Overview

Dataset statistics

Number of variables4
Number of observations288
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 KiB
Average record size in memory33.5 B

Variable types

Categorical3
Numeric1

Dataset

Description자치구명,법정동명,업종명,업소수
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-11223/S/1/datasetView.do

Alerts

자치구명 has constant value ""Constant

Reproduction

Analysis started2024-05-18 08:38:03.113610
Analysis finished2024-05-18 08:38:04.208128
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
용산구
288 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용산구 288
100.0%

Length

2024-05-18T17:38:04.490956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T17:38:04.993405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용산구 288
100.0%

법정동명
Categorical

Distinct33
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
한남동
 
19
이촌동
 
18
한강로3가
 
18
한강로2가
 
17
이태원동
 
15
Other values (28)
201 

Length

Max length5
Median length3
Mean length3.90625
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
한남동 19
 
6.6%
이촌동 18
 
6.2%
한강로3가 18
 
6.2%
한강로2가 17
 
5.9%
이태원동 15
 
5.2%
보광동 14
 
4.9%
후암동 13
 
4.5%
용문동 12
 
4.2%
원효로1가 10
 
3.5%
동자동 10
 
3.5%
Other values (23) 142
49.3%

Length

2024-05-18T17:38:05.344666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한남동 19
 
6.6%
한강로3가 18
 
6.2%
이촌동 18
 
6.2%
한강로2가 17
 
5.9%
이태원동 15
 
5.2%
보광동 14
 
4.9%
후암동 13
 
4.5%
용문동 12
 
4.2%
원효로1가 10
 
3.5%
동자동 10
 
3.5%
Other values (23) 142
49.3%

업종명
Categorical

Distinct23
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
일반미용업
32 
공중이용시설
28 
세탁업
27 
이용업
21 
위생관리용역업
21 
Other values (18)
159 

Length

Max length23
Median length16
Mean length7.5277778
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row숙박업(일반)
2nd row목욕장업
3rd row이용업
4th row세탁업
5th row위생관리용역업

Common Values

ValueCountFrequency (%)
일반미용업 32
11.1%
공중이용시설 28
 
9.7%
세탁업 27
 
9.4%
이용업 21
 
7.3%
위생관리용역업 21
 
7.3%
피부미용업 20
 
6.9%
숙박업(일반) 18
 
6.2%
종합미용업 17
 
5.9%
네일미용업 17
 
5.9%
목욕장업 14
 
4.9%
Other values (13) 73
25.3%

Length

2024-05-18T17:38:05.948171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 59
14.2%
네일미용업 55
13.3%
미용업 55
13.3%
피부미용업 50
12.0%
화장ㆍ분장 49
11.8%
공중이용시설 28
6.7%
세탁업 27
6.5%
이용업 21
 
5.1%
위생관리용역업 21
 
5.1%
숙박업(일반 18
 
4.3%
Other values (3) 32
7.7%

업소수
Real number (ℝ)

Distinct24
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.96875
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-18T17:38:06.605882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile14
Maximum46
Range45
Interquartile range (IQR)3

Descriptive statistics

Standard deviation5.4263259
Coefficient of variation (CV)1.3672632
Kurtosis18.662466
Mean3.96875
Median Absolute Deviation (MAD)1
Skewness3.7156574
Sum1143
Variance29.445013
MonotonicityNot monotonic
2024-05-18T17:38:07.040410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 119
41.3%
2 44
 
15.3%
3 34
 
11.8%
4 23
 
8.0%
5 13
 
4.5%
6 10
 
3.5%
10 8
 
2.8%
7 7
 
2.4%
8 5
 
1.7%
9 3
 
1.0%
Other values (14) 22
 
7.6%
ValueCountFrequency (%)
1 119
41.3%
2 44
 
15.3%
3 34
 
11.8%
4 23
 
8.0%
5 13
 
4.5%
6 10
 
3.5%
7 7
 
2.4%
8 5
 
1.7%
9 3
 
1.0%
10 8
 
2.8%
ValueCountFrequency (%)
46 1
 
0.3%
35 1
 
0.3%
28 1
 
0.3%
26 1
 
0.3%
24 1
 
0.3%
23 1
 
0.3%
21 1
 
0.3%
19 2
0.7%
18 2
0.7%
15 3
1.0%

Interactions

2024-05-18T17:38:03.538201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T17:38:07.293999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명업종명업소수
법정동명1.0000.0000.000
업종명0.0001.0000.000
업소수0.0000.0001.000
2024-05-18T17:38:07.675867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명업종명
법정동명1.0000.000
업종명0.0001.000
2024-05-18T17:38:07.975634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소수법정동명업종명
업소수1.0000.0000.000
법정동명0.0001.0000.000
업종명0.0000.0001.000

Missing values

2024-05-18T17:38:03.846451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T17:38:04.112726image/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

자치구명법정동명업종명업소수
0용산구후암동숙박업(일반)2
1용산구후암동목욕장업3
2용산구후암동이용업4
3용산구후암동세탁업6
4용산구후암동위생관리용역업3
5용산구후암동공중이용시설5
6용산구후암동일반미용업18
7용산구후암동종합미용업2
8용산구후암동네일미용업1
9용산구후암동화장ㆍ분장 미용업1
자치구명법정동명업종명업소수
278용산구보광동위생관리용역업1
279용산구보광동공중이용시설2
280용산구보광동일반미용업24
281용산구보광동피부미용업8
282용산구보광동종합미용업3
283용산구보광동네일미용업2
284용산구보광동피부미용업, 네일미용업5
285용산구보광동일반미용업, 화장ㆍ분장 미용업1
286용산구보광동일반미용업, 네일미용업, 화장ㆍ분장 미용업4
287용산구서교동일반미용업1