Overview

Dataset statistics

Number of variables4
Number of observations470
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.3 KiB
Average record size in memory33.3 B

Variable types

Categorical2
Text1
Numeric1

Dataset

Description자치구명,법정동명,업종명,업소수
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-10222/S/1/datasetView.do

Alerts

자치구명 has constant value ""Constant

Reproduction

Analysis started2024-05-04 02:19:00.968007
Analysis finished2024-05-04 02:19:01.952350
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
중구
470 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 470
100.0%

Length

2024-05-04T02:19:02.087535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:19:02.288253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 470
100.0%

법정동명
Text

Distinct74
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-04T02:19:02.616511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.1765957
Min length2

Characters and Unicode

Total characters1963
Distinct characters68
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.9%

Sample

1st row무교동
2nd row무교동
3rd row무교동
4th row무교동
5th row무교동
ValueCountFrequency (%)
신당동 19
 
4.0%
황학동 14
 
3.0%
을지로6가 13
 
2.8%
광희동1가 13
 
2.8%
충무로2가 12
 
2.6%
충무로1가 12
 
2.6%
쌍림동 11
 
2.3%
명동2가 11
 
2.3%
남산동2가 10
 
2.1%
장충동2가 10
 
2.1%
Other values (64) 345
73.4%
2024-05-04T02:19:03.363414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 330
16.8%
가 290
 
14.8%
로 140
 
7.1%
2 103
 
5.2%
1 100
 
5.1%
남 63
 
3.2%
충 62
 
3.2%
무 52
 
2.6%
을 49
 
2.5%
지 49
 
2.5%
Other values (58) 725
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1673
85.2%
Decimal Number 290
 
14.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 330
19.7%
가 290
17.3%
로 140
 
8.4%
남 63
 
3.8%
충 62
 
3.7%
무 52
 
3.1%
을 49
 
2.9%
지 49
 
2.9%
문 34
 
2.0%
현 32
 
1.9%
Other values (51) 572
34.2%
Decimal Number
ValueCountFrequency (%)
2 103
35.5%
1 100
34.5%
3 35
 
12.1%
5 22
 
7.6%
4 14
 
4.8%
6 13
 
4.5%
7 3
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1673
85.2%
Common 290
 
14.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 330
19.7%
가 290
17.3%
로 140
 
8.4%
남 63
 
3.8%
충 62
 
3.7%
무 52
 
3.1%
을 49
 
2.9%
지 49
 
2.9%
문 34
 
2.0%
현 32
 
1.9%
Other values (51) 572
34.2%
Common
ValueCountFrequency (%)
2 103
35.5%
1 100
34.5%
3 35
 
12.1%
5 22
 
7.6%
4 14
 
4.8%
6 13
 
4.5%
7 3
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1673
85.2%
ASCII 290
 
14.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 330
19.7%
가 290
17.3%
로 140
 
8.4%
남 63
 
3.8%
충 62
 
3.7%
무 52
 
3.1%
을 49
 
2.9%
지 49
 
2.9%
문 34
 
2.0%
현 32
 
1.9%
Other values (51) 572
34.2%
ASCII
ValueCountFrequency (%)
2 103
35.5%
1 100
34.5%
3 35
 
12.1%
5 22
 
7.6%
4 14
 
4.8%
6 13
 
4.5%
7 3
 
1.0%

업종명
Categorical

Distinct23
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
공중이용시설
69 
숙박업(일반)
60 
위생관리용역업
48 
일반미용업
48 
피부미용업
39 
Other values (18)
206 

Length

Max length23
Median length19
Mean length6.4702128
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row목욕장업
2nd row위생관리용역업
3rd row공중이용시설
4th row피부미용업
5th row종합미용업

Common Values

ValueCountFrequency (%)
공중이용시설 69
14.7%
숙박업(일반) 60
12.8%
위생관리용역업 48
10.2%
일반미용업 48
10.2%
피부미용업 39
8.3%
세탁업 28
 
6.0%
이용업 26
 
5.5%
종합미용업 26
 
5.5%
목욕장업 23
 
4.9%
네일미용업 22
 
4.7%
Other values (13) 81
17.2%

Length

2024-05-04T02:19:03.811069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 70
12.5%
공중이용시설 69
12.3%
숙박업(일반 60
10.7%
피부미용업 59
10.5%
네일미용업 49
8.8%
위생관리용역업 48
8.6%
미용업 48
8.6%
화장ㆍ분장 35
6.2%
세탁업 28
 
5.0%
이용업 26
 
4.6%
Other values (3) 68
12.1%

업소수
Real number (ℝ)

Distinct25
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6085106
Minimum1
Maximum110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-04T02:19:04.187093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile12
Maximum110
Range109
Interquartile range (IQR)3

Descriptive statistics

Standard deviation6.6649908
Coefficient of variation (CV)1.8470199
Kurtosis140.60952
Mean3.6085106
Median Absolute Deviation (MAD)1
Skewness9.697224
Sum1696
Variance44.422102
MonotonicityNot monotonic
2024-05-04T02:19:04.566832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 223
47.4%
2 78
 
16.6%
3 40
 
8.5%
4 37
 
7.9%
5 18
 
3.8%
6 17
 
3.6%
7 10
 
2.1%
12 7
 
1.5%
8 6
 
1.3%
11 5
 
1.1%
Other values (15) 29
 
6.2%
ValueCountFrequency (%)
1 223
47.4%
2 78
 
16.6%
3 40
 
8.5%
4 37
 
7.9%
5 18
 
3.8%
6 17
 
3.6%
7 10
 
2.1%
8 6
 
1.3%
9 4
 
0.9%
10 2
 
0.4%
ValueCountFrequency (%)
110 1
 
0.2%
37 1
 
0.2%
28 1
 
0.2%
27 1
 
0.2%
24 1
 
0.2%
23 2
0.4%
22 2
0.4%
21 2
0.4%
18 3
0.6%
17 2
0.4%

Interactions

2024-05-04T02:19:01.213557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T02:19:04.815656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명업종명업소수
법정동명1.0000.0000.000
업종명0.0001.0000.000
업소수0.0000.0001.000
2024-05-04T02:19:05.047110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소수업종명
업소수1.0000.000
업종명0.0001.000

Missing values

2024-05-04T02:19:01.610582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T02:19:01.873093image/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
0중구무교동목욕장업1
1중구무교동위생관리용역업3
2중구무교동공중이용시설11
3중구무교동피부미용업4
4중구무교동종합미용업1
5중구다동숙박업(일반)3
6중구다동미용업1
7중구다동세탁업1
8중구다동위생관리용역업4
9중구다동공중이용시설12
자치구명법정동명업종명업소수
460중구만리동1가이용업1
461중구만리동1가위생관리용역업1
462중구만리동1가공중이용시설1
463중구만리동1가일반미용업1
464중구만리동2가세탁업2
465중구만리동2가공중이용시설5
466중구만리동2가일반미용업2
467중구만리동2가종합미용업2
468중구만리동2가네일미용업, 화장ㆍ분장 미용업1
469중구여의도동위생관리용역업1