Overview

Dataset statistics

Number of variables4
Number of observations136
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory34.0 B

Variable types

Categorical3
Numeric1

Dataset

Description자치구명,법정동명,업종명,업소수
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-2299/S/1/datasetView.do

Alerts

자치구명 has constant value ""Constant

Reproduction

Analysis started2024-05-11 04:27:15.039946
Analysis finished2024-05-11 04:27:16.512276
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
구로구
136 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구로구 136
100.0%

Length

2024-05-11T04:27:16.713537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:27:17.024240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구로구 136
100.0%

법정동명
Categorical

Distinct10
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
구로동
23 
개봉동
19 
신도림동
17 
고척동
16 
오류동
16 
Other values (5)
45 

Length

Max length4
Median length3
Mean length3.0808824
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구로동 23
16.9%
개봉동 19
14.0%
신도림동 17
12.5%
고척동 16
11.8%
오류동 16
11.8%
가리봉동 14
10.3%
궁동 12
8.8%
항동 8
 
5.9%
온수동 6
 
4.4%
천왕동 5
 
3.7%

Length

2024-05-11T04:27:17.376206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:27:17.938843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구로동 23
16.9%
개봉동 19
14.0%
신도림동 17
12.5%
고척동 16
11.8%
오류동 16
11.8%
가리봉동 14
10.3%
궁동 12
8.8%
항동 8
 
5.9%
온수동 6
 
4.4%
천왕동 5
 
3.7%

업종명
Categorical

Distinct26
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
세탁업
10 
일반미용업
10 
네일미용업
10 
위생관리용역업
9 
피부미용업
9 
Other values (21)
88 

Length

Max length23
Median length16
Mean length8.3823529
Min length3

Unique

Unique4 ?
Unique (%)2.9%

Sample

1st row이용업
2nd row미용업
3rd row세탁업
4th row위생관리용역업
5th row공중이용시설

Common Values

ValueCountFrequency (%)
세탁업 10
 
7.4%
일반미용업 10
 
7.4%
네일미용업 10
 
7.4%
위생관리용역업 9
 
6.6%
피부미용업 9
 
6.6%
이용업 8
 
5.9%
네일미용업, 화장ㆍ분장 미용업 8
 
5.9%
종합미용업 8
 
5.9%
공중이용시설 7
 
5.1%
화장ㆍ분장 미용업 6
 
4.4%
Other values (16) 51
37.5%

Length

2024-05-11T04:27:18.416493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 36
16.7%
네일미용업 35
16.2%
피부미용업 31
14.4%
화장ㆍ분장 31
14.4%
일반미용업 26
12.0%
세탁업 10
 
4.6%
위생관리용역업 9
 
4.2%
이용업 8
 
3.7%
종합미용업 8
 
3.7%
공중이용시설 7
 
3.2%
Other values (6) 15
6.9%

업소수
Real number (ℝ)

Distinct35
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.801471
Minimum1
Maximum232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T04:27:18.830032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median4
Q312
95-th percentile59
Maximum232
Range231
Interquartile range (IQR)11

Descriptive statistics

Standard deviation29.940885
Coefficient of variation (CV)2.1693982
Kurtosis26.8139
Mean13.801471
Median Absolute Deviation (MAD)3
Skewness4.7237527
Sum1877
Variance896.45659
MonotonicityNot monotonic
2024-05-11T04:27:19.457793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 35
25.7%
2 17
12.5%
4 13
 
9.6%
10 8
 
5.9%
3 7
 
5.1%
5 6
 
4.4%
12 5
 
3.7%
7 4
 
2.9%
13 3
 
2.2%
8 3
 
2.2%
Other values (25) 35
25.7%
ValueCountFrequency (%)
1 35
25.7%
2 17
12.5%
3 7
 
5.1%
4 13
 
9.6%
5 6
 
4.4%
6 3
 
2.2%
7 4
 
2.9%
8 3
 
2.2%
9 3
 
2.2%
10 8
 
5.9%
ValueCountFrequency (%)
232 1
0.7%
171 1
0.7%
115 1
0.7%
100 1
0.7%
87 1
0.7%
78 1
0.7%
65 1
0.7%
57 1
0.7%
54 1
0.7%
51 1
0.7%

Interactions

2024-05-11T04:27:15.489682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T04:27:19.763935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명업종명업소수
법정동명1.0000.0000.000
업종명0.0001.0000.000
업소수0.0000.0001.000
2024-05-11T04:27:20.050040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명법정동명
업종명1.0000.000
법정동명0.0001.000
2024-05-11T04:27:20.418159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소수법정동명업종명
업소수1.0000.0000.000
법정동명0.0001.0000.000
업종명0.0000.0001.000

Missing values

2024-05-11T04:27:16.048741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T04:27:16.414922image/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
0구로구신도림동이용업5
1구로구신도림동미용업4
2구로구신도림동세탁업12
3구로구신도림동위생관리용역업10
4구로구신도림동공중이용시설10
5구로구신도림동일반미용업41
6구로구신도림동피부미용업18
7구로구신도림동종합미용업10
8구로구신도림동네일미용업8
9구로구신도림동일반미용업, 피부미용업1
자치구명법정동명업종명업소수
126구로구천왕동네일미용업1
127구로구천왕동일반미용업, 네일미용업1
128구로구항동세탁업1
129구로구항동위생관리용역업2
130구로구항동일반미용업12
131구로구항동피부미용업3
132구로구항동종합미용업2
133구로구항동네일미용업5
134구로구항동일반미용업, 화장ㆍ분장 미용업1
135구로구항동네일미용업, 화장ㆍ분장 미용업1