Overview

Dataset statistics

Number of variables4
Number of observations357
Missing cells5
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 KiB
Average record size in memory33.4 B

Variable types

Categorical2
Text1
Numeric1

Dataset

Description자치구명,법정동명,업태명,업소수
Author광진구
URLhttps://data.seoul.go.kr/dataList/OA-9913/S/1/datasetView.do

Alerts

자치구명 has constant value ""Constant
업태명 has 5 (1.4%) missing valuesMissing

Reproduction

Analysis started2024-05-03 23:50:03.181722
Analysis finished2024-05-03 23:50:04.437611
Duration1.26 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
광진구
357 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광진구 357
100.0%

Length

2024-05-03T23:50:04.645140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:50:04.942479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광진구 357
100.0%

법정동명
Categorical

Distinct7
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
자양동
60 
구의동
57 
중곡동
52 
화양동
51 
군자동
51 
Other values (2)
86 

Length

Max length3
Median length3
Mean length2.8851541
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자양동 60
16.8%
구의동 57
16.0%
중곡동 52
14.6%
화양동 51
14.3%
군자동 51
14.3%
광장동 45
12.6%
능동 41
11.5%

Length

2024-05-03T23:50:05.260348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:50:05.620685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자양동 60
16.8%
구의동 57
16.0%
중곡동 52
14.6%
화양동 51
14.3%
군자동 51
14.3%
광장동 45
12.6%
능동 41
11.5%

업태명
Text

MISSING 

Distinct74
Distinct (%)21.0%
Missing5
Missing (%)1.4%
Memory size2.9 KiB
2024-05-03T23:50:06.281435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.6988636
Min length2

Characters and Unicode

Total characters2006
Distinct characters151
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)3.7%

Sample

1st row한식
2nd row중국식
3rd row경양식
4th row일식
5th row분식
ValueCountFrequency (%)
기타 22
 
5.7%
패스트푸드 13
 
3.4%
식품제조가공업 11
 
2.9%
즉석판매제조가공업 7
 
1.8%
영업장판매 7
 
1.8%
유통전문판매업 7
 
1.8%
중국식 7
 
1.8%
일반조리판매 7
 
1.8%
위탁급식영업 7
 
1.8%
수입판매업 7
 
1.8%
Other values (65) 288
75.2%
2024-05-03T23:50:07.452736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 136
 
6.8%
업 115
 
5.7%
매 89
 
4.4%
판 84
 
4.2%
품 61
 
3.0%
기 60
 
3.0%
( 46
 
2.3%
) 46
 
2.3%
통 40
 
2.0%
점 40
 
2.0%
Other values (141) 1289
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1856
92.5%
Open Punctuation 46
 
2.3%
Close Punctuation 46
 
2.3%
Space Separator 31
 
1.5%
Other Punctuation 27
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 136
 
7.3%
업 115
 
6.2%
매 89
 
4.8%
판 84
 
4.5%
품 61
 
3.3%
기 60
 
3.2%
통 40
 
2.2%
점 40
 
2.2%
전 32
 
1.7%
타 32
 
1.7%
Other values (135) 1167
62.9%
Other Punctuation
ValueCountFrequency (%)
/ 19
70.4%
, 7
 
25.9%
. 1
 
3.7%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Space Separator
ValueCountFrequency (%)
31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1856
92.5%
Common 150
 
7.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 136
 
7.3%
업 115
 
6.2%
매 89
 
4.8%
판 84
 
4.5%
품 61
 
3.3%
기 60
 
3.2%
통 40
 
2.2%
점 40
 
2.2%
전 32
 
1.7%
타 32
 
1.7%
Other values (135) 1167
62.9%
Common
ValueCountFrequency (%)
( 46
30.7%
) 46
30.7%
31
20.7%
/ 19
12.7%
, 7
 
4.7%
. 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1856
92.5%
ASCII 150
 
7.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 136
 
7.3%
업 115
 
6.2%
매 89
 
4.8%
판 84
 
4.5%
품 61
 
3.3%
기 60
 
3.2%
통 40
 
2.2%
점 40
 
2.2%
전 32
 
1.7%
타 32
 
1.7%
Other values (135) 1167
62.9%
ASCII
ValueCountFrequency (%)
( 46
30.7%
) 46
30.7%
31
20.7%
/ 19
12.7%
, 7
 
4.7%
. 1
 
0.7%

업소수
Real number (ℝ)

Distinct82
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.014006
Minimum1
Maximum402
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-03T23:50:07.891956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median7
Q320
95-th percentile100
Maximum402
Range401
Interquartile range (IQR)18

Descriptive statistics

Standard deviation47.706527
Coefficient of variation (CV)2.0729345
Kurtosis31.729365
Mean23.014006
Median Absolute Deviation (MAD)6
Skewness4.9727108
Sum8216
Variance2275.9127
MonotonicityNot monotonic
2024-05-03T23:50:08.407257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 64
17.9%
2 42
 
11.8%
4 24
 
6.7%
3 21
 
5.9%
5 16
 
4.5%
7 15
 
4.2%
9 12
 
3.4%
6 11
 
3.1%
11 8
 
2.2%
8 8
 
2.2%
Other values (72) 136
38.1%
ValueCountFrequency (%)
1 64
17.9%
2 42
11.8%
3 21
 
5.9%
4 24
 
6.7%
5 16
 
4.5%
6 11
 
3.1%
7 15
 
4.2%
8 8
 
2.2%
9 12
 
3.4%
10 4
 
1.1%
ValueCountFrequency (%)
402 1
0.3%
399 1
0.3%
364 1
0.3%
303 1
0.3%
196 1
0.3%
149 1
0.3%
144 1
0.3%
142 1
0.3%
137 1
0.3%
134 1
0.3%

Interactions

2024-05-03T23:50:03.560409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T23:50:08.773091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명업태명업소수
법정동명1.0000.0000.070
업태명0.0001.0000.562
업소수0.0700.5621.000
2024-05-03T23:50:09.050425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소수법정동명
업소수1.0000.024
법정동명0.0241.000

Missing values

2024-05-03T23:50:03.936955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T23:50:04.317943image/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

자치구명법정동명업태명업소수
0광진구중곡동한식364
1광진구중곡동중국식20
2광진구중곡동경양식31
3광진구중곡동일식56
4광진구중곡동분식71
5광진구중곡동정종/대포집/소주방19
6광진구중곡동출장조리1
7광진구중곡동패스트푸드4
8광진구중곡동호프/통닭117
9광진구중곡동통닭(치킨)9
자치구명법정동명업태명업소수
347광진구군자동집단급식소 식품판매업1
348광진구군자동건강기능식품수입업3
349광진구군자동영업장판매10
350광진구군자동방문판매3
351광진구군자동전화권유판매1
352광진구군자동전자상거래(통신판매업)64
353광진구군자동도매업(유통)1
354광진구군자동기타(복합 등)1
355광진구군자동기타 건강기능식품일반판매업1
356광진구군자동건강기능식품유통전문판매업9