><NA>02 7104946583.00121803서울특별시 마포구 공덕동 254-5번지 (신용보증기금)<NA><NA>(주)이씨엠디 신용보증기금2003-06-19 00:00:00I2018-08-31 23:59:59.0위탁급식영업195734.571728449230.050578위탁급식영업15<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N583.0<NA><NA><NA>
131300003130000-120-2003-0000220030628<NA>3폐업2폐업20100210<NA><NA><NA><NA>155.64121856서울특별시 마포구 신수동 371-1번지 신수중학교<NA><NA>(주)델리푸드서비스신수중학교점2003-06-28 00:00:00I2018-08-31 23:59:59.0위탁급식영업194077.237559449324.838135위탁급식영업00학교정화(절대)자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N155.64<NA><NA><NA>
231300003130000-120-2003-0000320030709<NA>3폐업2폐업20050104<NA><NA><NA>02 7040856565.00121873서울특별시 마포구 염리동 150번지 동도중고등학교<NA><NA>대원유통2003-07-09 00:00:00I2018-08-31 23:59:59.0위탁급식영업195305.845755449346.612463위탁급식영업00주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N565.0<NA><NA><NA>
331300003130000-120-2003-0000420030710<NA>3폐업2폐업20071211<NA><NA><NA>7101999413.77121872서울특별시 마포구 염리동 85-2번지<NA><NA>신세계푸드 케이티솔루션지원센터2006-03-31 00:00:00I2018-08-31 23:59:59.0위탁급식영업195078.612135449471.580403위탁급식영업00주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N413.77<NA><NA><NA>
431300003130000-120-2003-0000520030711<NA>3폐업2폐업20100219<NA><NA><NA>02 3639274215.00121859서울특별시 마포구 아현동 267-1번지 아현중학교<NA><NA>한화호텔앤드리조트(주)아현중2010-01-20 17:09:26I2018-08-31 23:59:59.0위탁급식영업196135.577339450493.296798위탁급식영업10<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N215.0<NA><NA><NA>
531300003130000-120-2003-0000620030711<NA>3폐업2폐업20111007<NA><NA><NA>7039163833.40121809서울특별시 마포구 대흥동 28번지 숭문중고등학교<NA><NA>한화호텔앤드리조트(주)숭문중고점2010-01-21 10:31:44I2018-08-31 23:59:59.0위탁급식영업<NA><NA>위탁급식영업00학교정화(절대)자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N833.4<NA><NA><NA>
631300003130000-120-2003-0000720030724<NA>3폐업2폐업20081024<NA><NA><NA>3302575156.60121848서울특별시 마포구 성산동 275-3번지<NA><NA>신세계푸드마포구청2006-03-28 00:00:00I2018-08-31 23:59:59.0위탁급식영업191843.829548451282.558169위탁급식영업00주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N156.6<NA><NA><NA>
731300003130000-120-2003-0000820030725<NA>3폐업2폐업20141110<NA><NA><NA>7062120410.84121804서울특별시 마포구 공덕동 370-4번지서울특별시 마포구 백범로31길 21 (공덕동, 4층)4147(주)상우알에스2012-07-13 14:05:09I2018-08-31 23:59:59.0위탁급식영업195509.580071449388.26922위탁급식영업00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N410.84<NA><NA><NA>
831300003130000-120-2003-0000920030902<NA>3폐업2폐업20050602<NA><NA><NA>7113755664.20121872서울특별시 마포구 염리동 128-2번지 서울여자고등학교<NA><NA>서울여자고등학교2003-09-02 00:00:00I2018-08-31 23:59:59.0위탁급식영업195369.300033449516.005661위탁급식영업00학교정화(절대)자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N664.2<NA><NA><NA>
931300003130000-120-2003-0001020030902<NA>3폐업2폐업20100430<NA><NA><NA>32753755584.80121872서울특별시 마포구 염리동 128-2번지 서울여자중학교<NA><NA>(주)진풍푸드서비스2003-09-02 00:00:00I2018-08-31 23:59:59.0위탁급식영업195369.300033449516.005661위탁급식영업00학교정화(절대)자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N584.8<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
19331300003130000-120-2023-000042023-03-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>196.59121-812서울특별시 마포구 도화동 51-3 한국전력 마포용산지사서울특별시 마포구 토정로37길 38, 한국전력 마포용산지사 (도화동)4158이조케터링서비스(주)한전마포용산지점2023-03-21 14:19:53I2022-12-02 22:03:00.0위탁급식영업195210.825322448848.191603<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19431300003130000-120-2023-000052023-05-12<NA>1영업/정상1영업<NA><NA><NA><NA>0234007795802.37121-807서울특별시 마포구 노고산동 49-31 농협중앙회서울특별시 마포구 신촌로 66, 농협중앙회 12층 (노고산동)4057풀무원푸드앤컬처농협하나로유통2023-08-14 09:38:06U2022-12-07 23:07:00.0위탁급식영업194020.023177450426.583344<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19531300003130000-120-2023-000062023-09-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>330.60121-791서울특별시 마포구 상수동 72-1 홍익대학교서울특별시 마포구 와우산로 94, 홍익대학교 교직원식당 문헌관 16층 (상수동)4066한돌푸드2023-09-18 11:08:34I2022-12-08 22:00:00.0위탁급식영업193359.271901449831.533271<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19631300003130000-120-2023-000072023-09-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>86.00121-841서울특별시 마포구 서교동 447-1 아만티호텔 서울서울특별시 마포구 월드컵북로 31, 아만티호텔 서울 지3층 (서교동)4001허니푸드2023-09-18 14:18:26I2022-12-08 22:00:00.0위탁급식영업192736.935397450550.232656<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19731300003130000-120-2023-000082023-12-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>247.50121-030서울특별시 마포구 신공덕동 173 대우 월드마크마포서울특별시 마포구 백범로 212, 지하2층 (신공덕동, 대우 월드마크마포)4196㈜한울에프앤에스 이마트마포점2024-02-23 09:49:59U2023-12-01 22:05:00.0위탁급식영업195808.904524448910.741284<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19831300003130000-120-2024-000012024-01-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>121-835서울특별시 마포구 상암동 1595 한국지역정보개발원(KLID Tower)서울특별시 마포구 성암로 301, 한국지역정보개발원(KLID Tower) 4층 일부호 (상암동)3923한국지역정보개발원 구내식당2024-01-12 14:11:25I2023-11-30 23:04:00.0위탁급식영업190038.734552453367.521772<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19931300003130000-120-2024-000022024-02-29<NA>1영업/정상1영업<NA><NA><NA><NA>02 7032211129.60121-872서울특별시 마포구 염리동 128-2 서울여고서울특별시 마포구 백범로25길 34, 서울여고 (염리동)4140(주)엘에스씨푸드 서울여고2024-02-29 15:51:32I2023-12-03 00:02:00.0위탁급식영업195369.300033449516.005661<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20031300003130000-120-2024-000032024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>338.00121-010서울특별시 마포구 아현동 771 한세사이버보안고등학교서울특별시 마포구 마포대로11길 44-80, 한세사이버보안고등학교 (아현동)4129제이제이케터링(주) 한세사이버보안고등학교2024-03-04 15:29:42I2023-12-03 00:06:00.0위탁급식영업195692.259461449946.77819<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20131300003130000-120-2024-000042024-03-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>124.20121-050서울특별시 마포구 마포동 388-5 아리수 빌딩서울특별시 마포구 마포대로4다길 31, 아리수 빌딩 지하1층 B102호 (마포동)4178아라마크(주)좋은사람들2024-04-05 09:35:55U2023-12-04 00:07:00.0위탁급식영업195012.036013448161.548234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20231300003130000-120-2024-000052024-03-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>178.00121-832서울특별시 마포구 상암동 481-6 한국지역난방공사서울특별시 마포구 하늘공원로 84, 한국지역난방공사 (상암동)3900(주)명성에프에스2024-03-21 18:03:50I2023-12-02 22:03:00.0위탁급식영업189192.411434452075.998255<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>