Overview

Dataset statistics

Number of variables44
Number of observations475
Missing cells4730
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory175.0 KiB
Average record size in memory377.3 B

Variable types

Categorical20
Text6
DateTime4
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
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-18547/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 is highly imbalanced (59.0%)Imbalance
남성종사자수 is highly imbalanced (51.8%)Imbalance
급수시설구분명 is highly imbalanced (64.8%)Imbalance
총인원 is highly imbalanced (88.9%)Imbalance
본사종업원수 is highly imbalanced (88.9%)Imbalance
공장사무직종업원수 is highly imbalanced (88.9%)Imbalance
공장판매직종업원수 is highly imbalanced (88.9%)Imbalance
공장생산직종업원수 is highly imbalanced (88.9%)Imbalance
보증액 is highly imbalanced (88.9%)Imbalance
월세액 is highly imbalanced (88.9%)Imbalance
다중이용업소여부 is highly imbalanced (64.7%)Imbalance
인허가취소일자 has 475 (100.0%) missing valuesMissing
폐업일자 has 80 (16.8%) missing valuesMissing
휴업시작일자 has 475 (100.0%) missing valuesMissing
휴업종료일자 has 475 (100.0%) missing valuesMissing
재개업일자 has 475 (100.0%) missing valuesMissing
전화번호 has 57 (12.0%) missing valuesMissing
도로명주소 has 352 (74.1%) missing valuesMissing
도로명우편번호 has 353 (74.3%) missing valuesMissing
좌표정보(X) has 5 (1.1%) missing valuesMissing
좌표정보(Y) has 5 (1.1%) missing valuesMissing
건물소유구분명 has 475 (100.0%) missing valuesMissing
다중이용업소여부 has 39 (8.2%) missing valuesMissing
시설총규모 has 39 (8.2%) missing valuesMissing
전통업소지정번호 has 475 (100.0%) missing valuesMissing
전통업소주된음식 has 475 (100.0%) missing valuesMissing
홈페이지 has 475 (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 03:29:06.527155
Analysis finished2024-05-11 03:29:08.238221
Duration1.71 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3200000
475 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 475
100.0%

Length

2024-05-11T03:29:08.546562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:08.941002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 475
100.0%

관리번호
Text

UNIQUE 

Distinct475
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T03:29:09.519935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10450
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

Unique475 ?
Unique (%)100.0%

Sample

1st row3200000-103-1993-07856
2nd row3200000-103-1993-07857
3rd row3200000-103-1993-07858
4th row3200000-103-1993-07859
5th row3200000-103-1993-07861
ValueCountFrequency (%)
3200000-103-1993-07856 1
 
0.2%
3200000-103-1998-09987 1
 
0.2%
3200000-103-1999-08209 1
 
0.2%
3200000-103-1999-08208 1
 
0.2%
3200000-103-1999-08199 1
 
0.2%
3200000-103-1999-08197 1
 
0.2%
3200000-103-1999-08193 1
 
0.2%
3200000-103-1999-08162 1
 
0.2%
3200000-103-1999-08119 1
 
0.2%
3200000-103-1999-08088 1
 
0.2%
Other values (465) 465
97.9%
2024-05-11T03:29:10.935524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4003
38.3%
- 1425
 
13.6%
3 1125
 
10.8%
1 1112
 
10.6%
9 904
 
8.7%
2 756
 
7.2%
8 377
 
3.6%
7 270
 
2.6%
5 166
 
1.6%
4 162
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9025
86.4%
Dash Punctuation 1425
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4003
44.4%
3 1125
 
12.5%
1 1112
 
12.3%
9 904
 
10.0%
2 756
 
8.4%
8 377
 
4.2%
7 270
 
3.0%
5 166
 
1.8%
4 162
 
1.8%
6 150
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 1425
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10450
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4003
38.3%
- 1425
 
13.6%
3 1125
 
10.8%
1 1112
 
10.6%
9 904
 
8.7%
2 756
 
7.2%
8 377
 
3.6%
7 270
 
2.6%
5 166
 
1.6%
4 162
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4003
38.3%
- 1425
 
13.6%
3 1125
 
10.8%
1 1112
 
10.6%
9 904
 
8.7%
2 756
 
7.2%
8 377
 
3.6%
7 270
 
2.6%
5 166
 
1.6%
4 162
 
1.6%

인허가일자
Date

Distinct422
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1993-08-18 00:00:00
Maximum2024-03-29 00:00:00
2024-05-11T03:29:11.616266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:29:12.246141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing475
Missing (%)100.0%
Memory size4.3 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3
395 
1
80 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 395
83.2%
1 80
 
16.8%

Length

2024-05-11T03:29:12.696534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:13.062453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 395
83.2%
1 80
 
16.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
395 
영업/정상
80 

Length

Max length5
Median length2
Mean length2.5052632
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 395
83.2%
영업/정상 80
 
16.8%

Length

2024-05-11T03:29:13.503358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:13.881565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 395
83.2%
영업/정상 80
 
16.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2
395 
1
80 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 395
83.2%
1 80
 
16.8%

Length

2024-05-11T03:29:14.268359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:14.748609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 395
83.2%
1 80
 
16.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
395 
영업
80 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 395
83.2%
영업 80
 
16.8%

Length

2024-05-11T03:29:15.233461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:15.617717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 395
83.2%
영업 80
 
16.8%

폐업일자
Date

MISSING 

Distinct355
Distinct (%)89.9%
Missing80
Missing (%)16.8%
Memory size3.8 KiB
Minimum1994-02-05 00:00:00
Maximum2023-05-25 00:00:00
2024-05-11T03:29:16.129067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:29:16.738792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing475
Missing (%)100.0%
Memory size4.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing475
Missing (%)100.0%
Memory size4.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing475
Missing (%)100.0%
Memory size4.3 KiB

전화번호
Text

MISSING 

Distinct299
Distinct (%)71.5%
Missing57
Missing (%)12.0%
Memory size3.8 KiB
2024-05-11T03:29:17.589512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length8.1698565
Min length2

Characters and Unicode

Total characters3415
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

Unique289 ?
Unique (%)69.1%

Sample

1st row0208785045
2nd row02 00000
3rd row02
4th row0208830388
5th row02 8364885
ValueCountFrequency (%)
02 389
53.3%
00000 10
 
1.4%
0 5
 
0.7%
8883771 3
 
0.4%
865 3
 
0.4%
8859842 2
 
0.3%
872 2
 
0.3%
8771822 2
 
0.3%
875 2
 
0.3%
5873838 2
 
0.3%
Other values (307) 310
42.5%
2024-05-11T03:29:19.031644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 635
18.6%
2 585
17.1%
8 554
16.2%
367
10.7%
7 261
7.6%
5 213
 
6.2%
3 179
 
5.2%
6 179
 
5.2%
1 159
 
4.7%
4 156
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3048
89.3%
Space Separator 367
 
10.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 635
20.8%
2 585
19.2%
8 554
18.2%
7 261
8.6%
5 213
 
7.0%
3 179
 
5.9%
6 179
 
5.9%
1 159
 
5.2%
4 156
 
5.1%
9 127
 
4.2%
Space Separator
ValueCountFrequency (%)
367
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3415
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 635
18.6%
2 585
17.1%
8 554
16.2%
367
10.7%
7 261
7.6%
5 213
 
6.2%
3 179
 
5.2%
6 179
 
5.2%
1 159
 
4.7%
4 156
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 635
18.6%
2 585
17.1%
8 554
16.2%
367
10.7%
7 261
7.6%
5 213
 
6.2%
3 179
 
5.2%
6 179
 
5.2%
1 159
 
4.7%
4 156
 
4.6%

소재지면적
Real number (ℝ)

Distinct452
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.492105
Minimum12.37
Maximum354.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T03:29:19.668444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12.37
5-th percentile54.263
Q173.105
median94.66
Q3122.345
95-th percentile147.946
Maximum354.74
Range342.37
Interquartile range (IQR)49.24

Descriptive statistics

Standard deviation34.419757
Coefficient of variation (CV)0.34946717
Kurtosis6.0447283
Mean98.492105
Median Absolute Deviation (MAD)23.58
Skewness1.2276069
Sum46783.75
Variance1184.7197
MonotonicityNot monotonic
2024-05-11T03:29:20.379319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
77.57 2
 
0.4%
73.92 2
 
0.4%
133.75 2
 
0.4%
91.96 2
 
0.4%
78.2 2
 
0.4%
60.9 2
 
0.4%
75.59 2
 
0.4%
148.62 2
 
0.4%
71.08 2
 
0.4%
99.87 2
 
0.4%
Other values (442) 455
95.8%
ValueCountFrequency (%)
12.37 1
0.2%
25.73 1
0.2%
30.98 1
0.2%
31.0 1
0.2%
35.0 1
0.2%
41.0 1
0.2%
42.8 1
0.2%
43.1 1
0.2%
43.22 1
0.2%
45.15 1
0.2%
ValueCountFrequency (%)
354.74 1
0.2%
241.87 1
0.2%
208.75 1
0.2%
192.92 1
0.2%
187.14 1
0.2%
185.84 1
0.2%
171.63 1
0.2%
170.57 1
0.2%
166.64 1
0.2%
158.28 1
0.2%

소재지우편번호
Text

Distinct73
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T03:29:20.982255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0505263
Min length6

Characters and Unicode

Total characters2874
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

Unique25 ?
Unique (%)5.3%

Sample

1st row151892
2nd row151836
3rd row151848
4th row151890
5th row151836
ValueCountFrequency (%)
151892 49
 
10.3%
151930 49
 
10.3%
151890 41
 
8.6%
151800 31
 
6.5%
151903 27
 
5.7%
151848 21
 
4.4%
151836 20
 
4.2%
151891 19
 
4.0%
151875 16
 
3.4%
151876 14
 
2.9%
Other values (63) 188
39.6%
2024-05-11T03:29:22.214605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1003
34.9%
5 518
18.0%
8 415
14.4%
9 247
 
8.6%
0 232
 
8.1%
3 150
 
5.2%
4 91
 
3.2%
2 83
 
2.9%
7 56
 
1.9%
6 55
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2850
99.2%
Dash Punctuation 24
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1003
35.2%
5 518
18.2%
8 415
14.6%
9 247
 
8.7%
0 232
 
8.1%
3 150
 
5.3%
4 91
 
3.2%
2 83
 
2.9%
7 56
 
2.0%
6 55
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2874
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1003
34.9%
5 518
18.0%
8 415
14.4%
9 247
 
8.6%
0 232
 
8.1%
3 150
 
5.2%
4 91
 
3.2%
2 83
 
2.9%
7 56
 
1.9%
6 55
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2874
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1003
34.9%
5 518
18.0%
8 415
14.4%
9 247
 
8.6%
0 232
 
8.1%
3 150
 
5.2%
4 91
 
3.2%
2 83
 
2.9%
7 56
 
1.9%
6 55
 
1.9%

지번주소
Text

Distinct410
Distinct (%)86.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T03:29:23.164291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length30
Mean length23.425263
Min length19

Characters and Unicode

Total characters11127
Distinct characters44
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

Unique360 ?
Unique (%)75.8%

Sample

1st row서울특별시 관악구 신림동 1431-15번지
2nd row서울특별시 관악구 봉천동 883-4번지
3rd row서울특별시 관악구 봉천동 857-2번지
4th row서울특별시 관악구 신림동 1421-61번지
5th row서울특별시 관악구 봉천동 883-1번지
ValueCountFrequency (%)
서울특별시 475
24.3%
관악구 475
24.3%
신림동 304
15.6%
봉천동 134
 
6.9%
남현동 37
 
1.9%
지하1층 27
 
1.4%
1432-73번지 4
 
0.2%
1428-21번지 4
 
0.2%
지상2층 4
 
0.2%
1424-11번지 4
 
0.2%
Other values (416) 485
24.8%
2024-05-11T03:29:24.440975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1914
17.2%
1 639
 
5.7%
서 475
 
4.3%
악 475
 
4.3%
울 475
 
4.3%
구 475
 
4.3%
동 475
 
4.3%
관 475
 
4.3%
시 475
 
4.3%
별 475
 
4.3%
Other values (34) 4774
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6190
55.6%
Decimal Number 2541
22.8%
Space Separator 1914
 
17.2%
Dash Punctuation 473
 
4.3%
Other Punctuation 5
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 475
 
7.7%
악 475
 
7.7%
울 475
 
7.7%
구 475
 
7.7%
동 475
 
7.7%
관 475
 
7.7%
시 475
 
7.7%
별 475
 
7.7%
특 475
 
7.7%
지 457
 
7.4%
Other values (19) 1458
23.6%
Decimal Number
ValueCountFrequency (%)
1 639
25.1%
6 308
12.1%
2 281
11.1%
4 273
10.7%
3 264
10.4%
5 246
 
9.7%
8 168
 
6.6%
0 130
 
5.1%
7 117
 
4.6%
9 115
 
4.5%
Space Separator
ValueCountFrequency (%)
1914
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 473
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6190
55.6%
Common 4937
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 475
 
7.7%
악 475
 
7.7%
울 475
 
7.7%
구 475
 
7.7%
동 475
 
7.7%
관 475
 
7.7%
시 475
 
7.7%
별 475
 
7.7%
특 475
 
7.7%
지 457
 
7.4%
Other values (19) 1458
23.6%
Common
ValueCountFrequency (%)
1914
38.8%
1 639
 
12.9%
- 473
 
9.6%
6 308
 
6.2%
2 281
 
5.7%
4 273
 
5.5%
3 264
 
5.3%
5 246
 
5.0%
8 168
 
3.4%
0 130
 
2.6%
Other values (5) 241
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6190
55.6%
ASCII 4937
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1914
38.8%
1 639
 
12.9%
- 473
 
9.6%
6 308
 
6.2%
2 281
 
5.7%
4 273
 
5.5%
3 264
 
5.3%
5 246
 
5.0%
8 168
 
3.4%
0 130
 
2.6%
Other values (5) 241
 
4.9%
Hangul
ValueCountFrequency (%)
서 475
 
7.7%
악 475
 
7.7%
울 475
 
7.7%
구 475
 
7.7%
동 475
 
7.7%
관 475
 
7.7%
시 475
 
7.7%
별 475
 
7.7%
특 475
 
7.7%
지 457
 
7.4%
Other values (19) 1458
23.6%

도로명주소
Text

MISSING 

Distinct121
Distinct (%)98.4%
Missing352
Missing (%)74.1%
Memory size3.8 KiB
2024-05-11T03:29:25.167314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length27.308943
Min length21

Characters and Unicode

Total characters3359
Distinct characters64
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

Unique119 ?
Unique (%)96.7%

Sample

1st row서울특별시 관악구 남부순환로 1892 (봉천동)
2nd row서울특별시 관악구 관악로 268 (봉천동)
3rd row서울특별시 관악구 남부순환로 1872 (봉천동)
4th row서울특별시 관악구 시흥대로 548, 지하1층 (신림동)
5th row서울특별시 관악구 신사로 94, 지하1층 (신림동)
ValueCountFrequency (%)
서울특별시 123
18.2%
관악구 123
18.2%
신림동 72
 
10.7%
지하1층 39
 
5.8%
봉천동 34
 
5.0%
남부순환로 32
 
4.7%
신림로 11
 
1.6%
봉천로 10
 
1.5%
시흥대로 9
 
1.3%
난곡로 9
 
1.3%
Other values (154) 213
31.6%
2024-05-11T03:29:26.298554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
552
 
16.4%
1 134
 
4.0%
관 134
 
4.0%
시 132
 
3.9%
악 132
 
3.9%
동 125
 
3.7%
서 123
 
3.7%
울 123
 
3.7%
( 123
 
3.7%
) 123
 
3.7%
Other values (54) 1658
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2022
60.2%
Space Separator 552
 
16.4%
Decimal Number 467
 
13.9%
Open Punctuation 123
 
3.7%
Close Punctuation 123
 
3.7%
Other Punctuation 64
 
1.9%
Dash Punctuation 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 134
 
6.6%
시 132
 
6.5%
악 132
 
6.5%
동 125
 
6.2%
서 123
 
6.1%
울 123
 
6.1%
특 123
 
6.1%
구 123
 
6.1%
별 123
 
6.1%
로 113
 
5.6%
Other values (39) 771
38.1%
Decimal Number
ValueCountFrequency (%)
1 134
28.7%
2 51
 
10.9%
4 50
 
10.7%
5 46
 
9.9%
6 41
 
8.8%
3 39
 
8.4%
7 31
 
6.6%
8 27
 
5.8%
0 26
 
5.6%
9 22
 
4.7%
Space Separator
ValueCountFrequency (%)
552
100.0%
Open Punctuation
ValueCountFrequency (%)
( 123
100.0%
Close Punctuation
ValueCountFrequency (%)
) 123
100.0%
Other Punctuation
ValueCountFrequency (%)
, 64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2022
60.2%
Common 1337
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 134
 
6.6%
시 132
 
6.5%
악 132
 
6.5%
동 125
 
6.2%
서 123
 
6.1%
울 123
 
6.1%
특 123
 
6.1%
구 123
 
6.1%
별 123
 
6.1%
로 113
 
5.6%
Other values (39) 771
38.1%
Common
ValueCountFrequency (%)
552
41.3%
1 134
 
10.0%
( 123
 
9.2%
) 123
 
9.2%
, 64
 
4.8%
2 51
 
3.8%
4 50
 
3.7%
5 46
 
3.4%
6 41
 
3.1%
3 39
 
2.9%
Other values (5) 114
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2022
60.2%
ASCII 1337
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
552
41.3%
1 134
 
10.0%
( 123
 
9.2%
) 123
 
9.2%
, 64
 
4.8%
2 51
 
3.8%
4 50
 
3.7%
5 46
 
3.4%
6 41
 
3.1%
3 39
 
2.9%
Other values (5) 114
 
8.5%
Hangul
ValueCountFrequency (%)
관 134
 
6.6%
시 132
 
6.5%
악 132
 
6.5%
동 125
 
6.2%
서 123
 
6.1%
울 123
 
6.1%
특 123
 
6.1%
구 123
 
6.1%
별 123
 
6.1%
로 113
 
5.6%
Other values (39) 771
38.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)38.5%
Missing353
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean8767.1639
Minimum8700
Maximum8859
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T03:29:26.649584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8700
5-th percentile8707
Q18754
median8767.5
Q38785.75
95-th percentile8807
Maximum8859
Range159
Interquartile range (IQR)31.75

Descriptive statistics

Standard deviation29.075098
Coefficient of variation (CV)0.003316363
Kurtosis1.4069614
Mean8767.1639
Median Absolute Deviation (MAD)13.5
Skewness0.076236134
Sum1069594
Variance845.36133
MonotonicityNot monotonic
2024-05-11T03:29:27.036070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
8754 9
 
1.9%
8769 8
 
1.7%
8776 7
 
1.5%
8788 7
 
1.5%
8767 6
 
1.3%
8768 5
 
1.1%
8761 5
 
1.1%
8760 5
 
1.1%
8807 4
 
0.8%
8806 4
 
0.8%
Other values (37) 62
 
13.1%
(Missing) 353
74.3%
ValueCountFrequency (%)
8700 2
0.4%
8701 1
 
0.2%
8702 2
0.4%
8707 3
0.6%
8708 1
 
0.2%
8722 1
 
0.2%
8729 1
 
0.2%
8733 1
 
0.2%
8737 3
0.6%
8738 3
0.6%
ValueCountFrequency (%)
8859 1
 
0.2%
8849 1
 
0.2%
8846 1
 
0.2%
8839 1
 
0.2%
8807 4
0.8%
8806 4
0.8%
8805 1
 
0.2%
8801 1
 
0.2%
8793 2
0.4%
8789 4
0.8%

사업장명
Text

Distinct444
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T03:29:27.586647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length4.24
Min length1

Characters and Unicode

Total characters2014
Distinct characters390
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

Unique418 ?
Unique (%)88.0%

Sample

1st row뉴갈채
2nd row전원영상
3rd row이오단란주점
4th row째즈
5th row퀸단란주점
ValueCountFrequency (%)
월드컵 5
 
1.0%
노래바 4
 
0.8%
연 3
 
0.6%
7080 3
 
0.6%
준코뮤직타운 3
 
0.6%
코코 3
 
0.6%
준 3
 
0.6%
코리아 3
 
0.6%
단란주점 3
 
0.6%
퀸 3
 
0.6%
Other values (450) 476
93.5%
2024-05-11T03:29:28.810409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 65
 
3.2%
점 63
 
3.1%
란 56
 
2.8%
래 56
 
2.8%
단 55
 
2.7%
노 54
 
2.7%
스 50
 
2.5%
이 45
 
2.2%
리 42
 
2.1%
0 38
 
1.9%
Other values (380) 1490
74.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1822
90.5%
Decimal Number 90
 
4.5%
Uppercase Letter 42
 
2.1%
Space Separator 34
 
1.7%
Other Punctuation 9
 
0.4%
Close Punctuation 8
 
0.4%
Open Punctuation 8
 
0.4%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 65
 
3.6%
점 63
 
3.5%
란 56
 
3.1%
래 56
 
3.1%
단 55
 
3.0%
노 54
 
3.0%
스 50
 
2.7%
이 45
 
2.5%
리 42
 
2.3%
라 28
 
1.5%
Other values (343) 1308
71.8%
Uppercase Letter
ValueCountFrequency (%)
S 5
 
11.9%
L 4
 
9.5%
O 4
 
9.5%
I 3
 
7.1%
K 3
 
7.1%
T 2
 
4.8%
B 2
 
4.8%
A 2
 
4.8%
W 2
 
4.8%
E 2
 
4.8%
Other values (10) 13
31.0%
Decimal Number
ValueCountFrequency (%)
0 38
42.2%
7 16
17.8%
8 14
 
15.6%
2 8
 
8.9%
1 8
 
8.9%
9 3
 
3.3%
3 1
 
1.1%
4 1
 
1.1%
5 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 5
55.6%
, 2
 
22.2%
& 1
 
11.1%
% 1
 
11.1%
Space Separator
ValueCountFrequency (%)
34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
u 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1822
90.5%
Common 149
 
7.4%
Latin 43
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 65
 
3.6%
점 63
 
3.5%
란 56
 
3.1%
래 56
 
3.1%
단 55
 
3.0%
노 54
 
3.0%
스 50
 
2.7%
이 45
 
2.5%
리 42
 
2.3%
라 28
 
1.5%
Other values (343) 1308
71.8%
Latin
ValueCountFrequency (%)
S 5
 
11.6%
L 4
 
9.3%
O 4
 
9.3%
I 3
 
7.0%
K 3
 
7.0%
T 2
 
4.7%
B 2
 
4.7%
A 2
 
4.7%
W 2
 
4.7%
E 2
 
4.7%
Other values (11) 14
32.6%
Common
ValueCountFrequency (%)
0 38
25.5%
34
22.8%
7 16
10.7%
8 14
 
9.4%
2 8
 
5.4%
1 8
 
5.4%
) 8
 
5.4%
( 8
 
5.4%
. 5
 
3.4%
9 3
 
2.0%
Other values (6) 7
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1822
90.5%
ASCII 192
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 65
 
3.6%
점 63
 
3.5%
란 56
 
3.1%
래 56
 
3.1%
단 55
 
3.0%
노 54
 
3.0%
스 50
 
2.7%
이 45
 
2.5%
리 42
 
2.3%
라 28
 
1.5%
Other values (343) 1308
71.8%
ASCII
ValueCountFrequency (%)
0 38
19.8%
34
17.7%
7 16
 
8.3%
8 14
 
7.3%
2 8
 
4.2%
1 8
 
4.2%
) 8
 
4.2%
( 8
 
4.2%
S 5
 
2.6%
. 5
 
2.6%
Other values (27) 48
25.0%

최종수정일자
Date

Distinct259
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1999-02-08 00:00:00
Maximum2024-04-16 10:01:01
2024-05-11T03:29:29.219773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:29:29.591814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
I
402 
U
73 

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 402
84.6%
U 73
 
15.4%

Length

2024-05-11T03:29:29.947493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:30.234763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 402
84.6%
u 73
 
15.4%

데이터갱신일자
Date

Distinct70
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:08:00
2024-05-11T03:29:30.548933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:29:31.165771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
단란주점
475 

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 475
100.0%

Length

2024-05-11T03:29:31.661804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:31.997643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단란주점 475
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct382
Distinct (%)81.3%
Missing5
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean194161.4
Minimum191131.05
Maximum198278.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T03:29:32.477970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191131.05
5-th percentile191313.2
Q1192789.03
median193715.72
Q3195637.44
95-th percentile198225.77
Maximum198278.93
Range7147.8811
Interquartile range (IQR)2848.4102

Descriptive statistics

Standard deviation1848.867
Coefficient of variation (CV)0.0095223201
Kurtosis-0.23594229
Mean194161.4
Median Absolute Deviation (MAD)1324.5527
Skewness0.55094215
Sum91255858
Variance3418309.2
MonotonicityNot monotonic
2024-05-11T03:29:33.211078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193652.870855264 4
 
0.8%
193667.814824278 4
 
0.8%
192342.519273529 4
 
0.8%
193715.720946633 4
 
0.8%
193620.638417218 3
 
0.6%
196571.376338921 3
 
0.6%
192363.831421228 3
 
0.6%
193356.709032718 3
 
0.6%
195759.872774126 3
 
0.6%
191217.026445816 3
 
0.6%
Other values (372) 436
91.8%
(Missing) 5
 
1.1%
ValueCountFrequency (%)
191131.049995846 1
 
0.2%
191182.000480527 2
0.4%
191204.884621244 1
 
0.2%
191210.00657717 1
 
0.2%
191210.078732513 1
 
0.2%
191215.879312952 1
 
0.2%
191217.026445816 3
0.6%
191223.827173065 2
0.4%
191244.186952943 1
 
0.2%
191256.899646094 1
 
0.2%
ValueCountFrequency (%)
198278.931088754 1
0.2%
198278.438025281 2
0.4%
198275.013917658 1
0.2%
198268.135159088 1
0.2%
198266.765199796 1
0.2%
198265.804887714 2
0.4%
198264.099355157 1
0.2%
198262.406512171 2
0.4%
198260.790961903 2
0.4%
198260.085928707 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct382
Distinct (%)81.3%
Missing5
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean442191.23
Minimum440299.38
Maximum443280.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T03:29:33.864781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440299.38
5-th percentile441424.77
Q1441984.74
median442252.83
Q3442498.95
95-th percentile442794.45
Maximum443280.4
Range2981.019
Interquartile range (IQR)514.21171

Descriptive statistics

Standard deviation457.68086
Coefficient of variation (CV)0.0010350292
Kurtosis0.92217293
Mean442191.23
Median Absolute Deviation (MAD)260.93621
Skewness-0.82426055
Sum2.0782988 × 108
Variance209471.77
MonotonicityNot monotonic
2024-05-11T03:29:34.412037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442837.278342107 4
 
0.8%
442621.679865443 4
 
0.8%
442214.191245685 4
 
0.8%
442661.600592493 4
 
0.8%
442783.198406659 3
 
0.6%
441754.121622412 3
 
0.6%
442363.569839222 3
 
0.6%
442367.140508663 3
 
0.6%
441941.015435004 3
 
0.6%
442233.874417452 3
 
0.6%
Other values (372) 436
91.8%
(Missing) 5
 
1.1%
ValueCountFrequency (%)
440299.376149385 1
 
0.2%
440378.188412704 1
 
0.2%
440938.389825273 1
 
0.2%
440958.073685948 1
 
0.2%
440971.786602804 2
0.4%
440972.42985213 1
 
0.2%
440976.482644471 3
0.6%
440983.612003888 1
 
0.2%
441002.10027233 2
0.4%
441121.616432787 1
 
0.2%
ValueCountFrequency (%)
443280.395116602 1
0.2%
443157.363464064 1
0.2%
443109.84937523 1
0.2%
443074.210493312 1
0.2%
443057.195231809 1
0.2%
442996.344931519 1
0.2%
442986.213945228 1
0.2%
442932.143196354 1
0.2%
442899.970020959 1
0.2%
442867.665973694 1
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
단란주점
436 
<NA>
 
39

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 436
91.8%
<NA> 39
 
8.2%

Length

2024-05-11T03:29:34.893990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:35.225518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단란주점 436
91.8%
na 39
 
8.2%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
333 
<NA>
116 
1
 
23
2
 
2
3
 
1

Length

Max length4
Median length1
Mean length1.7326316
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 333
70.1%
<NA> 116
 
24.4%
1 23
 
4.8%
2 2
 
0.4%
3 1
 
0.2%

Length

2024-05-11T03:29:35.591998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:35.957056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 333
70.1%
na 116
 
24.4%
1 23
 
4.8%
2 2
 
0.4%
3 1
 
0.2%

여성종사자수
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
326 
<NA>
118 
1
 
28
2
 
3

Length

Max length4
Median length1
Mean length1.7452632
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row2
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 326
68.6%
<NA> 118
 
24.8%
1 28
 
5.9%
2 3
 
0.6%

Length

2024-05-11T03:29:36.442828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:36.906494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 326
68.6%
na 118
 
24.8%
1 28
 
5.9%
2 3
 
0.6%

영업장주변구분명
Categorical

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
유흥업소밀집지역
160 
주택가주변
149 
기타
76 
<NA>
73 
학교정화(상대)
 
16

Length

Max length8
Median length7
Mean length5.4821053
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row유흥업소밀집지역
2nd row기타
3rd row유흥업소밀집지역
4th row유흥업소밀집지역
5th row기타

Common Values

ValueCountFrequency (%)
유흥업소밀집지역 160
33.7%
주택가주변 149
31.4%
기타 76
16.0%
<NA> 73
15.4%
학교정화(상대) 16
 
3.4%
결혼예식장주변 1
 
0.2%

Length

2024-05-11T03:29:37.453960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:37.978666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유흥업소밀집지역 160
33.7%
주택가주변 149
31.4%
기타 76
16.0%
na 73
15.4%
학교정화(상대 16
 
3.4%
결혼예식장주변 1
 
0.2%

등급구분명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
기타
366 
<NA>
109 

Length

Max length4
Median length2
Mean length2.4589474
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 366
77.1%
<NA> 109
 
22.9%

Length

2024-05-11T03:29:38.528727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:39.055924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 366
77.1%
na 109
 
22.9%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
상수도전용
394 
<NA>
78 
상수도(음용)지하수(주방용)겸용
 
2
간이상수도
 
1

Length

Max length17
Median length5
Mean length4.8863158
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 394
82.9%
<NA> 78
 
16.4%
상수도(음용)지하수(주방용)겸용 2
 
0.4%
간이상수도 1
 
0.2%

Length

2024-05-11T03:29:39.498035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:39.957475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 394
82.9%
na 78
 
16.4%
상수도(음용)지하수(주방용)겸용 2
 
0.4%
간이상수도 1
 
0.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
468 
0
 
7

Length

Max length4
Median length4
Mean length3.9557895
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> 468
98.5%
0 7
 
1.5%

Length

2024-05-11T03:29:40.426830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:40.909829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 468
98.5%
0 7
 
1.5%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
468 
0
 
7

Length

Max length4
Median length4
Mean length3.9557895
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> 468
98.5%
0 7
 
1.5%

Length

2024-05-11T03:29:41.307779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:41.679991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 468
98.5%
0 7
 
1.5%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
468 
0
 
7

Length

Max length4
Median length4
Mean length3.9557895
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> 468
98.5%
0 7
 
1.5%

Length

2024-05-11T03:29:41.983948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:42.310531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 468
98.5%
0 7
 
1.5%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
468 
0
 
7

Length

Max length4
Median length4
Mean length3.9557895
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> 468
98.5%
0 7
 
1.5%

Length

2024-05-11T03:29:42.722564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:43.129776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 468
98.5%
0 7
 
1.5%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
468 
0
 
7

Length

Max length4
Median length4
Mean length3.9557895
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> 468
98.5%
0 7
 
1.5%

Length

2024-05-11T03:29:43.509780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:43.975331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 468
98.5%
0 7
 
1.5%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing475
Missing (%)100.0%
Memory size4.3 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
468 
0
 
7

Length

Max length4
Median length4
Mean length3.9557895
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> 468
98.5%
0 7
 
1.5%

Length

2024-05-11T03:29:44.361508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:44.767512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 468
98.5%
0 7
 
1.5%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
468 
0
 
7

Length

Max length4
Median length4
Mean length3.9557895
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> 468
98.5%
0 7
 
1.5%

Length

2024-05-11T03:29:45.106858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:29:45.428655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 468
98.5%
0 7
 
1.5%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.5%
Missing39
Missing (%)8.2%
Memory size1.1 KiB
False
407 
True
 
29
(Missing)
 
39
ValueCountFrequency (%)
False 407
85.7%
True 29
 
6.1%
(Missing) 39
 
8.2%
2024-05-11T03:29:45.702986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct418
Distinct (%)95.9%
Missing39
Missing (%)8.2%
Infinite0
Infinite (%)0.0%
Mean98.105321
Minimum25.73
Maximum354.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T03:29:46.048841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.73
5-th percentile53.615
Q172.58
median93.83
Q3121.9325
95-th percentile147.775
Maximum354.74
Range329.01
Interquartile range (IQR)49.3525

Descriptive statistics

Standard deviation34.395939
Coefficient of variation (CV)0.35060218
Kurtosis6.725169
Mean98.105321
Median Absolute Deviation (MAD)23.515
Skewness1.3582259
Sum42773.92
Variance1183.0806
MonotonicityNot monotonic
2024-05-11T03:29:46.493651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
78.2 2
 
0.4%
133.75 2
 
0.4%
60.9 2
 
0.4%
67.5 2
 
0.4%
101.08 2
 
0.4%
148.8 2
 
0.4%
148.62 2
 
0.4%
75.59 2
 
0.4%
79.45 2
 
0.4%
107.72 2
 
0.4%
Other values (408) 416
87.6%
(Missing) 39
 
8.2%
ValueCountFrequency (%)
25.73 1
0.2%
30.98 1
0.2%
31.0 1
0.2%
35.0 1
0.2%
41.0 1
0.2%
42.8 1
0.2%
43.1 1
0.2%
43.22 1
0.2%
45.15 1
0.2%
46.35 1
0.2%
ValueCountFrequency (%)
354.74 1
0.2%
241.87 1
0.2%
208.75 1
0.2%
192.92 1
0.2%
187.14 1
0.2%
185.84 1
0.2%
171.63 1
0.2%
170.57 1
0.2%
158.28 1
0.2%
149.61 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing475
Missing (%)100.0%
Memory size4.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing475
Missing (%)100.0%
Memory size4.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing475
Missing (%)100.0%
Memory size4.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032000003200000-103-1993-0785619930818<NA>3폐업2폐업19981117<NA><NA><NA>0208785045118.0151892서울특별시 관악구 신림동 1431-15번지<NA><NA>뉴갈채2001-09-29 00:00:00I2018-08-31 23:59:59.0단란주점193651.40079442694.194138단란주점00유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N118.0<NA><NA><NA>
132000003200000-103-1993-0785719930825<NA>3폐업2폐업19960201<NA><NA><NA>02 00000106.75151836서울특별시 관악구 봉천동 883-4번지<NA><NA>전원영상2001-09-29 00:00:00I2018-08-31 23:59:59.0단란주점195405.435005442132.094286단란주점00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N106.75<NA><NA><NA>
232000003200000-103-1993-0785819930825<NA>3폐업2폐업20000215<NA><NA><NA>0282.36151848서울특별시 관악구 봉천동 857-2번지<NA><NA>이오단란주점2001-09-29 00:00:00I2018-08-31 23:59:59.0단란주점195789.121943442057.860854단란주점02유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N82.36<NA><NA><NA>
332000003200000-103-1993-0785919930826<NA>3폐업2폐업19961014<NA><NA><NA>0208830388121.16151890서울특별시 관악구 신림동 1421-61번지<NA><NA>째즈2001-09-29 00:00:00I2018-08-31 23:59:59.0단란주점193762.098063442570.919052단란주점00유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N121.16<NA><NA><NA>
432000003200000-103-1993-0786119930827<NA>3폐업2폐업20000609<NA><NA><NA>02 8364885115.71151836서울특별시 관악구 봉천동 883-1번지<NA><NA>퀸단란주점2000-06-09 00:00:00I2018-08-31 23:59:59.0단란주점195418.480626442130.611876단란주점00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N115.71<NA><NA><NA>
532000003200000-103-1993-0786219930828<NA>3폐업2폐업20000222<NA><NA><NA>02109.96151836서울특별시 관악구 봉천동 863-14번지<NA><NA>리빠똥2001-09-29 00:00:00I2018-08-31 23:59:59.0단란주점195687.976856441910.74633단란주점00유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N109.96<NA><NA><NA>
632000003200000-103-1993-0786319930903<NA>3폐업2폐업20021023<NA><NA><NA>02 882366560.42151843서울특별시 관악구 봉천동 950-23번지<NA><NA>다 연2001-09-29 00:00:00I2018-08-31 23:59:59.0단란주점194466.041116442554.327382단란주점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N60.42<NA><NA><NA>
732000003200000-103-1993-0786419930909<NA>3폐업2폐업19981128<NA><NA><NA>0208899536138.62151930서울특별시 관악구 신림동 1639-6번지<NA><NA>나누리2001-09-29 00:00:00I2018-08-31 23:59:59.0단란주점193502.854194442375.446568단란주점00유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N138.62<NA><NA><NA>
832000003200000-103-1993-0786519930910<NA>3폐업2폐업19960620<NA><NA><NA>02 0000070.29151888서울특별시 관악구 신림동 607-124번지<NA><NA>썬2002-01-08 00:00:00I2018-08-31 23:59:59.0단란주점192589.960183441436.332673단란주점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N70.29<NA><NA><NA>
932000003200000-103-1993-0786619930911<NA>3폐업2폐업20020530<NA><NA><NA>02 8723121130.48151843서울특별시 관악구 봉천동 931-8번지<NA><NA>자유성2001-09-29 00:00:00I2018-08-31 23:59:59.0단란주점194702.898407442319.059742단란주점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N130.48<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
46532000003200000-103-2019-0000220190816<NA>3폐업2폐업20191007<NA><NA><NA><NA>117.32151890서울특별시 관악구 신림동 1424-11번지서울특별시 관악구 신림로 356, 지하1층 (신림동)8754꿀벌2019-10-07 10:03:03U2019-10-09 02:40:00.0단란주점193715.720947442661.600592단란주점<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y117.32<NA><NA><NA>
46632000003200000-103-2021-0000120211027<NA>1영업/정상1영업<NA><NA><NA><NA><NA>103.49151892서울특별시 관악구 신림동 1433-66서울특별시 관악구 남부순환로 1597-10, 지하1층 (신림동)8759베를린2021-10-27 09:05:17I2021-10-28 00:22:56.0단란주점193555.192678442490.551773단란주점00유흥업소밀집지역<NA>상수도전용00000<NA>00Y103.49<NA><NA><NA>
46732000003200000-103-2022-000012022-01-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>166.64151-930서울특별시 관악구 신림동 1640-28서울특별시 관악구 남부순환로 1600-8, 5층 (신림동)8776플로우서울(FLOW)2023-01-31 13:46:20U2022-12-02 00:02:00.0단란주점193632.390178442385.351113<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46832000003200000-103-2022-0000220220228<NA>1영업/정상1영업<NA><NA><NA><NA><NA>74.46151930서울특별시 관악구 신림동 1640-30서울특별시 관악구 남부순환로176길 11, 3층 (신림동)8776클래스2022-03-10 15:35:33U2022-03-13 02:40:00.0단란주점193612.249353442364.884315단란주점00유흥업소밀집지역<NA>상수도전용00000<NA>00Y74.46<NA><NA><NA>
46932000003200000-103-2022-0000320220324<NA>1영업/정상1영업<NA><NA><NA><NA><NA>83.64151930서울특별시 관악구 신림동 1639-20서울특별시 관악구 남부순환로 1594-4, 지하1층 (신림동)8776볼트 마이크(VOLT MIC)2022-03-25 15:05:03I2022-03-26 00:22:34.0단란주점193555.772031442391.715617단란주점00기타<NA>상수도(음용)지하수(주방용)겸용00000<NA>00Y83.64<NA><NA><NA>
47032000003200000-103-2022-000042022-07-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>149.72151-834서울특별시 관악구 봉천동 858-7서울특별시 관악구 남부순환로 1827, 지하1층 (봉천동)8738조이2023-05-30 14:28:04U2022-12-06 00:01:00.0단란주점195808.05709442130.00084<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47132000003200000-103-2022-0000520221019<NA>1영업/정상1영업<NA><NA><NA><NA><NA>146.95151876서울특별시 관악구 신림동 538-11서울특별시 관악구 남부순환로 1461, 지하1층 (신림동)8767청춘스케치7090라이브2022-10-19 16:01:54I2021-10-30 22:02:00.0단란주점192225.364497442185.794626<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47232000003200000-103-2023-000012023-03-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>141.35151-876서울특별시 관악구 신림동 530-31 상진서울특별시 관악구 난곡로 323, 상진 2층 (신림동)8767판도라2023-02-28 13:25:59I2022-12-03 00:03:00.0단란주점192332.463248442308.045654<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47332000003200000-103-2023-000022023-09-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>99.87151-875서울특별시 관악구 신림동 527-3서울특별시 관악구 남부순환로 1479, 지1층 (신림동)8761모이자2023-09-25 17:15:54I2022-12-08 22:07:00.0단란주점192405.258847442228.060872<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47432000003200000-103-2024-000012024-03-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>147.94151-930서울특별시 관악구 신림동 1638-24서울특별시 관악구 신림로59길 7, 지하1층 (신림동)8776파이프2024-04-16 10:01:01U2023-12-03 23:08:00.0단란주점193676.763447442304.46217<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>