Overview

Dataset statistics

Number of variables44
Number of observations173
Missing cells1514
Missing cells (%)19.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory63.7 KiB
Average record size in memory376.8 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric5
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
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-18179/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (62.2%)Imbalance
영업장주변구분명 is highly imbalanced (70.3%)Imbalance
등급구분명 is highly imbalanced (65.3%)Imbalance
총인원 is highly imbalanced (68.1%)Imbalance
인허가취소일자 has 173 (100.0%) missing valuesMissing
폐업일자 has 62 (35.8%) missing valuesMissing
휴업시작일자 has 173 (100.0%) missing valuesMissing
휴업종료일자 has 173 (100.0%) missing valuesMissing
재개업일자 has 173 (100.0%) missing valuesMissing
전화번호 has 57 (32.9%) missing valuesMissing
소재지면적 has 4 (2.3%) missing valuesMissing
도로명주소 has 48 (27.7%) missing valuesMissing
도로명우편번호 has 50 (28.9%) missing valuesMissing
좌표정보(X) has 2 (1.2%) missing valuesMissing
좌표정보(Y) has 2 (1.2%) missing valuesMissing
다중이용업소여부 has 39 (22.5%) missing valuesMissing
시설총규모 has 39 (22.5%) missing valuesMissing
전통업소지정번호 has 173 (100.0%) missing valuesMissing
전통업소주된음식 has 173 (100.0%) missing valuesMissing
홈페이지 has 173 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 7 (4.0%) zerosZeros
시설총규모 has 122 (70.5%) zerosZeros

Reproduction

Analysis started2024-05-18 02:55:09.673859
Analysis finished2024-05-18 02:55:11.112813
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3020000
173 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 173
100.0%

Length

2024-05-18T11:55:11.307440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:11.625204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 173
100.0%

관리번호
Text

UNIQUE 

Distinct173
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-05-18T11:55:12.006441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3806
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

Unique173 ?
Unique (%)100.0%

Sample

1st row3020000-109-1993-00001
2nd row3020000-109-1995-00001
3rd row3020000-109-1996-00030
4th row3020000-109-1997-00010
5th row3020000-109-1997-00014
ValueCountFrequency (%)
3020000-109-1993-00001 1
 
0.6%
3020000-109-2016-00007 1
 
0.6%
3020000-109-2016-00009 1
 
0.6%
3020000-109-2016-00010 1
 
0.6%
3020000-109-2017-00001 1
 
0.6%
3020000-109-2018-00001 1
 
0.6%
3020000-109-2018-00002 1
 
0.6%
3020000-109-2018-00003 1
 
0.6%
3020000-109-2018-00004 1
 
0.6%
3020000-109-2019-00001 1
 
0.6%
Other values (163) 163
94.2%
2024-05-18T11:55:12.809603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1915
50.3%
- 519
 
13.6%
2 425
 
11.2%
1 330
 
8.7%
3 232
 
6.1%
9 230
 
6.0%
4 43
 
1.1%
6 32
 
0.8%
5 29
 
0.8%
8 27
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3287
86.4%
Dash Punctuation 519
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1915
58.3%
2 425
 
12.9%
1 330
 
10.0%
3 232
 
7.1%
9 230
 
7.0%
4 43
 
1.3%
6 32
 
1.0%
5 29
 
0.9%
8 27
 
0.8%
7 24
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 519
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3806
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1915
50.3%
- 519
 
13.6%
2 425
 
11.2%
1 330
 
8.7%
3 232
 
6.1%
9 230
 
6.0%
4 43
 
1.1%
6 32
 
0.8%
5 29
 
0.8%
8 27
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3806
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1915
50.3%
- 519
 
13.6%
2 425
 
11.2%
1 330
 
8.7%
3 232
 
6.1%
9 230
 
6.0%
4 43
 
1.1%
6 32
 
0.8%
5 29
 
0.8%
8 27
 
0.7%

인허가일자
Date

Distinct172
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum1993-10-16 00:00:00
Maximum2024-05-16 00:00:00
2024-05-18T11:55:13.430276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:55:13.895195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing173
Missing (%)100.0%
Memory size1.6 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3
111 
1
62 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 111
64.2%
1 62
35.8%

Length

2024-05-18T11:55:14.304881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:14.629462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 111
64.2%
1 62
35.8%

영업상태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
폐업
111 
영업/정상
62 

Length

Max length5
Median length2
Mean length3.0751445
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 111
64.2%
영업/정상 62
35.8%

Length

2024-05-18T11:55:15.006511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:15.359665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 111
64.2%
영업/정상 62
35.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2
111 
1
62 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 111
64.2%
1 62
35.8%

Length

2024-05-18T11:55:15.709255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:16.042204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 111
64.2%
1 62
35.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
폐업
111 
영업
62 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 111
64.2%
영업 62
35.8%

Length

2024-05-18T11:55:16.419858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:16.766231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 111
64.2%
영업 62
35.8%

폐업일자
Date

MISSING 

Distinct95
Distinct (%)85.6%
Missing62
Missing (%)35.8%
Memory size1.5 KiB
Minimum1997-06-30 00:00:00
Maximum2024-04-01 00:00:00
2024-05-18T11:55:17.127700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:55:17.521326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing173
Missing (%)100.0%
Memory size1.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing173
Missing (%)100.0%
Memory size1.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing173
Missing (%)100.0%
Memory size1.6 KiB

전화번호
Text

MISSING 

Distinct111
Distinct (%)95.7%
Missing57
Missing (%)32.9%
Memory size1.5 KiB
2024-05-18T11:55:18.045238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.422414
Min length2

Characters and Unicode

Total characters1209
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

Unique107 ?
Unique (%)92.2%

Sample

1st row02 7132694
2nd row02 7902642
3rd row02 5444904
4th row02 00000
5th row02 00000
ValueCountFrequency (%)
02 84
36.8%
070 7
 
3.1%
7961890 2
 
0.9%
00000 2
 
0.9%
711 2
 
0.9%
3449 2
 
0.9%
34445862 1
 
0.4%
07088470874 1
 
0.4%
20120650 1
 
0.4%
7132694 1
 
0.4%
Other values (125) 125
54.8%
2024-05-18T11:55:19.020113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 240
19.9%
2 177
14.6%
7 157
13.0%
146
12.1%
9 87
 
7.2%
1 83
 
6.9%
3 73
 
6.0%
4 69
 
5.7%
5 64
 
5.3%
8 62
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1063
87.9%
Space Separator 146
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 240
22.6%
2 177
16.7%
7 157
14.8%
9 87
 
8.2%
1 83
 
7.8%
3 73
 
6.9%
4 69
 
6.5%
5 64
 
6.0%
8 62
 
5.8%
6 51
 
4.8%
Space Separator
ValueCountFrequency (%)
146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1209
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 240
19.9%
2 177
14.6%
7 157
13.0%
146
12.1%
9 87
 
7.2%
1 83
 
6.9%
3 73
 
6.0%
4 69
 
5.7%
5 64
 
5.3%
8 62
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1209
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 240
19.9%
2 177
14.6%
7 157
13.0%
146
12.1%
9 87
 
7.2%
1 83
 
6.9%
3 73
 
6.0%
4 69
 
5.7%
5 64
 
5.3%
8 62
 
5.1%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct99
Distinct (%)58.6%
Missing4
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean25.883609
Minimum0
Maximum317.21
Zeros7
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-18T11:55:19.337127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.342
Q16.6
median15
Q333
95-th percentile81.098
Maximum317.21
Range317.21
Interquartile range (IQR)26.4

Descriptive statistics

Standard deviation35.566341
Coefficient of variation (CV)1.3740874
Kurtosis28.293053
Mean25.883609
Median Absolute Deviation (MAD)11.7
Skewness4.3188159
Sum4374.33
Variance1264.9646
MonotonicityNot monotonic
2024-05-18T11:55:19.657897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 13
 
7.5%
6.6 8
 
4.6%
3.0 7
 
4.0%
33.0 7
 
4.0%
0.0 7
 
4.0%
10.0 6
 
3.5%
15.0 6
 
3.5%
9.9 5
 
2.9%
9.0 4
 
2.3%
6.0 3
 
1.7%
Other values (89) 103
59.5%
(Missing) 4
 
2.3%
ValueCountFrequency (%)
0.0 7
4.0%
2.31 1
 
0.6%
2.33 1
 
0.6%
2.36 1
 
0.6%
2.49 1
 
0.6%
2.5 1
 
0.6%
3.0 7
4.0%
3.3 13
7.5%
3.9 1
 
0.6%
4.0 1
 
0.6%
ValueCountFrequency (%)
317.21 1
0.6%
165.0 2
1.2%
99.0 1
0.6%
95.7 1
0.6%
92.8 1
0.6%
90.08 1
0.6%
88.4 1
0.6%
81.43 1
0.6%
80.6 1
0.6%
75.0 1
0.6%

소재지우편번호
Text

Distinct88
Distinct (%)50.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-05-18T11:55:20.207684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1734104
Min length6

Characters and Unicode

Total characters1068
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

Unique52 ?
Unique (%)30.1%

Sample

1st row140847
2nd row140853
3rd row140011
4th row140875
5th row140880
ValueCountFrequency (%)
140873 11
 
6.4%
140780 8
 
4.6%
140847 7
 
4.0%
140832 6
 
3.5%
140882 5
 
2.9%
140900 5
 
2.9%
140889 4
 
2.3%
140863 4
 
2.3%
140872 4
 
2.3%
140893 4
 
2.3%
Other values (78) 115
66.5%
2024-05-18T11:55:21.260006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 241
22.6%
1 203
19.0%
4 199
18.6%
8 163
15.3%
9 54
 
5.1%
7 45
 
4.2%
2 45
 
4.2%
3 37
 
3.5%
6 32
 
3.0%
- 30
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1038
97.2%
Dash Punctuation 30
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 241
23.2%
1 203
19.6%
4 199
19.2%
8 163
15.7%
9 54
 
5.2%
7 45
 
4.3%
2 45
 
4.3%
3 37
 
3.6%
6 32
 
3.1%
5 19
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1068
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 241
22.6%
1 203
19.0%
4 199
18.6%
8 163
15.3%
9 54
 
5.1%
7 45
 
4.2%
2 45
 
4.2%
3 37
 
3.5%
6 32
 
3.0%
- 30
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1068
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 241
22.6%
1 203
19.0%
4 199
18.6%
8 163
15.3%
9 54
 
5.1%
7 45
 
4.2%
2 45
 
4.2%
3 37
 
3.5%
6 32
 
3.0%
- 30
 
2.8%

지번주소
Text

Distinct161
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-05-18T11:55:21.821055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length24.138728
Min length17

Characters and Unicode

Total characters4176
Distinct characters134
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

Unique153 ?
Unique (%)88.4%

Sample

1st row서울특별시 용산구 원효로2가 80-8
2nd row서울특별시 용산구 이촌동 300-15
3rd row서울특별시 용산구 한강로1가 231-23
4th row서울특별시 용산구 한강로2가 194-2
5th row서울특별시 용산구 한강로3가 40-10
ValueCountFrequency (%)
서울특별시 173
21.1%
용산구 173
21.1%
한남동 27
 
3.3%
한강로2가 22
 
2.7%
한강로3가 18
 
2.2%
이태원동 18
 
2.2%
후암동 17
 
2.1%
1층 16
 
2.0%
지하1층 12
 
1.5%
15-19 10
 
1.2%
Other values (237) 333
40.7%
2024-05-18T11:55:22.634602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
775
18.6%
1 207
 
5.0%
산 188
 
4.5%
용 188
 
4.5%
서 181
 
4.3%
울 176
 
4.2%
시 173
 
4.1%
특 173
 
4.1%
구 173
 
4.1%
별 173
 
4.1%
Other values (124) 1769
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2348
56.2%
Decimal Number 874
 
20.9%
Space Separator 775
 
18.6%
Dash Punctuation 162
 
3.9%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%
Uppercase Letter 4
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 188
 
8.0%
용 188
 
8.0%
서 181
 
7.7%
울 176
 
7.5%
시 173
 
7.4%
특 173
 
7.4%
구 173
 
7.4%
별 173
 
7.4%
동 122
 
5.2%
한 75
 
3.2%
Other values (105) 726
30.9%
Decimal Number
ValueCountFrequency (%)
1 207
23.7%
2 132
15.1%
3 122
14.0%
4 72
 
8.2%
9 64
 
7.3%
0 60
 
6.9%
5 60
 
6.9%
7 60
 
6.9%
6 60
 
6.9%
8 37
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
H 1
25.0%
T 1
25.0%
N 1
25.0%
Y 1
25.0%
Space Separator
ValueCountFrequency (%)
775
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 162
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2348
56.2%
Common 1824
43.7%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 188
 
8.0%
용 188
 
8.0%
서 181
 
7.7%
울 176
 
7.5%
시 173
 
7.4%
특 173
 
7.4%
구 173
 
7.4%
별 173
 
7.4%
동 122
 
5.2%
한 75
 
3.2%
Other values (105) 726
30.9%
Common
ValueCountFrequency (%)
775
42.5%
1 207
 
11.3%
- 162
 
8.9%
2 132
 
7.2%
3 122
 
6.7%
4 72
 
3.9%
9 64
 
3.5%
0 60
 
3.3%
5 60
 
3.3%
7 60
 
3.3%
Other values (5) 110
 
6.0%
Latin
ValueCountFrequency (%)
H 1
25.0%
T 1
25.0%
N 1
25.0%
Y 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2348
56.2%
ASCII 1828
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
775
42.4%
1 207
 
11.3%
- 162
 
8.9%
2 132
 
7.2%
3 122
 
6.7%
4 72
 
3.9%
9 64
 
3.5%
0 60
 
3.3%
5 60
 
3.3%
7 60
 
3.3%
Other values (9) 114
 
6.2%
Hangul
ValueCountFrequency (%)
산 188
 
8.0%
용 188
 
8.0%
서 181
 
7.7%
울 176
 
7.5%
시 173
 
7.4%
특 173
 
7.4%
구 173
 
7.4%
별 173
 
7.4%
동 122
 
5.2%
한 75
 
3.2%
Other values (105) 726
30.9%

도로명주소
Text

MISSING 

Distinct124
Distinct (%)99.2%
Missing48
Missing (%)27.7%
Memory size1.5 KiB
2024-05-18T11:55:23.212054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length42
Mean length33.048
Min length22

Characters and Unicode

Total characters4131
Distinct characters146
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

Unique123 ?
Unique (%)98.4%

Sample

1st row서울특별시 용산구 원효로53길 20 (원효로2가)
2nd row서울특별시 용산구 한강대로62길 26 (한강로1가)
3rd row서울특별시 용산구 한강대로 296 (남영동)
4th row서울특별시 용산구 원효로 51 (산천동)
5th row서울특별시 용산구 서빙고로62길 27 (서빙고동)
ValueCountFrequency (%)
서울특별시 125
 
15.7%
용산구 125
 
15.7%
1층 38
 
4.8%
한남동 25
 
3.1%
이태원동 14
 
1.8%
후암동 13
 
1.6%
원효로 11
 
1.4%
한강로2가 10
 
1.3%
2층 10
 
1.3%
지하1층 9
 
1.1%
Other values (275) 414
52.1%
2024-05-18T11:55:24.324552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
670
 
16.2%
1 171
 
4.1%
로 163
 
3.9%
서 140
 
3.4%
2 139
 
3.4%
용 138
 
3.3%
산 137
 
3.3%
) 129
 
3.1%
( 129
 
3.1%
, 128
 
3.1%
Other values (136) 2187
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2365
57.3%
Decimal Number 679
 
16.4%
Space Separator 670
 
16.2%
Close Punctuation 129
 
3.1%
Open Punctuation 129
 
3.1%
Other Punctuation 128
 
3.1%
Dash Punctuation 23
 
0.6%
Uppercase Letter 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 163
 
6.9%
서 140
 
5.9%
용 138
 
5.8%
산 137
 
5.8%
울 127
 
5.4%
별 126
 
5.3%
시 126
 
5.3%
특 125
 
5.3%
구 125
 
5.3%
층 97
 
4.1%
Other values (115) 1061
44.9%
Decimal Number
ValueCountFrequency (%)
1 171
25.2%
2 139
20.5%
3 74
10.9%
0 61
 
9.0%
4 54
 
8.0%
5 51
 
7.5%
6 46
 
6.8%
8 29
 
4.3%
7 29
 
4.3%
9 25
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 3
37.5%
Y 1
 
12.5%
T 1
 
12.5%
N 1
 
12.5%
H 1
 
12.5%
A 1
 
12.5%
Space Separator
ValueCountFrequency (%)
670
100.0%
Close Punctuation
ValueCountFrequency (%)
) 129
100.0%
Open Punctuation
ValueCountFrequency (%)
( 129
100.0%
Other Punctuation
ValueCountFrequency (%)
, 128
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2365
57.3%
Common 1758
42.6%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 163
 
6.9%
서 140
 
5.9%
용 138
 
5.8%
산 137
 
5.8%
울 127
 
5.4%
별 126
 
5.3%
시 126
 
5.3%
특 125
 
5.3%
구 125
 
5.3%
층 97
 
4.1%
Other values (115) 1061
44.9%
Common
ValueCountFrequency (%)
670
38.1%
1 171
 
9.7%
2 139
 
7.9%
) 129
 
7.3%
( 129
 
7.3%
, 128
 
7.3%
3 74
 
4.2%
0 61
 
3.5%
4 54
 
3.1%
5 51
 
2.9%
Other values (5) 152
 
8.6%
Latin
ValueCountFrequency (%)
B 3
37.5%
Y 1
 
12.5%
T 1
 
12.5%
N 1
 
12.5%
H 1
 
12.5%
A 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2365
57.3%
ASCII 1766
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
670
37.9%
1 171
 
9.7%
2 139
 
7.9%
) 129
 
7.3%
( 129
 
7.3%
, 128
 
7.2%
3 74
 
4.2%
0 61
 
3.5%
4 54
 
3.1%
5 51
 
2.9%
Other values (11) 160
 
9.1%
Hangul
ValueCountFrequency (%)
로 163
 
6.9%
서 140
 
5.9%
용 138
 
5.8%
산 137
 
5.8%
울 127
 
5.4%
별 126
 
5.3%
시 126
 
5.3%
특 125
 
5.3%
구 125
 
5.3%
층 97
 
4.1%
Other values (115) 1061
44.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)52.8%
Missing50
Missing (%)28.9%
Infinite0
Infinite (%)0.0%
Mean4369.9756
Minimum4303
Maximum4428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-18T11:55:24.758721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4303
5-th percentile4317
Q14344.5
median4371
Q34399.5
95-th percentile4418.9
Maximum4428
Range125
Interquartile range (IQR)55

Descriptive statistics

Standard deviation32.494505
Coefficient of variation (CV)0.007435855
Kurtosis-1.0225946
Mean4369.9756
Median Absolute Deviation (MAD)28
Skewness-0.14825653
Sum537507
Variance1055.8928
MonotonicityNot monotonic
2024-05-18T11:55:25.181199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4382 7
 
4.0%
4405 5
 
2.9%
4363 5
 
2.9%
4391 4
 
2.3%
4333 4
 
2.3%
4371 4
 
2.3%
4419 4
 
2.3%
4378 3
 
1.7%
4410 3
 
1.7%
4317 3
 
1.7%
Other values (55) 81
46.8%
(Missing) 50
28.9%
ValueCountFrequency (%)
4303 1
 
0.6%
4304 1
 
0.6%
4314 1
 
0.6%
4315 1
 
0.6%
4316 2
1.2%
4317 3
1.7%
4318 1
 
0.6%
4322 1
 
0.6%
4325 1
 
0.6%
4326 1
 
0.6%
ValueCountFrequency (%)
4428 1
 
0.6%
4427 1
 
0.6%
4426 1
 
0.6%
4419 4
2.3%
4418 2
1.2%
4417 1
 
0.6%
4412 1
 
0.6%
4410 3
1.7%
4409 3
1.7%
4407 2
1.2%

사업장명
Text

Distinct171
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-05-18T11:55:25.796573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length6.867052
Min length2

Characters and Unicode

Total characters1188
Distinct characters322
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique169 ?
Unique (%)97.7%

Sample

1st row(주)아다미
2nd row한일마트
3rd row(주)노른자쇼핑 마니마니
4th row제일식품가공사
5th row일흥상사
ValueCountFrequency (%)
주식회사 4
 
2.0%
코스코마트 2
 
1.0%
위니비니 2
 
1.0%
한아름마트 2
 
1.0%
케르반 2
 
1.0%
한남점 2
 
1.0%
콤포타블 1
 
0.5%
월간커피박스 1
 
0.5%
주)나무종 1
 
0.5%
주)이심전심에프엔비 1
 
0.5%
Other values (187) 187
91.2%
2024-05-18T11:55:27.060902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 49
 
4.1%
( 48
 
4.0%
주 45
 
3.8%
이 35
 
2.9%
32
 
2.7%
스 27
 
2.3%
트 25
 
2.1%
리 24
 
2.0%
마 22
 
1.9%
아 19
 
1.6%
Other values (312) 862
72.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 975
82.1%
Close Punctuation 49
 
4.1%
Open Punctuation 48
 
4.0%
Space Separator 32
 
2.7%
Lowercase Letter 30
 
2.5%
Uppercase Letter 30
 
2.5%
Decimal Number 15
 
1.3%
Other Punctuation 5
 
0.4%
Dash Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 45
 
4.6%
이 35
 
3.6%
스 27
 
2.8%
트 25
 
2.6%
리 24
 
2.5%
마 22
 
2.3%
아 19
 
1.9%
식 17
 
1.7%
사 14
 
1.4%
드 13
 
1.3%
Other values (271) 734
75.3%
Lowercase Letter
ValueCountFrequency (%)
a 5
16.7%
l 4
13.3%
p 3
10.0%
y 3
10.0%
b 2
 
6.7%
s 2
 
6.7%
h 2
 
6.7%
c 2
 
6.7%
u 2
 
6.7%
r 1
 
3.3%
Other values (4) 4
13.3%
Uppercase Letter
ValueCountFrequency (%)
O 5
16.7%
M 5
16.7%
A 4
13.3%
N 3
10.0%
F 3
10.0%
H 2
 
6.7%
T 2
 
6.7%
G 1
 
3.3%
L 1
 
3.3%
I 1
 
3.3%
Other values (3) 3
10.0%
Decimal Number
ValueCountFrequency (%)
7 3
20.0%
9 2
13.3%
0 2
13.3%
4 2
13.3%
2 2
13.3%
1 2
13.3%
5 1
 
6.7%
3 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
? 4
80.0%
' 1
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 972
81.8%
Common 153
 
12.9%
Latin 60
 
5.1%
Han 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 45
 
4.6%
이 35
 
3.6%
스 27
 
2.8%
트 25
 
2.6%
리 24
 
2.5%
마 22
 
2.3%
아 19
 
2.0%
식 17
 
1.7%
사 14
 
1.4%
드 13
 
1.3%
Other values (268) 731
75.2%
Latin
ValueCountFrequency (%)
a 5
 
8.3%
O 5
 
8.3%
M 5
 
8.3%
l 4
 
6.7%
A 4
 
6.7%
N 3
 
5.0%
F 3
 
5.0%
p 3
 
5.0%
y 3
 
5.0%
H 2
 
3.3%
Other values (17) 23
38.3%
Common
ValueCountFrequency (%)
) 49
32.0%
( 48
31.4%
32
20.9%
? 4
 
2.6%
- 4
 
2.6%
7 3
 
2.0%
9 2
 
1.3%
0 2
 
1.3%
4 2
 
1.3%
2 2
 
1.3%
Other values (4) 5
 
3.3%
Han
ValueCountFrequency (%)
洋 1
33.3%
臼 1
33.3%
肄 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 972
81.8%
ASCII 213
 
17.9%
CJK 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 49
23.0%
( 48
22.5%
32
15.0%
a 5
 
2.3%
O 5
 
2.3%
M 5
 
2.3%
l 4
 
1.9%
? 4
 
1.9%
A 4
 
1.9%
- 4
 
1.9%
Other values (31) 53
24.9%
Hangul
ValueCountFrequency (%)
주 45
 
4.6%
이 35
 
3.6%
스 27
 
2.8%
트 25
 
2.6%
리 24
 
2.5%
마 22
 
2.3%
아 19
 
2.0%
식 17
 
1.7%
사 14
 
1.4%
드 13
 
1.3%
Other values (268) 731
75.2%
CJK
ValueCountFrequency (%)
洋 1
33.3%
臼 1
33.3%
肄 1
33.3%

최종수정일자
Date

Distinct166
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum1999-08-06 00:00:00
Maximum2024-05-16 15:52:03
2024-05-18T11:55:27.539907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:55:27.965789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
I
128 
U
45 

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 128
74.0%
U 45
 
26.0%

Length

2024-05-18T11:55:28.394192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:28.713116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 128
74.0%
u 45
 
26.0%

데이터갱신일자
Date

Distinct79
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 23:08:00
2024-05-18T11:55:29.017807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:55:29.326682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
식품소분업
173 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 173
100.0%

Length

2024-05-18T11:55:29.738003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:30.005729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 173
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct145
Distinct (%)84.8%
Missing2
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean197986.49
Minimum195544.61
Maximum200837.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-18T11:55:30.347280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195544.61
5-th percentile196281.49
Q1196802.69
median197504.65
Q3199281.43
95-th percentile200473.53
Maximum200837.14
Range5292.5303
Interquartile range (IQR)2478.7344

Descriptive statistics

Standard deviation1431.9683
Coefficient of variation (CV)0.0072326568
Kurtosis-1.0838275
Mean197986.49
Median Absolute Deviation (MAD)893.40998
Skewness0.48830257
Sum33855690
Variance2050533.3
MonotonicityNot monotonic
2024-05-18T11:55:30.775733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196813.258497258 10
 
5.8%
196762.077394917 7
 
4.0%
197804.482012591 3
 
1.7%
198043.461924383 2
 
1.2%
200401.947859104 2
 
1.2%
198994.001920861 2
 
1.2%
199268.814402981 2
 
1.2%
197055.562941213 2
 
1.2%
200837.136549128 2
 
1.2%
197721.947781082 2
 
1.2%
Other values (135) 137
79.2%
ValueCountFrequency (%)
195544.606275448 1
0.6%
195547.140326252 1
0.6%
195864.371540157 1
0.6%
195956.83241222 1
0.6%
195983.193740092 1
0.6%
196029.038711 1
0.6%
196039.664260104 1
0.6%
196215.450842338 1
0.6%
196272.456929147 1
0.6%
196290.526521217 1
0.6%
ValueCountFrequency (%)
200837.136549128 2
1.2%
200733.150411988 1
0.6%
200717.111495657 1
0.6%
200691.496940327 1
0.6%
200626.06966197 1
0.6%
200616.950505776 1
0.6%
200597.940803088 1
0.6%
200477.029427002 1
0.6%
200470.039218382 1
0.6%
200431.145594386 1
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct145
Distinct (%)84.8%
Missing2
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean448213.88
Minimum446114.16
Maximum450198.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-18T11:55:31.287121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446114.16
5-th percentile446791.2
Q1447659.71
median448053.07
Q3448710.68
95-th percentile449817.63
Maximum450198.03
Range4083.8778
Interquartile range (IQR)1050.9651

Descriptive statistics

Standard deviation918.98714
Coefficient of variation (CV)0.0020503317
Kurtosis-0.34277974
Mean448213.88
Median Absolute Deviation (MAD)488.80204
Skewness0.28699438
Sum76644574
Variance844537.37
MonotonicityNot monotonic
2024-05-18T11:55:31.750429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447881.970772064 10
 
5.8%
447480.039577359 7
 
4.0%
449752.252401559 3
 
1.7%
449732.012463716 2
 
1.2%
447748.320460119 2
 
1.2%
449630.953175642 2
 
1.2%
446349.092131061 2
 
1.2%
447033.794383442 2
 
1.2%
448057.231929995 2
 
1.2%
449834.912613535 2
 
1.2%
Other values (135) 137
79.2%
ValueCountFrequency (%)
446114.155238838 1
0.6%
446243.198701013 1
0.6%
446344.591216568 1
0.6%
446349.092131061 2
1.2%
446437.197878548 1
0.6%
446586.516612702 1
0.6%
446653.550561806 1
0.6%
446661.791595739 1
0.6%
446920.601371614 1
0.6%
446946.902690409 1
0.6%
ValueCountFrequency (%)
450198.033078924 1
0.6%
450140.794806055 1
0.6%
450014.537949042 1
0.6%
450002.778511517 1
0.6%
449889.220063562 1
0.6%
449834.912613535 2
1.2%
449829.998949456 1
0.6%
449817.63174008 2
1.2%
449781.906305019 1
0.6%
449760.779873134 1
0.6%

위생업태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
식품소분업
134 
<NA>
39 

Length

Max length5
Median length5
Mean length4.7745665
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 134
77.5%
<NA> 39
 
22.5%

Length

2024-05-18T11:55:32.181710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:32.545905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 134
77.5%
na 39
 
22.5%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
150 
0
22 
3
 
1

Length

Max length4
Median length4
Mean length3.6011561
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 150
86.7%
0 22
 
12.7%
3 1
 
0.6%

Length

2024-05-18T11:55:32.918409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:33.267236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
86.7%
0 22
 
12.7%
3 1
 
0.6%

여성종사자수
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
150 
0
23 

Length

Max length4
Median length4
Mean length3.6011561
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> 150
86.7%
0 23
 
13.3%

Length

2024-05-18T11:55:33.631114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:34.048896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
86.7%
0 23
 
13.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
153 
기타
 
12
주택가주변
 
5
유흥업소밀집지역
 
2
학교정화(상대)
 
1

Length

Max length8
Median length4
Mean length3.9595376
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 153
88.4%
기타 12
 
6.9%
주택가주변 5
 
2.9%
유흥업소밀집지역 2
 
1.2%
학교정화(상대) 1
 
0.6%

Length

2024-05-18T11:55:34.416774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:34.777931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 153
88.4%
기타 12
 
6.9%
주택가주변 5
 
2.9%
유흥업소밀집지역 2
 
1.2%
학교정화(상대 1
 
0.6%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
153 
기타
19 
우수
 
1

Length

Max length4
Median length4
Mean length3.7687861
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 153
88.4%
기타 19
 
11.0%
우수 1
 
0.6%

Length

2024-05-18T11:55:35.177235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:35.389436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 153
88.4%
기타 19
 
11.0%
우수 1
 
0.6%

급수시설구분명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
152 
상수도전용
21 

Length

Max length5
Median length4
Mean length4.1213873
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
87.9%
상수도전용 21
 
12.1%

Length

2024-05-18T11:55:35.745468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:36.086861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
87.9%
상수도전용 21
 
12.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
163 
0
 
10

Length

Max length4
Median length4
Mean length3.8265896
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> 163
94.2%
0 10
 
5.8%

Length

2024-05-18T11:55:36.379465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:36.720696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 163
94.2%
0 10
 
5.8%

본사종업원수
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
125 
0
48 

Length

Max length4
Median length4
Mean length3.1676301
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 125
72.3%
0 48
 
27.7%

Length

2024-05-18T11:55:37.087081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:37.427941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
72.3%
0 48
 
27.7%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
125 
0
48 

Length

Max length4
Median length4
Mean length3.1676301
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 125
72.3%
0 48
 
27.7%

Length

2024-05-18T11:55:37.820729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:38.173375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
72.3%
0 48
 
27.7%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
125 
0
48 

Length

Max length4
Median length4
Mean length3.1676301
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 125
72.3%
0 48
 
27.7%

Length

2024-05-18T11:55:38.486458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:38.810294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
72.3%
0 48
 
27.7%

공장생산직종업원수
Categorical

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
125 
0
47 
1
 
1

Length

Max length4
Median length4
Mean length3.1676301
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 125
72.3%
0 47
 
27.2%
1 1
 
0.6%

Length

2024-05-18T11:55:39.256150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:39.641467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
72.3%
0 47
 
27.2%
1 1
 
0.6%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
68 
자가
66 
임대
39 

Length

Max length4
Median length2
Mean length2.7861272
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 68
39.3%
자가 66
38.2%
임대 39
22.5%

Length

2024-05-18T11:55:39.996626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:40.469013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 68
39.3%
자가 66
38.2%
임대 39
22.5%

보증액
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
149 
0
24 

Length

Max length4
Median length4
Mean length3.583815
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> 149
86.1%
0 24
 
13.9%

Length

2024-05-18T11:55:40.859047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:41.254891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
86.1%
0 24
 
13.9%

월세액
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
149 
0
24 

Length

Max length4
Median length4
Mean length3.583815
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> 149
86.1%
0 24
 
13.9%

Length

2024-05-18T11:55:41.591619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:55:41.874271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
86.1%
0 24
 
13.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.7%
Missing39
Missing (%)22.5%
Memory size478.0 B
False
134 
(Missing)
39 
ValueCountFrequency (%)
False 134
77.5%
(Missing) 39
 
22.5%
2024-05-18T11:55:42.178501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)9.7%
Missing39
Missing (%)22.5%
Infinite0
Infinite (%)0.0%
Mean3.8458955
Minimum0
Maximum165
Zeros122
Zeros (%)70.5%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-18T11:55:42.536635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile15.17
Maximum165
Range165
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.728066
Coefficient of variation (CV)4.8696243
Kurtosis46.396237
Mean3.8458955
Median Absolute Deviation (MAD)0
Skewness6.3997303
Sum515.35
Variance350.74047
MonotonicityNot monotonic
2024-05-18T11:55:42.951905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.0 122
70.5%
30.0 1
 
0.6%
35.0 1
 
0.6%
88.4 1
 
0.6%
23.1 1
 
0.6%
165.0 1
 
0.6%
3.3 1
 
0.6%
73.92 1
 
0.6%
4.0 1
 
0.6%
10.9 1
 
0.6%
Other values (3) 3
 
1.7%
(Missing) 39
 
22.5%
ValueCountFrequency (%)
0.0 122
70.5%
2.33 1
 
0.6%
3.3 1
 
0.6%
4.0 1
 
0.6%
6.8 1
 
0.6%
10.9 1
 
0.6%
23.1 1
 
0.6%
30.0 1
 
0.6%
35.0 1
 
0.6%
72.6 1
 
0.6%
ValueCountFrequency (%)
165.0 1
0.6%
88.4 1
0.6%
73.92 1
0.6%
72.6 1
0.6%
35.0 1
0.6%
30.0 1
0.6%
23.1 1
0.6%
10.9 1
0.6%
6.8 1
0.6%
4.0 1
0.6%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing173
Missing (%)100.0%
Memory size1.6 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing173
Missing (%)100.0%
Memory size1.6 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing173
Missing (%)100.0%
Memory size1.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030200003020000-109-1993-0000119931016<NA>1영업/정상1영업<NA><NA><NA><NA>02 7132694<NA>140847서울특별시 용산구 원효로2가 80-8서울특별시 용산구 원효로53길 20 (원효로2가)4364(주)아다미2009-01-21 10:59:55I2018-08-31 23:59:59.0식품소분업196590.382904448261.626665식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
130200003020000-109-1995-0000119950923<NA>3폐업2폐업20021128<NA><NA><NA>02 7902642<NA>140853서울특별시 용산구 이촌동 300-15<NA><NA>한일마트2002-01-16 00:00:00I2018-08-31 23:59:59.0식품소분업197974.143195446243.198701식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230200003020000-109-1996-0003019960701<NA>3폐업2폐업20140818<NA><NA><NA>02 544490419.08140011서울특별시 용산구 한강로1가 231-23서울특별시 용산구 한강대로62길 26 (한강로1가)4382(주)노른자쇼핑 마니마니2013-04-12 09:44:15I2018-08-31 23:59:59.0식품소분업197570.006193447953.578982식품소분업<NA><NA>주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
330200003020000-109-1997-0001019970730<NA>3폐업2폐업19980409<NA><NA><NA>02 000000.0140875서울특별시 용산구 한강로2가 194-2<NA><NA>제일식품가공사2001-09-27 00:00:00I2018-08-31 23:59:59.0식품소분업197028.683565447234.744546식품소분업<NA><NA>유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430200003020000-109-1997-0001419970630<NA>3폐업2폐업19970630<NA><NA><NA>02 000000.0140880서울특별시 용산구 한강로3가 40-10<NA><NA>일흥상사2001-09-27 00:00:00I2018-08-31 23:59:59.0식품소분업196611.85379446963.630871식품소분업<NA><NA>학교정화(상대)우수상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530200003020000-109-1997-0003119970610<NA>3폐업2폐업19980407<NA><NA><NA>02 0 0000.0140011서울특별시 용산구 한강로1가 47-1<NA><NA>(주)신한무역2001-09-27 00:00:00I2018-08-31 23:59:59.0식품소분업197600.903999448291.626358식품소분업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630200003020000-109-1998-0001119980319<NA>3폐업2폐업20010817<NA><NA><NA>02 790095911.65140780서울특별시 용산구 한강로3가 40-129<NA><NA>일흥유통2001-09-27 00:00:00I2018-08-31 23:59:59.0식품소분업196720.116527447108.794901식품소분업<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730200003020000-109-1998-0001219980831<NA>3폐업2폐업20020814<NA><NA><NA>02 57911360.0140820서울특별시 용산구 동자동 19-37<NA><NA>대진유통2001-09-27 00:00:00I2018-08-31 23:59:59.0식품소분업197721.947781449834.912614식품소분업<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
830200003020000-109-1999-0007819990211<NA>3폐업2폐업19990806<NA><NA><NA>02 70121289.45140869서울특별시 용산구 청파동1가 187-0<NA><NA>풍요상사(주)1999-08-06 00:00:00I2018-08-31 23:59:59.0식품소분업197277.369901449433.808828식품소분업30주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930200003020000-109-1999-0011819990621<NA>3폐업2폐업20000621<NA><NA><NA>0227.47140897서울특별시 용산구 효창동 3-186<NA><NA>현대유통2000-06-21 00:00:00I2018-08-31 23:59:59.0식품소분업196215.450842449216.964636식품소분업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
16330200003020000-109-2023-000042023-04-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.2140-811서울특별시 용산구 동빙고동 89-5 현대그린카서비스서울특별시 용산구 서빙고로 303, 현대그린카서비스 비1층 (동빙고동)4397주식회사 심플리케이2023-04-20 17:18:07I2022-12-03 22:03:00.0식품소분업199669.051328446586.516613<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16430200003020000-109-2023-000052023-05-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.0140-861서울특별시 용산구 이태원동 336-1서울특별시 용산구 녹사평대로46길 16, 1층 (이태원동)4345스페이스 티엠디2023-10-19 16:18:48U2022-10-30 22:01:00.0식품소분업198839.974391448323.249715<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16530200003020000-109-2023-000062023-05-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.0140-160서울특별시 용산구 남영동 94-1서울특별시 용산구 한강대로80길 12, 201호 (남영동)4352물 수튜디오2023-05-12 17:04:28I2022-12-04 23:04:00.0식품소분업197588.444621448921.377493<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16630200003020000-109-2023-000072023-06-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>18.31140-901서울특별시 용산구 후암동 358-17 대원정사서울특별시 용산구 두텁바위로60길 49, 대원정사 별관3층 (후암동)4328콤포타블 남산2023-06-02 16:34:50I2022-12-06 00:04:00.0식품소분업198470.128905449639.883506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16730200003020000-109-2023-000082023-06-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.8140-821서울특별시 용산구 동자동 23-31서울특별시 용산구 한강대로104나길 4, 1층 (동자동)4333건어물대통령(동자점)2023-06-23 09:32:52I2022-12-05 22:05:00.0식품소분업197692.077925449781.906305<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16830200003020000-109-2023-000092023-07-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>18.0140-887서울특별시 용산구 한남동 631-5 허준빌딩서울특별시 용산구 대사관로34길 26, 허준빌딩 1층 (한남동)4402롯데프레시 한남점2023-07-04 17:08:41I2022-12-07 00:06:00.0식품소분업200431.145594447763.414163<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16930200003020000-109-2023-000102023-12-06<NA>1영업/정상1영업<NA><NA><NA><NA>02 774 88603.3140-900서울특별시 용산구 후암동 115-1서울특별시 용산구 후암로35길 36, 1층 (후암동)4333웰빙마트2023-12-06 15:25:30I2022-11-02 00:08:00.0식품소분업197804.482013449752.252402<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17030200003020000-109-2023-000112023-12-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.0140-012서울특별시 용산구 한강로2가 422 래미안용산 더 센트럴서울특별시 용산구 한강대로 95, 상가 A동 4층 406호 (한강로2가, 래미안용산 더 센트럴)4378주식회사 육달상회2024-02-29 16:29:34U2023-12-03 00:02:00.0식품소분업197011.737529447430.100251<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17130200003020000-109-2024-000012024-01-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.0140-872서울특별시 용산구 한강로2가 107-3서울특별시 용산구 한강대로46길 16, 1층 103호 (한강로2가)4382델로 커피컴퍼니2024-01-25 17:02:51I2023-11-30 22:07:00.0식품소분업197368.776856447648.536368<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17230200003020000-109-2024-000022024-05-16<NA>1영업/정상1영업<NA><NA><NA><NA>02 6465729115.0140-901서울특별시 용산구 후암동 303-5서울특별시 용산구 후암로28길 60, 1층 (후암동)4331주식회사 스파이서리2024-05-16 15:52:03I2023-12-04 23:08:00.0식품소분업198208.319055449639.178239<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>