Overview

Dataset statistics

Number of variables6
Number of observations80
Missing cells8
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory49.6 B

Variable types

Categorical2
Text4

Dataset

Description파일 다운로드
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-22058/F/1/datasetView.do

Alerts

데이터기준일자 has constant value ""Constant
업종명 is highly imbalanced (61.6%)Imbalance
소재지전화번호 has 8 (10.0%) missing valuesMissing
소재지(도로명) has unique valuesUnique
소재지(지번)_일부 has unique valuesUnique

Reproduction

Analysis started2023-12-11 04:18:19.576737
Analysis finished2023-12-11 04:18:20.270874
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
단란주점
74 
유흥주점영업
 
6

Length

Max length6
Median length4
Mean length4.15
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단란주점 74
92.5%
유흥주점영업 6
 
7.5%

Length

2023-12-11T13:18:20.404798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:18:20.573772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단란주점 74
92.5%
유흥주점영업 6
 
7.5%

업소명
Text

Distinct76
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-11T13:18:20.910243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length4.125
Min length1

Characters and Unicode

Total characters330
Distinct characters145
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)90.0%

Sample

1st row팡팡노래바
2nd row터널
3rd row타임노래뱅크
4th row은하수
5th row캉캉노래바
ValueCountFrequency (%)
팡팡노래바 2
 
2.5%
황실 2
 
2.5%
터널 2
 
2.5%
7080 2
 
2.5%
오디션단란주점 1
 
1.2%
파노라마 1
 
1.2%
오페라노래바 1
 
1.2%
30-70생음악 1
 
1.2%
황금노래광장 1
 
1.2%
휠링 1
 
1.2%
Other values (66) 66
82.5%
2023-12-11T13:18:21.501425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
노 20
 
6.1%
래 19
 
5.8%
0 10
 
3.0%
장 8
 
2.4%
바 8
 
2.4%
광 8
 
2.4%
주 8
 
2.4%
점 7
 
2.1%
황 7
 
2.1%
리 6
 
1.8%
Other values (135) 229
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 298
90.3%
Decimal Number 22
 
6.7%
Uppercase Letter 5
 
1.5%
Open Punctuation 2
 
0.6%
Close Punctuation 2
 
0.6%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
노 20
 
6.7%
래 19
 
6.4%
장 8
 
2.7%
바 8
 
2.7%
광 8
 
2.7%
주 8
 
2.7%
점 7
 
2.3%
황 7
 
2.3%
리 6
 
2.0%
이 5
 
1.7%
Other values (123) 202
67.8%
Uppercase Letter
ValueCountFrequency (%)
B 1
20.0%
O 1
20.0%
S 1
20.0%
E 1
20.0%
Y 1
20.0%
Decimal Number
ValueCountFrequency (%)
0 10
45.5%
7 6
27.3%
8 5
22.7%
3 1
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 298
90.3%
Common 27
 
8.2%
Latin 5
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
노 20
 
6.7%
래 19
 
6.4%
장 8
 
2.7%
바 8
 
2.7%
광 8
 
2.7%
주 8
 
2.7%
점 7
 
2.3%
황 7
 
2.3%
리 6
 
2.0%
이 5
 
1.7%
Other values (123) 202
67.8%
Common
ValueCountFrequency (%)
0 10
37.0%
7 6
22.2%
8 5
18.5%
( 2
 
7.4%
) 2
 
7.4%
- 1
 
3.7%
3 1
 
3.7%
Latin
ValueCountFrequency (%)
B 1
20.0%
O 1
20.0%
S 1
20.0%
E 1
20.0%
Y 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 298
90.3%
ASCII 32
 
9.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
노 20
 
6.7%
래 19
 
6.4%
장 8
 
2.7%
바 8
 
2.7%
광 8
 
2.7%
주 8
 
2.7%
점 7
 
2.3%
황 7
 
2.3%
리 6
 
2.0%
이 5
 
1.7%
Other values (123) 202
67.8%
ASCII
ValueCountFrequency (%)
0 10
31.2%
7 6
18.8%
8 5
15.6%
( 2
 
6.2%
) 2
 
6.2%
- 1
 
3.1%
3 1
 
3.1%
B 1
 
3.1%
O 1
 
3.1%
S 1
 
3.1%
Other values (2) 2
 
6.2%

소재지(도로명)
Text

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-11T13:18:21.981779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length38
Mean length28.5
Min length21

Characters and Unicode

Total characters2280
Distinct characters65
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

Unique80 ?
Unique (%)100.0%

Sample

1st row서울특별시 양천구 공항대로 564 (목동,지하1층(공항로 113))
2nd row서울특별시 양천구 신월로 292 (신정동)
3rd row서울특별시 양천구 등촌로 182 (목동)
4th row서울특별시 양천구 등촌로 20 (목동)
5th row서울특별시 양천구 목동서로 213 (목동, 세신프라자 306,307,308,309호)
ValueCountFrequency (%)
서울특별시 80
17.7%
양천구 80
17.7%
신정동 30
 
6.7%
지하1층 24
 
5.3%
목동 19
 
4.2%
중앙로 15
 
3.3%
신월동 14
 
3.1%
신월로 12
 
2.7%
등촌로 8
 
1.8%
신목로 8
 
1.8%
Other values (130) 161
35.7%
2023-12-11T13:18:22.581384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
371
 
16.3%
로 96
 
4.2%
) 92
 
4.0%
( 92
 
4.0%
동 91
 
4.0%
서 88
 
3.9%
신 87
 
3.8%
1 84
 
3.7%
양 83
 
3.6%
천 82
 
3.6%
Other values (55) 1114
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1322
58.0%
Space Separator 371
 
16.3%
Decimal Number 335
 
14.7%
Close Punctuation 92
 
4.0%
Open Punctuation 92
 
4.0%
Other Punctuation 56
 
2.5%
Dash Punctuation 11
 
0.5%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 96
 
7.3%
동 91
 
6.9%
서 88
 
6.7%
신 87
 
6.6%
양 83
 
6.3%
천 82
 
6.2%
구 80
 
6.1%
울 80
 
6.1%
시 80
 
6.1%
특 80
 
6.1%
Other values (39) 475
35.9%
Decimal Number
ValueCountFrequency (%)
1 84
25.1%
2 55
16.4%
3 42
12.5%
0 28
 
8.4%
5 25
 
7.5%
6 24
 
7.2%
8 21
 
6.3%
4 20
 
6.0%
7 19
 
5.7%
9 17
 
5.1%
Space Separator
ValueCountFrequency (%)
371
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 92
100.0%
Other Punctuation
ValueCountFrequency (%)
, 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1322
58.0%
Common 957
42.0%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 96
 
7.3%
동 91
 
6.9%
서 88
 
6.7%
신 87
 
6.6%
양 83
 
6.3%
천 82
 
6.2%
구 80
 
6.1%
울 80
 
6.1%
시 80
 
6.1%
특 80
 
6.1%
Other values (39) 475
35.9%
Common
ValueCountFrequency (%)
371
38.8%
) 92
 
9.6%
( 92
 
9.6%
1 84
 
8.8%
, 56
 
5.9%
2 55
 
5.7%
3 42
 
4.4%
0 28
 
2.9%
5 25
 
2.6%
6 24
 
2.5%
Other values (5) 88
 
9.2%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1322
58.0%
ASCII 958
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
371
38.7%
) 92
 
9.6%
( 92
 
9.6%
1 84
 
8.8%
, 56
 
5.8%
2 55
 
5.7%
3 42
 
4.4%
0 28
 
2.9%
5 25
 
2.6%
6 24
 
2.5%
Other values (6) 89
 
9.3%
Hangul
ValueCountFrequency (%)
로 96
 
7.3%
동 91
 
6.9%
서 88
 
6.7%
신 87
 
6.6%
양 83
 
6.3%
천 82
 
6.2%
구 80
 
6.1%
울 80
 
6.1%
시 80
 
6.1%
특 80
 
6.1%
Other values (39) 475
35.9%

소재지(지번)_일부
Text

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-11T13:18:22.936462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length18.375
Min length13

Characters and Unicode

Total characters1470
Distinct characters49
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

Unique80 ?
Unique (%)100.0%

Sample

1st row목동 602번지 1호 지하1층(공항로 113)
2nd row신정동 1030번지 1호
3rd row목동 651번지 9호
4th row목동 793번지 6호
5th row목동 923번지 세신프라자 306,307,308,309호
ValueCountFrequency (%)
신정동 44
 
14.3%
지하1층 26
 
8.4%
목동 20
 
6.5%
신월동 16
 
5.2%
1호 10
 
3.2%
6호 8
 
2.6%
5호 7
 
2.3%
3호 7
 
2.3%
2호 6
 
1.9%
1183번지 5
 
1.6%
Other values (107) 159
51.6%
2023-12-11T13:18:23.439200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
338
23.0%
1 135
 
9.2%
지 119
 
8.1%
호 83
 
5.6%
동 82
 
5.6%
번 80
 
5.4%
신 65
 
4.4%
3 53
 
3.6%
2 47
 
3.2%
0 45
 
3.1%
Other values (39) 423
28.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 635
43.2%
Decimal Number 464
31.6%
Space Separator 338
23.0%
Open Punctuation 13
 
0.9%
Close Punctuation 13
 
0.9%
Other Punctuation 5
 
0.3%
Uppercase Letter 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 119
18.7%
호 83
13.1%
동 82
12.9%
번 80
12.6%
신 65
10.2%
정 44
 
6.9%
층 41
 
6.5%
하 35
 
5.5%
목 21
 
3.3%
월 20
 
3.1%
Other values (23) 45
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 135
29.1%
3 53
 
11.4%
2 47
 
10.1%
0 45
 
9.7%
9 45
 
9.7%
6 32
 
6.9%
5 29
 
6.2%
7 27
 
5.8%
4 26
 
5.6%
8 25
 
5.4%
Space Separator
ValueCountFrequency (%)
338
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 834
56.7%
Hangul 635
43.2%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 119
18.7%
호 83
13.1%
동 82
12.9%
번 80
12.6%
신 65
10.2%
정 44
 
6.9%
층 41
 
6.5%
하 35
 
5.5%
목 21
 
3.3%
월 20
 
3.1%
Other values (23) 45
 
7.1%
Common
ValueCountFrequency (%)
338
40.5%
1 135
 
16.2%
3 53
 
6.4%
2 47
 
5.6%
0 45
 
5.4%
9 45
 
5.4%
6 32
 
3.8%
5 29
 
3.5%
7 27
 
3.2%
4 26
 
3.1%
Other values (5) 57
 
6.8%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 835
56.8%
Hangul 635
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
338
40.5%
1 135
 
16.2%
3 53
 
6.3%
2 47
 
5.6%
0 45
 
5.4%
9 45
 
5.4%
6 32
 
3.8%
5 29
 
3.5%
7 27
 
3.2%
4 26
 
3.1%
Other values (6) 58
 
6.9%
Hangul
ValueCountFrequency (%)
지 119
18.7%
호 83
13.1%
동 82
12.9%
번 80
12.6%
신 65
10.2%
정 44
 
6.9%
층 41
 
6.5%
하 35
 
5.5%
목 21
 
3.3%
월 20
 
3.1%
Other values (23) 45
 
7.1%

소재지전화번호
Text

MISSING 

Distinct72
Distinct (%)100.0%
Missing8
Missing (%)10.0%
Memory size772.0 B
2023-12-11T13:18:23.775887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.763889
Min length11

Characters and Unicode

Total characters847
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

Unique72 ?
Unique (%)100.0%

Sample

1st row02-2652-8983
2nd row02-2651-4028
3rd row02-2651-4208
4th row02-642-1466
5th row02-2653-2991
ValueCountFrequency (%)
02-2651-4028 1
 
1.4%
02-2651-4208 1
 
1.4%
02-2645-1186 1
 
1.4%
02-2649-9677 1
 
1.4%
02-2607-8527 1
 
1.4%
02-648-3020 1
 
1.4%
02-2696-5330 1
 
1.4%
02-2653-1750 1
 
1.4%
02-2696-5055 1
 
1.4%
02-606-2606 1
 
1.4%
Other values (62) 62
86.1%
2023-12-11T13:18:24.230100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 168
19.8%
- 144
17.0%
0 118
13.9%
6 113
13.3%
9 59
 
7.0%
4 58
 
6.8%
5 56
 
6.6%
3 36
 
4.3%
1 32
 
3.8%
8 32
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 703
83.0%
Dash Punctuation 144
 
17.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 168
23.9%
0 118
16.8%
6 113
16.1%
9 59
 
8.4%
4 58
 
8.3%
5 56
 
8.0%
3 36
 
5.1%
1 32
 
4.6%
8 32
 
4.6%
7 31
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 847
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 168
19.8%
- 144
17.0%
0 118
13.9%
6 113
13.3%
9 59
 
7.0%
4 58
 
6.8%
5 56
 
6.6%
3 36
 
4.3%
1 32
 
3.8%
8 32
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 847
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 168
19.8%
- 144
17.0%
0 118
13.9%
6 113
13.3%
9 59
 
7.0%
4 58
 
6.8%
5 56
 
6.6%
3 36
 
4.3%
1 32
 
3.8%
8 32
 
3.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
2022-08-01
80 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-01
2nd row2022-08-01
3rd row2022-08-01
4th row2022-08-01
5th row2022-08-01

Common Values

ValueCountFrequency (%)
2022-08-01 80
100.0%

Length

2023-12-11T13:18:24.401042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:18:24.525853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-01 80
100.0%

Correlations

2023-12-11T13:18:24.604304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업소명소재지(도로명)소재지(지번)_일부소재지전화번호
업종명1.0000.0001.0001.0001.000
업소명0.0001.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.0001.000
소재지(지번)_일부1.0001.0001.0001.0001.000
소재지전화번호1.0001.0001.0001.0001.000

Missing values

2023-12-11T13:18:20.068476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:18:20.214834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

업종명업소명소재지(도로명)소재지(지번)_일부소재지전화번호데이터기준일자
0유흥주점영업팡팡노래바서울특별시 양천구 공항대로 564 (목동,지하1층(공항로 113))목동 602번지 1호 지하1층(공항로 113)02-2652-89832022-08-01
1유흥주점영업터널서울특별시 양천구 신월로 292 (신정동)신정동 1030번지 1호02-2651-40282022-08-01
2유흥주점영업타임노래뱅크서울특별시 양천구 등촌로 182 (목동)목동 651번지 9호02-2651-42082022-08-01
3유흥주점영업은하수서울특별시 양천구 등촌로 20 (목동)목동 793번지 6호02-642-14662022-08-01
4유흥주점영업캉캉노래바서울특별시 양천구 목동서로 213 (목동, 세신프라자 306,307,308,309호)목동 923번지 세신프라자 306,307,308,309호02-2653-29912022-08-01
5유흥주점영업유나노래바서울특별시 양천구 신월로 310 (신정동)신정동 1029번지 14호02-2654-35992022-08-01
6단란주점예스(YES)서울특별시 양천구 중앙로 263 (신정동, 지하)신정동 1183번지 7호 지하02-2695-89152022-08-01
7단란주점가야서울특별시 양천구 신목로 94, 지하1층 (목동)목동 404번지 115호 지하1층02-2646-22912022-08-01
8단란주점세인서울특별시 양천구 신월로 294 (신정동,지하1층(신월로 105))신정동 1030번지 2호 지하1층(신월로 105)02-2645-88202022-08-01
9단란주점꼬빵서울특별시 양천구 신목로 78-1 (신정동, 지하1층)신정동 117번지 36호 지하1층02-2647-73362022-08-01
업종명업소명소재지(도로명)소재지(지번)_일부소재지전화번호데이터기준일자
70단란주점타임노래광장서울특별시 양천구 신월로 282 (신정동,(신월로 117))신정동 1190번지 2호 (신월로 117)02-2690-31402022-08-01
71단란주점에이스노래광장서울특별시 양천구 중앙로 282 (신정동,(강서로 633) 지하1층)신정동 972번지 4호 (강서로 633) 지하1층<NA>2022-08-01
72단란주점퓨전서울특별시 양천구 중앙로 288 (신정동, 지상2층)신정동 972번지 1호 지상2층02-2692-77122022-08-01
73단란주점아주노래광장서울특별시 양천구 중앙로34길 30 (신정동, 2층)신정동 1030번지 6호 2층02-2649-99982022-08-01
74단란주점강남노래바서울특별시 양천구 중앙로 264 (신정동,지하1층)신정동 1031번지 8호 지하1층02-2646-88432022-08-01
75단란주점7박8일생음악메들리서울특별시 양천구 중앙로 284 (신정동,지하1층(강서로 631))신정동 972번지 3호 지하1층(강서로 631)<NA>2022-08-01
76단란주점오페라노래바서울특별시 양천구 중앙로 257 (신정동,지하1층)신정동 1183번지 11호 지하1층02-2695-82592022-08-01
77단란주점로마서울특별시 양천구 중앙로 269 (신정동,지하1층(중앙로 269))신정동 1190번지 6호 지하1층(중앙로 269)<NA>2022-08-01
78단란주점터널서울특별시 양천구 중앙로 261, 2층 (신정동)신정동 1183번지 8호 2층02-2698-54542022-08-01
79단란주점보고싶다서울특별시 양천구 중앙로 247, 지하1층 (신정동)신정동 1182번지 7호 지하1층<NA>2022-08-01