Overview

Dataset statistics

Number of variables4
Number of observations358
Missing cells5
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 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 started2024-05-18 01:09:42.474278
Analysis finished2024-05-18 01:09:43.749860
Duration1.28 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
358 

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 358
100.0%

Length

2024-05-18T10:09:43.939491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:09:44.240349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광진구 358
100.0%

법정동명
Categorical

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

Length

Max length3
Median length3
Mean length2.8854749
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
15.9%
중곡동 52
14.5%
화양동 52
14.5%
군자동 51
14.2%
광장동 45
12.6%
능동 41
11.5%

Length

2024-05-18T10:09:44.643991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:09:45.021306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자양동 60
16.8%
구의동 57
15.9%
중곡동 52
14.5%
화양동 52
14.5%
군자동 51
14.2%
광장동 45
12.6%
능동 41
11.5%

업태명
Text

MISSING 

Distinct74
Distinct (%)21.0%
Missing5
Missing (%)1.4%
Memory size2.9 KiB
2024-05-18T10:09:45.688202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.6968839
Min length2

Characters and Unicode

Total characters2011
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%
한식 7
 
1.8%
식품소분업 7
 
1.8%
영업장판매 7
 
1.8%
위탁급식영업 7
 
1.8%
중국식 7
 
1.8%
편의점 7
 
1.8%
유통전문판매업 7
 
1.8%
Other values (65) 289
75.3%
2024-05-18T10:09:47.244526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 137
 
6.8%
업 116
 
5.8%
매 89
 
4.4%
판 84
 
4.2%
품 62
 
3.1%
기 60
 
3.0%
( 46
 
2.3%
) 46
 
2.3%
점 40
 
2.0%
통 40
 
2.0%
Other values (141) 1291
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1861
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 137
 
7.4%
업 116
 
6.2%
매 89
 
4.8%
판 84
 
4.5%
품 62
 
3.3%
기 60
 
3.2%
점 40
 
2.1%
통 40
 
2.1%
전 32
 
1.7%
타 32
 
1.7%
Other values (135) 1169
62.8%
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 1861
92.5%
Common 150
 
7.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 137
 
7.4%
업 116
 
6.2%
매 89
 
4.8%
판 84
 
4.5%
품 62
 
3.3%
기 60
 
3.2%
점 40
 
2.1%
통 40
 
2.1%
전 32
 
1.7%
타 32
 
1.7%
Other values (135) 1169
62.8%
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 1861
92.5%
ASCII 150
 
7.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 137
 
7.4%
업 116
 
6.2%
매 89
 
4.8%
판 84
 
4.5%
품 62
 
3.3%
기 60
 
3.2%
점 40
 
2.1%
통 40
 
2.1%
전 32
 
1.7%
타 32
 
1.7%
Other values (135) 1169
62.8%
ASCII
ValueCountFrequency (%)
( 46
30.7%
) 46
30.7%
31
20.7%
/ 19
12.7%
, 7
 
4.7%
. 1
 
0.7%

업소수
Real number (ℝ)

Distinct83
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.916201
Minimum1
Maximum400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-18T10:09:47.928857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median6.5
Q320
95-th percentile99.15
Maximum400
Range399
Interquartile range (IQR)18

Descriptive statistics

Standard deviation47.513156
Coefficient of variation (CV)2.0733435
Kurtosis31.6996
Mean22.916201
Median Absolute Deviation (MAD)5.5
Skewness4.9680799
Sum8204
Variance2257.5
MonotonicityNot monotonic
2024-05-18T10:09:48.955531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 64
17.9%
2 45
 
12.6%
4 24
 
6.7%
3 19
 
5.3%
5 16
 
4.5%
7 15
 
4.2%
6 11
 
3.1%
9 11
 
3.1%
8 8
 
2.2%
13 8
 
2.2%
Other values (73) 137
38.3%
ValueCountFrequency (%)
1 64
17.9%
2 45
12.6%
3 19
 
5.3%
4 24
 
6.7%
5 16
 
4.5%
6 11
 
3.1%
7 15
 
4.2%
8 8
 
2.2%
9 11
 
3.1%
10 5
 
1.4%
ValueCountFrequency (%)
400 1
0.3%
398 1
0.3%
363 1
0.3%
302 1
0.3%
192 1
0.3%
147 1
0.3%
144 1
0.3%
143 1
0.3%
136 1
0.3%
135 1
0.3%

Interactions

2024-05-18T10:09:42.933539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T10:09:49.478371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명업태명업소수
법정동명1.0000.0000.000
업태명0.0001.0000.577
업소수0.0000.5771.000
2024-05-18T10:09:49.924612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소수법정동명
업소수1.0000.000
법정동명0.0001.000

Missing values

2024-05-18T10:09:43.393037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T10:09:43.658457image/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
0광진구중곡동한식363
1광진구중곡동중국식20
2광진구중곡동경양식31
3광진구중곡동일식56
4광진구중곡동분식72
5광진구중곡동정종/대포집/소주방19
6광진구중곡동출장조리1
7광진구중곡동패스트푸드4
8광진구중곡동호프/통닭118
9광진구중곡동통닭(치킨)9
자치구명법정동명업태명업소수
348광진구군자동집단급식소 식품판매업1
349광진구군자동건강기능식품수입업3
350광진구군자동영업장판매10
351광진구군자동방문판매3
352광진구군자동전화권유판매1
353광진구군자동전자상거래(통신판매업)63
354광진구군자동도매업(유통)1
355광진구군자동기타(복합 등)1
356광진구군자동기타 건강기능식품일반판매업1
357광진구군자동건강기능식품유통전문판매업9