Overview

Dataset statistics

Number of variables5
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory45.4 B

Variable types

Categorical4
Text1

Dataset

Description샘플 데이터
Author한국신용데이터
URLhttps://bigdata-region.kr/#/dataset/dbc2ec45-d70e-446d-926a-c4d82cd9492b

Alerts

년월 has constant value ""Constant
매출평균액 has constant value ""Constant
유형명 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 유형명High correlation

Reproduction

Analysis started2023-12-22 20:34:38.415225
Analysis finished2023-12-22 20:34:52.949523
Duration14.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유형명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
지역
17 
업종
9 
지역x업종
4 

Length

Max length5
Median length2
Mean length2.4
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지역 17
56.7%
업종 9
30.0%
지역x업종 4
 
13.3%

Length

2023-12-22T20:34:53.554224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T20:34:54.361915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지역 17
56.7%
업종 9
30.0%
지역x업종 4
 
13.3%

년월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2021-05
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-05
2nd row2021-05
3rd row2021-05
4th row2021-05
5th row2021-05

Common Values

ValueCountFrequency (%)
2021-05 30
100.0%

Length

2023-12-22T20:34:55.012916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T20:34:55.523748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-05 30
100.0%

업종명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
전체
17 
제조업
3 
외식업
2 
기타
2 
서비스업
 
1
Other values (5)
5 

Length

Max length8
Median length2
Mean length2.6666667
Min length2

Unique

Unique6 ?
Unique (%)20.0%

Sample

1st row서비스업
2nd row외식업
3rd row농업/임업/어업
4th row정보통신업
5th row건설업

Common Values

ValueCountFrequency (%)
전체 17
56.7%
제조업 3
 
10.0%
외식업 2
 
6.7%
기타 2
 
6.7%
서비스업 1
 
3.3%
농업/임업/어업 1
 
3.3%
정보통신업 1
 
3.3%
건설업 1
 
3.3%
부동산업 1
 
3.3%
유통업 1
 
3.3%

Length

2023-12-22T20:34:56.482898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T20:34:57.071465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 17
56.7%
제조업 3
 
10.0%
외식업 2
 
6.7%
기타 2
 
6.7%
서비스업 1
 
3.3%
농업/임업/어업 1
 
3.3%
정보통신업 1
 
3.3%
건설업 1
 
3.3%
부동산업 1
 
3.3%
유통업 1
 
3.3%

시도명
Text

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-22T20:34:57.666134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.9
Min length2

Characters and Unicode

Total characters117
Distinct characters32
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)46.7%

Sample

1st row전국
2nd row전국
3rd row전국
4th row전국
5th row전국
ValueCountFrequency (%)
전국 9
30.0%
충청북도 3
 
10.0%
대구광역시 2
 
6.7%
제주특별자치도 2
 
6.7%
대전광역시 1
 
3.3%
전라남도 1
 
3.3%
광주광역시 1
 
3.3%
인천광역시 1
 
3.3%
부산광역시 1
 
3.3%
충청남도 1
 
3.3%
Other values (8) 8
26.7%
2023-12-22T20:34:59.269756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 12
 
10.3%
도 12
 
10.3%
시 9
 
7.7%
국 9
 
7.7%
광 8
 
6.8%
역 7
 
6.0%
북 5
 
4.3%
별 4
 
3.4%
충 4
 
3.4%
청 4
 
3.4%
Other values (22) 43
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 12
 
10.3%
도 12
 
10.3%
시 9
 
7.7%
국 9
 
7.7%
광 8
 
6.8%
역 7
 
6.0%
북 5
 
4.3%
별 4
 
3.4%
충 4
 
3.4%
청 4
 
3.4%
Other values (22) 43
36.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 12
 
10.3%
도 12
 
10.3%
시 9
 
7.7%
국 9
 
7.7%
광 8
 
6.8%
역 7
 
6.0%
북 5
 
4.3%
별 4
 
3.4%
충 4
 
3.4%
청 4
 
3.4%
Other values (22) 43
36.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 12
 
10.3%
도 12
 
10.3%
시 9
 
7.7%
국 9
 
7.7%
광 8
 
6.8%
역 7
 
6.0%
북 5
 
4.3%
별 4
 
3.4%
충 4
 
3.4%
청 4
 
3.4%
Other values (22) 43
36.8%

매출평균액
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
10000000
30 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10000000
2nd row10000000
3rd row10000000
4th row10000000
5th row10000000

Common Values

ValueCountFrequency (%)
10000000 30
100.0%

Length

2023-12-22T20:34:59.934804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T20:35:01.954738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10000000 30
100.0%

Correlations

2023-12-22T20:36:08.076771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형명업종명시도명
유형명1.0000.8420.877
업종명0.8421.0000.000
시도명0.8770.0001.000
2023-12-22T20:36:28.666168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형명업종명
유형명1.0000.646
업종명0.6461.000
2023-12-22T20:36:28.922355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형명업종명
유형명1.0000.646
업종명0.6461.000

Missing values

2023-12-22T20:34:50.777432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-22T20:34:52.194120image/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

유형명년월업종명시도명매출평균액
0업종2021-05서비스업전국10000000
1업종2021-05외식업전국10000000
2업종2021-05농업/임업/어업전국10000000
3업종2021-05정보통신업전국10000000
4업종2021-05건설업전국10000000
5업종2021-05부동산업전국10000000
6업종2021-05제조업전국10000000
7업종2021-05유통업전국10000000
8업종2021-05기타전국10000000
9지역2021-05전체전라북도10000000
유형명년월업종명시도명매출평균액
20지역2021-05전체충청남도10000000
21지역2021-05전체부산광역시10000000
22지역2021-05전체인천광역시10000000
23지역2021-05전체대구광역시10000000
24지역2021-05전체광주광역시10000000
25지역2021-05전체울산광역시10000000
26지역x업종2021-05기타충청북도10000000
27지역x업종2021-05제조업대구광역시10000000
28지역x업종2021-05외식업제주특별자치도10000000
29지역x업종2021-05제조업충청북도10000000