Overview

Dataset statistics

Number of variables44
Number of observations183
Missing cells1823
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory67.5 KiB
Average record size in memory377.7 B

Variable types

Categorical21
Text6
DateTime3
Unsupported8
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
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-18530/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
데이터갱신일자 is highly imbalanced (72.7%)Imbalance
위생업태명 is highly imbalanced (63.0%)Imbalance
남성종사자수 is highly imbalanced (56.5%)Imbalance
여성종사자수 is highly imbalanced (53.8%)Imbalance
급수시설구분명 is highly imbalanced (61.9%)Imbalance
총인원 is highly imbalanced (91.3%)Imbalance
본사종업원수 is highly imbalanced (91.3%)Imbalance
공장사무직종업원수 is highly imbalanced (91.3%)Imbalance
공장판매직종업원수 is highly imbalanced (91.3%)Imbalance
공장생산직종업원수 is highly imbalanced (91.3%)Imbalance
보증액 is highly imbalanced (91.3%)Imbalance
월세액 is highly imbalanced (91.3%)Imbalance
다중이용업소여부 is highly imbalanced (94.8%)Imbalance
인허가취소일자 has 183 (100.0%) missing valuesMissing
폐업일자 has 34 (18.6%) missing valuesMissing
휴업시작일자 has 183 (100.0%) missing valuesMissing
휴업종료일자 has 183 (100.0%) missing valuesMissing
재개업일자 has 183 (100.0%) missing valuesMissing
전화번호 has 8 (4.4%) missing valuesMissing
도로명주소 has 129 (70.5%) missing valuesMissing
도로명우편번호 has 135 (73.8%) missing valuesMissing
좌표정보(X) has 13 (7.1%) missing valuesMissing
좌표정보(Y) has 13 (7.1%) missing valuesMissing
건물소유구분명 has 183 (100.0%) missing valuesMissing
다중이용업소여부 has 13 (7.1%) missing valuesMissing
시설총규모 has 13 (7.1%) missing valuesMissing
전통업소지정번호 has 183 (100.0%) missing valuesMissing
전통업소주된음식 has 183 (100.0%) missing valuesMissing
홈페이지 has 183 (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

Reproduction

Analysis started2024-05-11 05:28:06.596620
Analysis finished2024-05-11 05:28:07.561899
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
3030000
183 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3030000
2nd row3030000
3rd row3030000
4th row3030000
5th row3030000

Common Values

ValueCountFrequency (%)
3030000 183
100.0%

Length

2024-05-11T14:28:07.676373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:07.834903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3030000 183
100.0%

관리번호
Text

UNIQUE 

Distinct183
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T14:28:08.094167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4026
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

Unique183 ?
Unique (%)100.0%

Sample

1st row3030000-103-1993-00090
2nd row3030000-103-1993-01016
3rd row3030000-103-1993-01056
4th row3030000-103-1993-01075
5th row3030000-103-1993-01077
ValueCountFrequency (%)
3030000-103-1993-00090 1
 
0.5%
3030000-103-1997-00972 1
 
0.5%
3030000-103-1996-01007 1
 
0.5%
3030000-103-1996-01008 1
 
0.5%
3030000-103-1996-01009 1
 
0.5%
3030000-103-1996-01010 1
 
0.5%
3030000-103-1996-01011 1
 
0.5%
3030000-103-1996-01012 1
 
0.5%
3030000-103-1996-01013 1
 
0.5%
3030000-103-1996-01014 1
 
0.5%
Other values (173) 173
94.5%
2024-05-11T14:28:08.685441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1539
38.2%
3 605
 
15.0%
- 549
 
13.6%
1 513
 
12.7%
9 432
 
10.7%
4 89
 
2.2%
6 69
 
1.7%
5 64
 
1.6%
7 63
 
1.6%
2 52
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3477
86.4%
Dash Punctuation 549
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1539
44.3%
3 605
 
17.4%
1 513
 
14.8%
9 432
 
12.4%
4 89
 
2.6%
6 69
 
2.0%
5 64
 
1.8%
7 63
 
1.8%
2 52
 
1.5%
8 51
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 549
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4026
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1539
38.2%
3 605
 
15.0%
- 549
 
13.6%
1 513
 
12.7%
9 432
 
10.7%
4 89
 
2.2%
6 69
 
1.7%
5 64
 
1.6%
7 63
 
1.6%
2 52
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4026
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1539
38.2%
3 605
 
15.0%
- 549
 
13.6%
1 513
 
12.7%
9 432
 
10.7%
4 89
 
2.2%
6 69
 
1.7%
5 64
 
1.6%
7 63
 
1.6%
2 52
 
1.3%

인허가일자
Date

Distinct164
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum1993-09-08 00:00:00
Maximum2014-12-17 00:00:00
2024-05-11T14:28:09.047244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:28:09.301485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing183
Missing (%)100.0%
Memory size1.7 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
3
149 
1
34 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 149
81.4%
1 34
 
18.6%

Length

2024-05-11T14:28:09.518347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:09.679775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 149
81.4%
1 34
 
18.6%

영업상태명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
폐업
149 
영업/정상
34 

Length

Max length5
Median length2
Mean length2.557377
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 149
81.4%
영업/정상 34
 
18.6%

Length

2024-05-11T14:28:09.874095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:10.050269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 149
81.4%
영업/정상 34
 
18.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2
149 
1
34 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 149
81.4%
1 34
 
18.6%

Length

2024-05-11T14:28:10.252714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:10.438503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 149
81.4%
1 34
 
18.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
폐업
149 
영업
34 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 149
81.4%
영업 34
 
18.6%

Length

2024-05-11T14:28:10.635302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:10.941574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 149
81.4%
영업 34
 
18.6%

폐업일자
Date

MISSING 

Distinct127
Distinct (%)85.2%
Missing34
Missing (%)18.6%
Memory size1.6 KiB
Minimum1994-08-22 00:00:00
Maximum2023-03-31 00:00:00
2024-05-11T14:28:11.225749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:28:11.497269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing183
Missing (%)100.0%
Memory size1.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing183
Missing (%)100.0%
Memory size1.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing183
Missing (%)100.0%
Memory size1.7 KiB

전화번호
Text

MISSING 

Distinct162
Distinct (%)92.6%
Missing8
Missing (%)4.4%
Memory size1.6 KiB
2024-05-11T14:28:11.871704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.4285714
Min length2

Characters and Unicode

Total characters1650
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

Unique159 ?
Unique (%)90.9%

Sample

1st row0222982367
2nd row02
3rd row02 4651487
4th row02 2944087
5th row02 4629239
ValueCountFrequency (%)
02 78
32.4%
0 2
 
0.8%
4626373 2
 
0.8%
0222958296 1
 
0.4%
0222944731 1
 
0.4%
0222982367 1
 
0.4%
0222399350 1
 
0.4%
4647909 1
 
0.4%
000222947154 1
 
0.4%
4696329 1
 
0.4%
Other values (152) 152
63.1%
2024-05-11T14:28:12.496599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 432
26.2%
0 287
17.4%
9 175
10.6%
4 151
 
9.2%
6 126
 
7.6%
7 89
 
5.4%
3 85
 
5.2%
8 82
 
5.0%
5 81
 
4.9%
1 72
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1580
95.8%
Space Separator 70
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 432
27.3%
0 287
18.2%
9 175
11.1%
4 151
 
9.6%
6 126
 
8.0%
7 89
 
5.6%
3 85
 
5.4%
8 82
 
5.2%
5 81
 
5.1%
1 72
 
4.6%
Space Separator
ValueCountFrequency (%)
70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1650
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 432
26.2%
0 287
17.4%
9 175
10.6%
4 151
 
9.2%
6 126
 
7.6%
7 89
 
5.4%
3 85
 
5.2%
8 82
 
5.0%
5 81
 
4.9%
1 72
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 432
26.2%
0 287
17.4%
9 175
10.6%
4 151
 
9.2%
6 126
 
7.6%
7 89
 
5.4%
3 85
 
5.2%
8 82
 
5.0%
5 81
 
4.9%
1 72
 
4.4%

소재지면적
Real number (ℝ)

Distinct173
Distinct (%)95.1%
Missing1
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean93.217802
Minimum0
Maximum179.22
Zeros1
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T14:28:12.761400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile46.4385
Q170.2625
median92.12
Q3118.0975
95-th percentile146
Maximum179.22
Range179.22
Interquartile range (IQR)47.835

Descriptive statistics

Standard deviation31.574598
Coefficient of variation (CV)0.33871854
Kurtosis-0.46043745
Mean93.217802
Median Absolute Deviation (MAD)24.41
Skewness0.15688701
Sum16965.64
Variance996.95522
MonotonicityNot monotonic
2024-05-11T14:28:13.037519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58.96 3
 
1.6%
148.5 2
 
1.1%
147.99 2
 
1.1%
71.76 2
 
1.1%
41.86 2
 
1.1%
148.03 2
 
1.1%
75.16 2
 
1.1%
75.53 2
 
1.1%
143.2 1
 
0.5%
142.82 1
 
0.5%
Other values (163) 163
89.1%
ValueCountFrequency (%)
0.0 1
0.5%
29.49 1
0.5%
35.0 1
0.5%
38.43 1
0.5%
41.78 1
0.5%
41.86 2
1.1%
45.75 1
0.5%
46.22 1
0.5%
46.41 1
0.5%
46.98 1
0.5%
ValueCountFrequency (%)
179.22 1
0.5%
148.81 1
0.5%
148.5 2
1.1%
148.3 1
0.5%
148.03 2
1.1%
147.99 2
1.1%
146.04 1
0.5%
145.24 1
0.5%
144.71 1
0.5%
144.54 1
0.5%

소재지우편번호
Text

Distinct56
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T14:28:13.445404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0327869
Min length6

Characters and Unicode

Total characters1104
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

Unique21 ?
Unique (%)11.5%

Sample

1st row133800
2nd row133882
3rd row133828
4th row133815
5th row133828
ValueCountFrequency (%)
133882 23
 
12.6%
133867 10
 
5.5%
133848 9
 
4.9%
133834 8
 
4.4%
133815 6
 
3.3%
133826 6
 
3.3%
133832 5
 
2.7%
133828 5
 
2.7%
133809 5
 
2.7%
133858 5
 
2.7%
Other values (46) 101
55.2%
2024-05-11T14:28:13.985269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 408
37.0%
1 223
20.2%
8 213
19.3%
2 67
 
6.1%
0 56
 
5.1%
5 33
 
3.0%
4 31
 
2.8%
7 29
 
2.6%
6 24
 
2.2%
9 14
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1098
99.5%
Dash Punctuation 6
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 408
37.2%
1 223
20.3%
8 213
19.4%
2 67
 
6.1%
0 56
 
5.1%
5 33
 
3.0%
4 31
 
2.8%
7 29
 
2.6%
6 24
 
2.2%
9 14
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1104
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 408
37.0%
1 223
20.2%
8 213
19.3%
2 67
 
6.1%
0 56
 
5.1%
5 33
 
3.0%
4 31
 
2.8%
7 29
 
2.6%
6 24
 
2.2%
9 14
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 408
37.0%
1 223
20.2%
8 213
19.3%
2 67
 
6.1%
0 56
 
5.1%
5 33
 
3.0%
4 31
 
2.8%
7 29
 
2.6%
6 24
 
2.2%
9 14
 
1.3%

지번주소
Text

Distinct168
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T14:28:14.395278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35
Mean length23.863388
Min length17

Characters and Unicode

Total characters4367
Distinct characters52
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique154 ?
Unique (%)84.2%

Sample

1st row서울특별시 성동구 금호동1가 110번지
2nd row서울특별시 성동구 도선동 29번지
3rd row서울특별시 성동구 성수동2가 346-2번지
4th row서울특별시 성동구 마장동 781-13번지
5th row서울특별시 성동구 성수동2가 346-4번지
ValueCountFrequency (%)
서울특별시 183
23.9%
성동구 183
23.9%
성수동2가 46
 
6.0%
도선동 28
 
3.7%
행당동 22
 
2.9%
용답동 17
 
2.2%
마장동 14
 
1.8%
성수동1가 14
 
1.8%
지하1층 9
 
1.2%
하왕십리동 8
 
1.0%
Other values (195) 241
31.5%
2024-05-11T14:28:14.978449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
752
17.2%
동 367
 
8.4%
성 243
 
5.6%
2 193
 
4.4%
서 183
 
4.2%
구 183
 
4.2%
울 183
 
4.2%
시 183
 
4.2%
특 183
 
4.2%
별 183
 
4.2%
Other values (42) 1714
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2499
57.2%
Decimal Number 914
 
20.9%
Space Separator 752
 
17.2%
Dash Punctuation 163
 
3.7%
Other Punctuation 19
 
0.4%
Open Punctuation 10
 
0.2%
Close Punctuation 10
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 367
14.7%
성 243
9.7%
서 183
7.3%
구 183
7.3%
울 183
7.3%
시 183
7.3%
특 183
7.3%
별 183
7.3%
지 179
7.2%
번 166
 
6.6%
Other values (27) 446
17.8%
Decimal Number
ValueCountFrequency (%)
2 193
21.1%
1 149
16.3%
3 112
12.3%
6 84
9.2%
5 69
 
7.5%
4 68
 
7.4%
9 65
 
7.1%
0 62
 
6.8%
7 58
 
6.3%
8 54
 
5.9%
Space Separator
ValueCountFrequency (%)
752
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 163
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2499
57.2%
Common 1868
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 367
14.7%
성 243
9.7%
서 183
7.3%
구 183
7.3%
울 183
7.3%
시 183
7.3%
특 183
7.3%
별 183
7.3%
지 179
7.2%
번 166
 
6.6%
Other values (27) 446
17.8%
Common
ValueCountFrequency (%)
752
40.3%
2 193
 
10.3%
- 163
 
8.7%
1 149
 
8.0%
3 112
 
6.0%
6 84
 
4.5%
5 69
 
3.7%
4 68
 
3.6%
9 65
 
3.5%
0 62
 
3.3%
Other values (5) 151
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2499
57.2%
ASCII 1868
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
752
40.3%
2 193
 
10.3%
- 163
 
8.7%
1 149
 
8.0%
3 112
 
6.0%
6 84
 
4.5%
5 69
 
3.7%
4 68
 
3.6%
9 65
 
3.5%
0 62
 
3.3%
Other values (5) 151
 
8.1%
Hangul
ValueCountFrequency (%)
동 367
14.7%
성 243
9.7%
서 183
7.3%
구 183
7.3%
울 183
7.3%
시 183
7.3%
특 183
7.3%
별 183
7.3%
지 179
7.2%
번 166
 
6.6%
Other values (27) 446
17.8%

도로명주소
Text

MISSING 

Distinct53
Distinct (%)98.1%
Missing129
Missing (%)70.5%
Memory size1.6 KiB
2024-05-11T14:28:15.381598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length40
Mean length29.166667
Min length21

Characters and Unicode

Total characters1575
Distinct characters70
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)96.3%

Sample

1st row서울특별시 성동구 성덕정길 76 (성수동2가)
2nd row서울특별시 성동구 무학로2길 38 (도선동, 253-3 지하1층)
3rd row서울특별시 성동구 청계천로12가길 지하 75-3 (마장동, 마장동 470-5 지하1층)
4th row서울특별시 성동구 금호로 86, 가동 지1층 1호 (금호동1가)
5th row서울특별시 성동구 성덕정19길 3 (성수동2가)
ValueCountFrequency (%)
서울특별시 54
 
17.8%
성동구 54
 
17.8%
성수동2가 15
 
4.9%
지하1층 9
 
3.0%
왕십리로 8
 
2.6%
도선동 7
 
2.3%
마장동 5
 
1.6%
지하 5
 
1.6%
무학로2길 5
 
1.6%
성덕정길 5
 
1.6%
Other values (97) 137
45.1%
2024-05-11T14:28:16.083539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
250
 
15.9%
동 113
 
7.2%
성 82
 
5.2%
2 63
 
4.0%
) 57
 
3.6%
( 57
 
3.6%
서 55
 
3.5%
특 54
 
3.4%
별 54
 
3.4%
시 54
 
3.4%
Other values (60) 736
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 913
58.0%
Decimal Number 251
 
15.9%
Space Separator 250
 
15.9%
Close Punctuation 57
 
3.6%
Open Punctuation 57
 
3.6%
Other Punctuation 29
 
1.8%
Dash Punctuation 18
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 113
 
12.4%
성 82
 
9.0%
서 55
 
6.0%
특 54
 
5.9%
별 54
 
5.9%
시 54
 
5.9%
구 54
 
5.9%
울 54
 
5.9%
로 43
 
4.7%
가 34
 
3.7%
Other values (45) 316
34.6%
Decimal Number
ValueCountFrequency (%)
2 63
25.1%
1 43
17.1%
3 33
13.1%
4 25
 
10.0%
0 19
 
7.6%
6 16
 
6.4%
7 15
 
6.0%
9 14
 
5.6%
5 12
 
4.8%
8 11
 
4.4%
Space Separator
ValueCountFrequency (%)
250
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 913
58.0%
Common 662
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 113
 
12.4%
성 82
 
9.0%
서 55
 
6.0%
특 54
 
5.9%
별 54
 
5.9%
시 54
 
5.9%
구 54
 
5.9%
울 54
 
5.9%
로 43
 
4.7%
가 34
 
3.7%
Other values (45) 316
34.6%
Common
ValueCountFrequency (%)
250
37.8%
2 63
 
9.5%
) 57
 
8.6%
( 57
 
8.6%
1 43
 
6.5%
3 33
 
5.0%
, 29
 
4.4%
4 25
 
3.8%
0 19
 
2.9%
- 18
 
2.7%
Other values (5) 68
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 913
58.0%
ASCII 662
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
250
37.8%
2 63
 
9.5%
) 57
 
8.6%
( 57
 
8.6%
1 43
 
6.5%
3 33
 
5.0%
, 29
 
4.4%
4 25
 
3.8%
0 19
 
2.9%
- 18
 
2.7%
Other values (5) 68
 
10.3%
Hangul
ValueCountFrequency (%)
동 113
 
12.4%
성 82
 
9.0%
서 55
 
6.0%
특 54
 
5.9%
별 54
 
5.9%
시 54
 
5.9%
구 54
 
5.9%
울 54
 
5.9%
로 43
 
4.7%
가 34
 
3.7%
Other values (45) 316
34.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)54.2%
Missing135
Missing (%)73.8%
Infinite0
Infinite (%)0.0%
Mean4743.3958
Minimum4704
Maximum4804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T14:28:16.297101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4704
5-th percentile4707
Q14709
median4728
Q34777.25
95-th percentile4794.65
Maximum4804
Range100
Interquartile range (IQR)68.25

Descriptive statistics

Standard deviation34.959393
Coefficient of variation (CV)0.0073701192
Kurtosis-1.5511407
Mean4743.3958
Median Absolute Deviation (MAD)21
Skewness0.37375623
Sum227683
Variance1222.1591
MonotonicityNot monotonic
2024-05-11T14:28:16.495899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
4709 11
 
6.0%
4707 3
 
1.6%
4775 3
 
1.6%
4718 3
 
1.6%
4804 2
 
1.1%
4778 2
 
1.1%
4794 2
 
1.1%
4730 2
 
1.1%
4726 2
 
1.1%
4715 2
 
1.1%
Other values (16) 16
 
8.7%
(Missing) 135
73.8%
ValueCountFrequency (%)
4704 1
 
0.5%
4707 3
 
1.6%
4709 11
6.0%
4710 1
 
0.5%
4715 2
 
1.1%
4718 3
 
1.6%
4725 1
 
0.5%
4726 2
 
1.1%
4730 2
 
1.1%
4745 1
 
0.5%
ValueCountFrequency (%)
4804 2
1.1%
4795 1
0.5%
4794 2
1.1%
4793 1
0.5%
4792 1
0.5%
4786 1
0.5%
4782 1
0.5%
4781 1
0.5%
4778 2
1.1%
4777 1
0.5%

사업장명
Text

Distinct165
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T14:28:16.916702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length4.4918033
Min length1

Characters and Unicode

Total characters822
Distinct characters245
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

Unique147 ?
Unique (%)80.3%

Sample

1st row노래하는포장마차
2nd row다모아
3rd row고향산천단란주점
4th row가시버시단란주점
5th row쫄랑이노래주점
ValueCountFrequency (%)
동경 2
 
1.1%
콩두단란주점 2
 
1.1%
비엠더블유 2
 
1.1%
태평양 2
 
1.1%
영상 2
 
1.1%
대주 2
 
1.1%
아리랑 2
 
1.1%
이태백 2
 
1.1%
소리창고 2
 
1.1%
르네상스 2
 
1.1%
Other values (160) 168
89.4%
2024-05-11T14:28:17.636336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 62
 
7.5%
점 60
 
7.3%
란 44
 
5.4%
단 43
 
5.2%
스 25
 
3.0%
래 18
 
2.2%
노 18
 
2.2%
리 17
 
2.1%
이 14
 
1.7%
0 10
 
1.2%
Other values (235) 511
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 753
91.6%
Uppercase Letter 25
 
3.0%
Decimal Number 22
 
2.7%
Open Punctuation 6
 
0.7%
Close Punctuation 6
 
0.7%
Space Separator 5
 
0.6%
Lowercase Letter 3
 
0.4%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 62
 
8.2%
점 60
 
8.0%
란 44
 
5.8%
단 43
 
5.7%
스 25
 
3.3%
래 18
 
2.4%
노 18
 
2.4%
리 17
 
2.3%
이 14
 
1.9%
시 9
 
1.2%
Other values (206) 443
58.8%
Uppercase Letter
ValueCountFrequency (%)
E 4
16.0%
V 3
12.0%
B 2
 
8.0%
I 2
 
8.0%
L 2
 
8.0%
M 2
 
8.0%
K 1
 
4.0%
C 1
 
4.0%
Y 1
 
4.0%
O 1
 
4.0%
Other values (6) 6
24.0%
Decimal Number
ValueCountFrequency (%)
0 10
45.5%
8 6
27.3%
7 4
 
18.2%
5 1
 
4.5%
9 1
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
o 1
33.3%
x 1
33.3%
f 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
! 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 753
91.6%
Common 41
 
5.0%
Latin 28
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 62
 
8.2%
점 60
 
8.0%
란 44
 
5.8%
단 43
 
5.7%
스 25
 
3.3%
래 18
 
2.4%
노 18
 
2.4%
리 17
 
2.3%
이 14
 
1.9%
시 9
 
1.2%
Other values (206) 443
58.8%
Latin
ValueCountFrequency (%)
E 4
14.3%
V 3
 
10.7%
B 2
 
7.1%
I 2
 
7.1%
L 2
 
7.1%
M 2
 
7.1%
o 1
 
3.6%
x 1
 
3.6%
f 1
 
3.6%
K 1
 
3.6%
Other values (9) 9
32.1%
Common
ValueCountFrequency (%)
0 10
24.4%
( 6
14.6%
) 6
14.6%
8 6
14.6%
5
12.2%
7 4
 
9.8%
. 1
 
2.4%
! 1
 
2.4%
5 1
 
2.4%
9 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 753
91.6%
ASCII 69
 
8.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 62
 
8.2%
점 60
 
8.0%
란 44
 
5.8%
단 43
 
5.7%
스 25
 
3.3%
래 18
 
2.4%
노 18
 
2.4%
리 17
 
2.3%
이 14
 
1.9%
시 9
 
1.2%
Other values (206) 443
58.8%
ASCII
ValueCountFrequency (%)
0 10
14.5%
( 6
 
8.7%
) 6
 
8.7%
8 6
 
8.7%
5
 
7.2%
E 4
 
5.8%
7 4
 
5.8%
V 3
 
4.3%
B 2
 
2.9%
I 2
 
2.9%
Other values (19) 21
30.4%

최종수정일자
Date

Distinct100
Distinct (%)54.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum1999-04-21 00:00:00
Maximum2024-03-21 15:59:53
2024-05-11T14:28:17.936505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:28:18.221652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
I
156 
U
27 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 156
85.2%
U 27
 
14.8%

Length

2024-05-11T14:28:18.527473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:18.712325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 156
85.2%
u 27
 
14.8%

데이터갱신일자
Categorical

IMBALANCE 

Distinct26
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2018-08-31 23:59:59.0
156 
2022-12-04 00:02:00.0
 
2
2022-12-02 00:01:00.0
 
2
2022-12-07 23:02:00.0
 
1
2020-11-18 02:40:00.0
 
1
Other values (21)
21 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique23 ?
Unique (%)12.6%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2019-08-09 02:40:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 156
85.2%
2022-12-04 00:02:00.0 2
 
1.1%
2022-12-02 00:01:00.0 2
 
1.1%
2022-12-07 23:02:00.0 1
 
0.5%
2020-11-18 02:40:00.0 1
 
0.5%
2023-12-02 22:03:00.0 1
 
0.5%
2019-07-18 02:40:00.0 1
 
0.5%
2021-10-31 23:06:00.0 1
 
0.5%
2018-09-17 23:59:59.0 1
 
0.5%
2022-11-30 22:02:00.0 1
 
0.5%
Other values (16) 16
 
8.7%

Length

2024-05-11T14:28:18.894537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23:59:59.0 157
42.9%
2018-08-31 156
42.6%
02:40:00.0 12
 
3.3%
2022-12-04 3
 
0.8%
00:02:00.0 2
 
0.5%
2022-12-02 2
 
0.5%
00:01:00.0 2
 
0.5%
2021-10-31 2
 
0.5%
2019-10-10 1
 
0.3%
22:08:00.0 1
 
0.3%
Other values (28) 28
 
7.7%

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
단란주점
183 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단란주점 183
100.0%

Length

2024-05-11T14:28:19.408459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:19.578014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단란주점 183
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct150
Distinct (%)88.2%
Missing13
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean203766.06
Minimum201560.9
Maximum206299.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T14:28:19.754438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201560.9
5-th percentile201746.79
Q1202891.31
median203796.64
Q3204753.74
95-th percentile205486.83
Maximum206299.73
Range4738.8347
Interquartile range (IQR)1862.4297

Descriptive statistics

Standard deviation1185.6491
Coefficient of variation (CV)0.005818678
Kurtosis-1.0917339
Mean203766.06
Median Absolute Deviation (MAD)926.24006
Skewness-0.060397252
Sum34640229
Variance1405763.7
MonotonicityNot monotonic
2024-05-11T14:28:19.987067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205371.082382793 3
 
1.6%
203956.270639014 2
 
1.1%
204754.415244381 2
 
1.1%
204848.299601913 2
 
1.1%
202207.929114266 2
 
1.1%
201871.482216012 2
 
1.1%
202990.555865701 2
 
1.1%
202967.042456635 2
 
1.1%
204620.431033989 2
 
1.1%
202962.989955324 2
 
1.1%
Other values (140) 149
81.4%
(Missing) 13
 
7.1%
ValueCountFrequency (%)
201560.899780182 2
1.1%
201660.781574598 1
0.5%
201692.069726796 1
0.5%
201708.144077028 1
0.5%
201720.668163129 1
0.5%
201724.912855008 1
0.5%
201725.507829035 1
0.5%
201729.474463119 1
0.5%
201767.953770014 1
0.5%
201774.771809814 1
0.5%
ValueCountFrequency (%)
206299.734441078 1
0.5%
205837.640591417 1
0.5%
205835.252894208 1
0.5%
205810.737642867 1
0.5%
205779.087396763 1
0.5%
205673.798753823 1
0.5%
205609.02502616 1
0.5%
205559.255165314 1
0.5%
205491.100216356 1
0.5%
205481.605724684 1
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct150
Distinct (%)88.2%
Missing13
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean450232.64
Minimum448229.13
Maximum452093.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T14:28:20.358574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448229.13
5-th percentile448400.51
Q1449390.4
median450324.97
Q3451183.07
95-th percentile451647.51
Maximum452093.43
Range3864.2989
Interquartile range (IQR)1792.6703

Descriptive statistics

Standard deviation1118.9334
Coefficient of variation (CV)0.0024852339
Kurtosis-1.3164884
Mean450232.64
Median Absolute Deviation (MAD)859.31287
Skewness-0.23727662
Sum76539549
Variance1252012
MonotonicityNot monotonic
2024-05-11T14:28:20.634928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448688.200477047 3
 
1.6%
451691.511506284 2
 
1.1%
449307.186204768 2
 
1.1%
449551.236385759 2
 
1.1%
449907.980065843 2
 
1.1%
449569.540265379 2
 
1.1%
451158.588973113 2
 
1.1%
451118.809600324 2
 
1.1%
451542.289258894 2
 
1.1%
451179.685189347 2
 
1.1%
Other values (140) 149
81.4%
(Missing) 13
 
7.1%
ValueCountFrequency (%)
448229.126737125 1
0.5%
448231.135811849 1
0.5%
448257.988722667 1
0.5%
448343.936023265 1
0.5%
448351.173333696 1
0.5%
448361.655898977 1
0.5%
448366.447718492 1
0.5%
448399.307778475 2
1.1%
448401.981843555 2
1.1%
448403.223425943 1
0.5%
ValueCountFrequency (%)
452093.42563973 1
0.5%
452019.132498433 1
0.5%
452004.414611622 1
0.5%
451977.414453728 1
0.5%
451965.03442982 1
0.5%
451739.812477467 1
0.5%
451691.511506284 2
1.1%
451662.364073697 1
0.5%
451629.351381183 1
0.5%
451621.422306344 1
0.5%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
단란주점
170 
<NA>
 
13

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단란주점 170
92.9%
<NA> 13
 
7.1%

Length

2024-05-11T14:28:20.881644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:21.056075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단란주점 170
92.9%
na 13
 
7.1%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
0
140 
<NA>
34 
1
 
7
3
 
1
2
 
1

Length

Max length4
Median length1
Mean length1.557377
Min length1

Unique

Unique2 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 140
76.5%
<NA> 34
 
18.6%
1 7
 
3.8%
3 1
 
0.5%
2 1
 
0.5%

Length

2024-05-11T14:28:21.276031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:21.476602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 140
76.5%
na 34
 
18.6%
1 7
 
3.8%
3 1
 
0.5%
2 1
 
0.5%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
0
142 
<NA>
35 
1
 
5
2
 
1

Length

Max length4
Median length1
Mean length1.5737705
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 142
77.6%
<NA> 35
 
19.1%
1 5
 
2.7%
2 1
 
0.5%

Length

2024-05-11T14:28:21.682871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:21.871927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 142
77.6%
na 35
 
19.1%
1 5
 
2.7%
2 1
 
0.5%

영업장주변구분명
Categorical

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
기타
97 
주택가주변
49 
<NA>
25 
유흥업소밀집지역
12 

Length

Max length8
Median length2
Mean length3.4699454
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 97
53.0%
주택가주변 49
26.8%
<NA> 25
 
13.7%
유흥업소밀집지역 12
 
6.6%

Length

2024-05-11T14:28:22.059931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:22.271216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 97
53.0%
주택가주변 49
26.8%
na 25
 
13.7%
유흥업소밀집지역 12
 
6.6%

등급구분명
Categorical

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
기타
146 
<NA>
31 
자율
 
6

Length

Max length4
Median length2
Mean length2.3387978
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 146
79.8%
<NA> 31
 
16.9%
자율 6
 
3.3%

Length

2024-05-11T14:28:22.515123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:22.718220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 146
79.8%
na 31
 
16.9%
자율 6
 
3.3%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
상수도전용
151 
<NA>
29 
간이상수도
 
2
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length5
Mean length4.9071038
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 151
82.5%
<NA> 29
 
15.8%
간이상수도 2
 
1.1%
상수도(음용)지하수(주방용)겸용 1
 
0.5%

Length

2024-05-11T14:28:22.955634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:23.209473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 151
82.5%
na 29
 
15.8%
간이상수도 2
 
1.1%
상수도(음용)지하수(주방용)겸용 1
 
0.5%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
181 
0
 
2

Length

Max length4
Median length4
Mean length3.9672131
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> 181
98.9%
0 2
 
1.1%

Length

2024-05-11T14:28:23.409273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:23.604978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 181
98.9%
0 2
 
1.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
181 
0
 
2

Length

Max length4
Median length4
Mean length3.9672131
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> 181
98.9%
0 2
 
1.1%

Length

2024-05-11T14:28:23.810365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:24.019920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 181
98.9%
0 2
 
1.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
181 
0
 
2

Length

Max length4
Median length4
Mean length3.9672131
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> 181
98.9%
0 2
 
1.1%

Length

2024-05-11T14:28:24.214598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:24.405977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 181
98.9%
0 2
 
1.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
181 
0
 
2

Length

Max length4
Median length4
Mean length3.9672131
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> 181
98.9%
0 2
 
1.1%

Length

2024-05-11T14:28:24.696012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:24.888390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 181
98.9%
0 2
 
1.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
181 
0
 
2

Length

Max length4
Median length4
Mean length3.9672131
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> 181
98.9%
0 2
 
1.1%

Length

2024-05-11T14:28:25.112906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:25.343711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 181
98.9%
0 2
 
1.1%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing183
Missing (%)100.0%
Memory size1.7 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
181 
0
 
2

Length

Max length4
Median length4
Mean length3.9672131
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> 181
98.9%
0 2
 
1.1%

Length

2024-05-11T14:28:25.560751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:25.749488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 181
98.9%
0 2
 
1.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
181 
0
 
2

Length

Max length4
Median length4
Mean length3.9672131
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> 181
98.9%
0 2
 
1.1%

Length

2024-05-11T14:28:25.923336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:26.103652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 181
98.9%
0 2
 
1.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.2%
Missing13
Missing (%)7.1%
Memory size498.0 B
False
169 
True
 
1
(Missing)
 
13
ValueCountFrequency (%)
False 169
92.3%
True 1
 
0.5%
(Missing) 13
 
7.1%
2024-05-11T14:28:26.265643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct161
Distinct (%)94.7%
Missing13
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean93.637471
Minimum0
Maximum179.22
Zeros1
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T14:28:26.474261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile46.562
Q171.5725
median92.605
Q3118.6375
95-th percentile147.1125
Maximum179.22
Range179.22
Interquartile range (IQR)47.065

Descriptive statistics

Standard deviation31.29536
Coefficient of variation (CV)0.33421834
Kurtosis-0.36924296
Mean93.637471
Median Absolute Deviation (MAD)23.59
Skewness0.12017948
Sum15918.37
Variance979.39955
MonotonicityNot monotonic
2024-05-11T14:28:26.734361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58.96 3
 
1.6%
148.5 2
 
1.1%
41.86 2
 
1.1%
148.03 2
 
1.1%
71.76 2
 
1.1%
75.16 2
 
1.1%
147.99 2
 
1.1%
75.53 2
 
1.1%
117.89 1
 
0.5%
91.87 1
 
0.5%
Other values (151) 151
82.5%
(Missing) 13
 
7.1%
ValueCountFrequency (%)
0.0 1
0.5%
29.49 1
0.5%
35.0 1
0.5%
38.43 1
0.5%
41.78 1
0.5%
41.86 2
1.1%
45.75 1
0.5%
46.22 1
0.5%
46.98 1
0.5%
47.84 1
0.5%
ValueCountFrequency (%)
179.22 1
0.5%
148.81 1
0.5%
148.5 2
1.1%
148.3 1
0.5%
148.03 2
1.1%
147.99 2
1.1%
146.04 1
0.5%
144.71 1
0.5%
144.54 1
0.5%
143.82 1
0.5%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing183
Missing (%)100.0%
Memory size1.7 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing183
Missing (%)100.0%
Memory size1.7 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing183
Missing (%)100.0%
Memory size1.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030300003030000-103-1993-0009019931202<NA>3폐업2폐업20081002<NA><NA><NA>02229823670.0133800서울특별시 성동구 금호동1가 110번지<NA><NA>노래하는포장마차2008-03-10 14:44:03I2018-08-31 23:59:59.0단란주점201720.668163450363.626141단란주점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
130300003030000-103-1993-0101619930908<NA>3폐업2폐업20010813<NA><NA><NA>02140.53133882서울특별시 성동구 도선동 29번지<NA><NA>다모아2001-12-10 00:00:00I2018-08-31 23:59:59.0단란주점203032.062295451134.858623단란주점00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N140.53<NA><NA><NA>
230300003030000-103-1993-0105619931222<NA>3폐업2폐업19971011<NA><NA><NA>02 465148793.65133828서울특별시 성동구 성수동2가 346-2번지<NA><NA>고향산천단란주점2001-09-25 00:00:00I2018-08-31 23:59:59.0단란주점204531.8628448399.307778단란주점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N93.65<NA><NA><NA>
330300003030000-103-1993-0107519931130<NA>3폐업2폐업19970707<NA><NA><NA>02 2944087104.73133815서울특별시 성동구 마장동 781-13번지<NA><NA>가시버시단란주점2001-09-25 00:00:00I2018-08-31 23:59:59.0단란주점203864.495851451629.351381단란주점00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N104.73<NA><NA><NA>
430300003030000-103-1993-0107719931203<NA>1영업/정상1영업<NA><NA><NA><NA>02 462923978.72133828서울특별시 성동구 성수동2가 346-4번지서울특별시 성동구 성덕정길 76 (성수동2가)4775쫄랑이노래주점2019-08-07 14:01:21U2019-08-09 02:40:00.0단란주점204516.477168448403.223426단란주점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N78.72<NA><NA><NA>
530300003030000-103-1993-0107819931211<NA>3폐업2폐업19991109<NA><NA><NA>02 4650966118.15133836서울특별시 성동구 송정동 66-270번지<NA><NA>벤츠2001-09-25 00:00:00I2018-08-31 23:59:59.0단란주점205609.025026449567.603299단란주점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N118.15<NA><NA><NA>
630300003030000-103-1993-0107919931211<NA>3폐업2폐업20101214<NA><NA><NA>02 497699165.63133826서울특별시 성동구 성수동2가 209-1번지<NA><NA>프랜드2007-12-26 14:59:36I2018-08-31 23:59:59.0단란주점205222.486515448231.135812단란주점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N65.63<NA><NA><NA>
730300003030000-103-1993-0108019931218<NA>3폐업2폐업19970804<NA><NA><NA>020491059875.16133828서울특별시 성동구 성수동2가 350-0번지<NA><NA>키단란주점2001-09-25 00:00:00I2018-08-31 23:59:59.0단란주점204474.754282448401.981844단란주점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N75.16<NA><NA><NA>
830300003030000-103-1993-0108119931227<NA>3폐업2폐업20090522<NA><NA><NA>0222940776119.23133091서울특별시 성동구 금호동1가 125-1번지 ,126-2, 124, 123-2<NA><NA>만남2001-12-07 00:00:00I2018-08-31 23:59:59.0단란주점201725.507829450286.30617단란주점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N119.23<NA><NA><NA>
930300003030000-103-1993-0108219931230<NA>3폐업2폐업20060313<NA><NA><NA>022297169593.5133845서울특별시 성동구 옥수동 523-1번지<NA><NA>여인천하2004-02-25 00:00:00I2018-08-31 23:59:59.0단란주점<NA><NA>단란주점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N93.5<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
17330300003030000-103-2002-0000320021204<NA>1영업/정상1영업<NA><NA><NA><NA>022299775075.53133882서울특별시 성동구 도선동 253-5번지 (지상2층)서울특별시 성동구 왕십리로24길 3 (도선동,(지상2층))4709안동역2019-10-08 18:45:50U2019-10-10 02:40:00.0단란주점202900.174382451184.194187단란주점00기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N75.53<NA><NA><NA>
17430300003030000-103-2003-0000120030502<NA>3폐업2폐업20050825<NA><NA><NA>2295144074.5133882서울특별시 성동구 도선동 64번지 (지하1층)<NA><NA>산타페2003-12-27 00:00:00I2018-08-31 23:59:59.0단란주점202961.064684451156.937353단란주점10유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N74.5<NA><NA><NA>
17530300003030000-103-2003-0000220030612<NA>1영업/정상1영업<NA><NA><NA><NA>022290027849.9133882서울특별시 성동구 도선동 253-4번지서울특별시 성동구 왕십리로24길 5 (도선동)4709테마2020-03-30 11:57:25U2020-04-01 02:40:00.0단란주점202909.052163451191.46263단란주점00유흥업소밀집지역<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N49.9<NA><NA><NA>
17630300003030000-103-2004-0000120041123<NA>1영업/정상1영업<NA><NA><NA><NA>07081166574101.48133882서울특별시 성동구 도선동 148번지 (지상2,3층)서울특별시 성동구 무학로2길 41 (도선동,(지상2,3층))4709앤2018-03-16 16:11:39I2018-08-31 23:59:59.0단란주점202962.989955451179.685189단란주점00유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N101.48<NA><NA><NA>
17730300003030000-103-2004-0000220041125<NA>1영업/정상1영업<NA><NA><NA><NA>0222958296119.22133882서울특별시 성동구 도선동 161번지 지하1층서울특별시 성동구 왕십리로24길 12 (도선동,지하1층)4709왕코 뮤직타운2019-09-26 14:11:51U2019-09-28 02:40:00.0단란주점202960.659418451249.820379단란주점00유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N119.22<NA><NA><NA>
17830300003030000-103-2006-0000120061215<NA>1영업/정상1영업<NA><NA><NA><NA><NA>64.98133882서울특별시 성동구 도선동 253-1번지 지하1층서울특별시 성동구 무학로2길 36 (도선동,지하1층)4709황금2019-10-14 16:22:34U2019-10-16 02:40:00.0단란주점202893.088358451205.200413단란주점10유흥업소밀집지역<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N64.98<NA><NA><NA>
17930300003030000-103-2008-000012008-01-02<NA>1영업/정상1영업<NA><NA><NA><NA>00022294497759.59133-882서울특별시 성동구 도선동 253-10 (지하1층)서울특별시 성동구 왕십리로 330-6, 지하1층 (도선동, 253-10)4709사파리2024-01-24 15:05:29U2023-11-30 22:06:00.0단란주점202894.670866451177.363713<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18030300003030000-103-2008-0000220081119<NA>3폐업2폐업20161208<NA><NA><NA>000222949933114.35133882서울특별시 성동구 도선동 29번지 지상3층서울특별시 성동구 왕십리로20길 8 (도선동,지상3층)4709모나코2014-04-28 09:36:22I2018-08-31 23:59:59.0단란주점203032.062295451134.858623단란주점21기타기타간이상수도<NA><NA><NA><NA><NA><NA><NA><NA>N114.35<NA><NA><NA>
18130300003030000-103-2014-0000120140402<NA>1영업/정상1영업<NA><NA><NA><NA><NA>45.75133882서울특별시 성동구 도선동 68번지서울특별시 성동구 무학로2길 46 (도선동)4709엠비씨(MBC)단란주점2016-06-20 13:54:54I2018-08-31 23:59:59.0단란주점202985.066832451131.062598단란주점<NA><NA>유흥업소밀집지역<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N45.75<NA><NA><NA>
18230300003030000-103-2014-0000220141217<NA>1영업/정상1영업<NA><NA><NA><NA><NA>98.5133882서울특별시 성동구 도선동 276번지서울특별시 성동구 무학로2길 32, 2층 (도선동)4709와이제이(YJ)2017-09-11 16:29:00I2018-08-31 23:59:59.0단란주점202869.629533451218.97949단란주점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>Y98.5<NA><NA><NA>