Overview

Dataset statistics

Number of variables4
Number of observations185
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory33.7 B

Variable types

Categorical2
Text1
Numeric1

Dataset

Description자치구명,법정동명,업태명,업소수
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-10144/S/1/datasetView.do

Alerts

자치구명 has constant value ""Constant

Reproduction

Analysis started2024-05-11 02:57:28.141026
Analysis finished2024-05-11 02:57:30.228977
Duration2.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
금천구
185 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
금천구 185
100.0%

Length

2024-05-11T02:57:30.431871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:57:30.847946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
금천구 185
100.0%

법정동명
Categorical

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
시흥동
63 
가산동
61 
독산동
61 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시흥동 63
34.1%
가산동 61
33.0%
독산동 61
33.0%

Length

2024-05-11T02:57:31.232526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:57:31.538393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시흥동 63
34.1%
가산동 61
33.0%
독산동 61
33.0%

업태명
Text

Distinct70
Distinct (%)38.0%
Missing1
Missing (%)0.5%
Memory size1.6 KiB
2024-05-11T02:57:32.038539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.7391304
Min length2

Characters and Unicode

Total characters1056
Distinct characters152
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

Unique10 ?
Unique (%)5.4%

Sample

1st row한식
2nd row중국식
3rd row경양식
4th row일식
5th row분식
ValueCountFrequency (%)
기타 14
 
7.0%
패스트푸드 6
 
3.0%
식품제조가공업 6
 
3.0%
집단급식소 5
 
2.5%
다단계판매 3
 
1.5%
식품소분업 3
 
1.5%
병원 3
 
1.5%
사회복지시설 3
 
1.5%
산업체 3
 
1.5%
어린이집 3
 
1.5%
Other values (61) 152
75.6%
2024-05-11T02:57:33.330830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 72
 
6.8%
업 63
 
6.0%
매 42
 
4.0%
판 39
 
3.7%
품 36
 
3.4%
기 33
 
3.1%
) 21
 
2.0%
( 21
 
2.0%
점 20
 
1.9%
조 18
 
1.7%
Other values (142) 691
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 982
93.0%
Close Punctuation 21
 
2.0%
Open Punctuation 21
 
2.0%
Space Separator 17
 
1.6%
Other Punctuation 15
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 72
 
7.3%
업 63
 
6.4%
매 42
 
4.3%
판 39
 
4.0%
품 36
 
3.7%
기 33
 
3.4%
점 20
 
2.0%
조 18
 
1.8%
타 18
 
1.8%
통 18
 
1.8%
Other values (136) 623
63.4%
Other Punctuation
ValueCountFrequency (%)
/ 9
60.0%
. 3
 
20.0%
, 3
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 982
93.0%
Common 74
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 72
 
7.3%
업 63
 
6.4%
매 42
 
4.3%
판 39
 
4.0%
품 36
 
3.7%
기 33
 
3.4%
점 20
 
2.0%
조 18
 
1.8%
타 18
 
1.8%
통 18
 
1.8%
Other values (136) 623
63.4%
Common
ValueCountFrequency (%)
) 21
28.4%
( 21
28.4%
17
23.0%
/ 9
12.2%
. 3
 
4.1%
, 3
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 982
93.0%
ASCII 74
 
7.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 72
 
7.3%
업 63
 
6.4%
매 42
 
4.3%
판 39
 
4.0%
품 36
 
3.7%
기 33
 
3.4%
점 20
 
2.0%
조 18
 
1.8%
타 18
 
1.8%
통 18
 
1.8%
Other values (136) 623
63.4%
ASCII
ValueCountFrequency (%)
) 21
28.4%
( 21
28.4%
17
23.0%
/ 9
12.2%
. 3
 
4.1%
, 3
 
4.1%

업소수
Real number (ℝ)

Distinct68
Distinct (%)36.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.189189
Minimum1
Maximum590
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-05-11T02:57:33.752536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median10
Q334
95-th percentile126.6
Maximum590
Range589
Interquartile range (IQR)32

Descriptive statistics

Standard deviation76.837858
Coefficient of variation (CV)2.1835643
Kurtosis28.41881
Mean35.189189
Median Absolute Deviation (MAD)9
Skewness4.9181631
Sum6510
Variance5904.0564
MonotonicityNot monotonic
2024-05-11T02:57:34.340262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 30
 
16.2%
2 18
 
9.7%
3 8
 
4.3%
5 8
 
4.3%
9 7
 
3.8%
13 6
 
3.2%
7 6
 
3.2%
6 6
 
3.2%
4 4
 
2.2%
18 4
 
2.2%
Other values (58) 88
47.6%
ValueCountFrequency (%)
1 30
16.2%
2 18
9.7%
3 8
 
4.3%
4 4
 
2.2%
5 8
 
4.3%
6 6
 
3.2%
7 6
 
3.2%
8 4
 
2.2%
9 7
 
3.8%
10 4
 
2.2%
ValueCountFrequency (%)
590 1
0.5%
540 1
0.5%
424 1
0.5%
351 1
0.5%
225 1
0.5%
186 1
0.5%
166 1
0.5%
157 1
0.5%
146 1
0.5%
127 1
0.5%

Interactions

2024-05-11T02:57:29.541645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:57:34.631816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명업태명업소수
법정동명1.0000.0000.000
업태명0.0001.0000.633
업소수0.0000.6331.000
2024-05-11T02:57:34.896837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소수법정동명
업소수1.0000.000
법정동명0.0001.000

Missing values

2024-05-11T02:57:29.874823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:57:30.135540image/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
0금천구가산동한식590
1금천구가산동중국식73
2금천구가산동경양식43
3금천구가산동일식65
4금천구가산동분식48
5금천구가산동뷔페식5
6금천구가산동정종/대포집/소주방13
7금천구가산동패스트푸드1
8금천구가산동호프/통닭79
9금천구가산동통닭(치킨)13
자치구명법정동명업태명업소수
175금천구시흥동제과점영업29
176금천구시흥동집단급식소 식품판매업8
177금천구시흥동건강기능식품수입업5
178금천구시흥동영업장판매62
179금천구시흥동방문판매17
180금천구시흥동전자상거래(통신판매업)106
181금천구시흥동다단계판매2
182금천구시흥동도매업(유통)1
183금천구시흥동기타 건강기능식품일반판매업1
184금천구시흥동건강기능식품유통전문판매업5