Overview

Dataset statistics

Number of variables4
Number of observations128
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory34.0 B

Variable types

Categorical3
Numeric1

Dataset

Description자치구명,법정동명,업종명,업소수
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-11069/S/1/datasetView.do

Alerts

자치구명 has constant value ""Constant

Reproduction

Analysis started2024-05-11 06:04:35.989432
Analysis finished2024-05-11 06:04:36.518289
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
서초구
128 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서초구 128
100.0%

Length

2024-05-11T15:04:36.657231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:36.852395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서초구 128
100.0%

법정동명
Categorical

Distinct9
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
반포동
21 
방배동
20 
서초동
20 
양재동
19 
잠원동
19 
Other values (4)
29 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
반포동 21
16.4%
방배동 20
15.6%
서초동 20
15.6%
양재동 19
14.8%
잠원동 19
14.8%
우면동 11
8.6%
신원동 7
 
5.5%
내곡동 6
 
4.7%
염곡동 5
 
3.9%

Length

2024-05-11T15:04:37.043365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:37.228208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
반포동 21
16.4%
방배동 20
15.6%
서초동 20
15.6%
양재동 19
14.8%
잠원동 19
14.8%
우면동 11
8.6%
신원동 7
 
5.5%
내곡동 6
 
4.7%
염곡동 5
 
3.9%

업종명
Categorical

Distinct22
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
세탁업
9 
일반미용업
9 
목욕장업
 
8
위생관리용역업
 
8
공중이용시설
 
8
Other values (17)
86 

Length

Max length23
Median length10.5
Mean length9.15625
Min length3

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
세탁업 9
 
7.0%
일반미용업 9
 
7.0%
목욕장업 8
 
6.2%
위생관리용역업 8
 
6.2%
공중이용시설 8
 
6.2%
피부미용업 7
 
5.5%
종합미용업 7
 
5.5%
피부미용업, 네일미용업 6
 
4.7%
이용업 6
 
4.7%
네일미용업 6
 
4.7%
Other values (12) 54
42.2%

Length

2024-05-11T15:04:37.463909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 36
16.4%
일반미용업 34
15.5%
네일미용업 33
15.1%
화장ㆍ분장 33
15.1%
피부미용업 30
13.7%
세탁업 9
 
4.1%
목욕장업 8
 
3.7%
위생관리용역업 8
 
3.7%
공중이용시설 8
 
3.7%
종합미용업 7
 
3.2%
Other values (3) 13
 
5.9%

업소수
Real number (ℝ)

Distinct43
Distinct (%)33.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.53125
Minimum1
Maximum441
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:04:37.699350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q318.75
95-th percentile86.3
Maximum441
Range440
Interquartile range (IQR)16.75

Descriptive statistics

Standard deviation47.402604
Coefficient of variation (CV)2.2015723
Kurtosis48.681195
Mean21.53125
Median Absolute Deviation (MAD)4
Skewness6.0348022
Sum2756
Variance2247.0069
MonotonicityNot monotonic
2024-05-11T15:04:37.946374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 26
20.3%
4 12
 
9.4%
5 12
 
9.4%
2 10
 
7.8%
3 9
 
7.0%
9 7
 
5.5%
11 5
 
3.9%
27 3
 
2.3%
12 3
 
2.3%
22 2
 
1.6%
Other values (33) 39
30.5%
ValueCountFrequency (%)
1 26
20.3%
2 10
 
7.8%
3 9
 
7.0%
4 12
9.4%
5 12
9.4%
7 2
 
1.6%
8 1
 
0.8%
9 7
 
5.5%
10 2
 
1.6%
11 5
 
3.9%
ValueCountFrequency (%)
441 1
0.8%
143 1
0.8%
139 1
0.8%
113 1
0.8%
112 1
0.8%
109 1
0.8%
87 1
0.8%
85 2
1.6%
74 1
0.8%
69 1
0.8%

Interactions

2024-05-11T15:04:36.139209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:04:38.078852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명업종명업소수
법정동명1.0000.0000.000
업종명0.0001.0000.083
업소수0.0000.0831.000
2024-05-11T15:04:38.234759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명법정동명
업종명1.0000.000
법정동명0.0001.000
2024-05-11T15:04:38.357529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소수법정동명업종명
업소수1.0000.0000.011
법정동명0.0001.0000.000
업종명0.0110.0001.000

Missing values

2024-05-11T15:04:36.305049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:04:36.452222image/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
0서초구방배동숙박업(일반)7
1서초구방배동목욕장업9
2서초구방배동이용업21
3서초구방배동미용업1
4서초구방배동세탁업40
5서초구방배동위생관리용역업51
6서초구방배동공중이용시설113
7서초구방배동일반미용업139
8서초구방배동피부미용업74
9서초구방배동종합미용업87
자치구명법정동명업종명업소수
118서초구염곡동위생관리용역업1
119서초구염곡동공중이용시설5
120서초구염곡동일반미용업1
121서초구신원동숙박업(일반)1
122서초구신원동목욕장업1
123서초구신원동세탁업2
124서초구신원동일반미용업3
125서초구신원동피부미용업1
126서초구신원동종합미용업1
127서초구신원동일반미용업, 화장ㆍ분장 미용업2