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/f208559f-8ba9-4cac-a016-850a10111bf4

Alerts

년월 has constant value ""Constant
평균 매출 건수 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 20:43:35.360910
Analysis finished2023-12-22 20:43:37.388161
Duration2.03 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

2023-12-22T20:43:37.700896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T20:43:38.534524image/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
Sep-21
30 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSep-21
2nd rowSep-21
3rd rowSep-21
4th rowSep-21
5th rowSep-21

Common Values

ValueCountFrequency (%)
Sep-21 30
100.0%

Length

2023-12-22T20:43:39.103589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T20:43:39.561759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
sep-21 30
100.0%

업종명
Categorical

HIGH CORRELATION 

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

Length

Max length8
Median length2
Mean length2.7666667
Min length2

Unique

Unique6 ?
Unique (%)20.0%

Sample

1st row정보통신업
2nd row건설업
3rd row제조업
4th row서비스업
5th row부동산업

Common Values

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

Length

2023-12-22T20:43:40.146835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T20:43:40.703944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 17
56.7%
건설업 3
 
10.0%
정보통신업 2
 
6.7%
제조업 2
 
6.7%
서비스업 1
 
3.3%
부동산업 1
 
3.3%
유통업 1
 
3.3%
농업/임업/어업 1
 
3.3%
기타 1
 
3.3%
외식업 1
 
3.3%

시도명
Text

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-22T20:43:41.266550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.8333333
Min length2

Characters and Unicode

Total characters115
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

Unique13 ?
Unique (%)43.3%

Sample

1st row전국
2nd row전국
3rd row전국
4th row전국
5th row전국
ValueCountFrequency (%)
전국 9
30.0%
충청북도 2
 
6.7%
경상남도 2
 
6.7%
인천광역시 2
 
6.7%
대구광역시 2
 
6.7%
울산광역시 1
 
3.3%
제주특별자치도 1
 
3.3%
세종특별자치시 1
 
3.3%
경상북도 1
 
3.3%
전라북도 1
 
3.3%
Other values (8) 8
26.7%
2023-12-22T20:43:42.263369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 12
 
10.4%
도 11
 
9.6%
시 10
 
8.7%
국 9
 
7.8%
광 9
 
7.8%
역 8
 
7.0%
남 4
 
3.5%
경 4
 
3.5%
북 4
 
3.5%
특 3
 
2.6%
Other values (22) 41
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 115
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 12
 
10.4%
도 11
 
9.6%
시 10
 
8.7%
국 9
 
7.8%
광 9
 
7.8%
역 8
 
7.0%
남 4
 
3.5%
경 4
 
3.5%
북 4
 
3.5%
특 3
 
2.6%
Other values (22) 41
35.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 115
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 12
 
10.4%
도 11
 
9.6%
시 10
 
8.7%
국 9
 
7.8%
광 9
 
7.8%
역 8
 
7.0%
남 4
 
3.5%
경 4
 
3.5%
북 4
 
3.5%
특 3
 
2.6%
Other values (22) 41
35.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 115
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 12
 
10.4%
도 11
 
9.6%
시 10
 
8.7%
국 9
 
7.8%
광 9
 
7.8%
역 8
 
7.0%
남 4
 
3.5%
경 4
 
3.5%
북 4
 
3.5%
특 3
 
2.6%
Other values (22) 41
35.7%

평균 매출 건수
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
100
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100

Common Values

ValueCountFrequency (%)
100 30
100.0%

Length

2023-12-22T20:43:42.841807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T20:43:43.240683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100 30
100.0%

Correlations

2023-12-22T20:43:43.451609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형명업종명시도명
유형명1.0000.8420.799
업종명0.8421.0000.000
시도명0.7990.0001.000
2023-12-22T20:43:43.684289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형명업종명
유형명1.0000.646
업종명0.6461.000
2023-12-22T20:43:43.922880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형명업종명
유형명1.0000.646
업종명0.6461.000

Missing values

2023-12-22T20:43:36.577015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-22T20:43:37.086582image/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

유형명년월업종명시도명평균 매출 건수
0업종Sep-21정보통신업전국100
1업종Sep-21건설업전국100
2업종Sep-21제조업전국100
3업종Sep-21서비스업전국100
4업종Sep-21부동산업전국100
5업종Sep-21유통업전국100
6업종Sep-21농업/임업/어업전국100
7업종Sep-21기타전국100
8업종Sep-21외식업전국100
9지역Sep-21전체강원도100
유형명년월업종명시도명평균 매출 건수
20지역Sep-21전체울산광역시100
21지역Sep-21전체전라북도100
22지역Sep-21전체충청북도100
23지역Sep-21전체경상북도100
24지역Sep-21전체세종특별자치시100
25지역Sep-21전체전라남도100
26지역x업종Sep-21제조업충청북도100
27지역x업종Sep-21정보통신업인천광역시100
28지역x업종Sep-21건설업경상남도100
29지역x업종Sep-21건설업대구광역시100