Overview

Dataset statistics

Number of variables5
Number of observations102
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory42.3 B

Variable types

Categorical4
DateTime1

Dataset

Description샘플 데이터
Author한국신용데이터
URLhttps://bigdata-region.kr/#/dataset/d83e9dcf-a7e9-4293-ae47-adb477d8cfec

Alerts

년월 has constant value ""Constant
평균인건비 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 20:39:25.911290
Analysis finished2023-12-22 20:39:32.385655
Duration6.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유형명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size948.0 B
지역X업종
78 
지역
17 
업종
 
6
통합
 
1

Length

Max length5
Median length5
Mean length4.2941176
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
지역X업종 78
76.5%
지역 17
 
16.7%
업종 6
 
5.9%
통합 1
 
1.0%

Length

2023-12-22T20:39:32.823069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T20:39:33.336057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지역x업종 78
76.5%
지역 17
 
16.7%
업종 6
 
5.9%
통합 1
 
1.0%

년월
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
Minimum2023-01-01 00:00:00
Maximum2023-01-01 00:00:00
2023-12-22T20:39:33.862817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-22T20:39:34.302847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

시도명
Categorical

Distinct18
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size948.0 B
전국
7 
부산광역시
7 
경기도
7 
서울특별시
7 
인천광역시
7 
Other values (13)
67 

Length

Max length7
Median length5
Mean length4.3921569
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전국 7
 
6.9%
부산광역시 7
 
6.9%
경기도 7
 
6.9%
서울특별시 7
 
6.9%
인천광역시 7
 
6.9%
경상남도 6
 
5.9%
충청남도 6
 
5.9%
경상북도 6
 
5.9%
대구광역시 6
 
5.9%
대전광역시 6
 
5.9%
Other values (8) 37
36.3%

Length

2023-12-22T20:39:34.735410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전국 7
 
6.9%
경기도 7
 
6.9%
서울특별시 7
 
6.9%
인천광역시 7
 
6.9%
부산광역시 7
 
6.9%
경상북도 6
 
5.9%
대구광역시 6
 
5.9%
대전광역시 6
 
5.9%
충청남도 6
 
5.9%
경상남도 6
 
5.9%
Other values (8) 37
36.3%

업종명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size948.0 B
유통업
18 
외식업
18 
서비스업
18 
전체
18 
제조업
15 
Other values (2)
15 

Length

Max length4
Median length3
Mean length2.9509804
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row유통업
3rd row외식업
4th row제조업
5th row건설업

Common Values

ValueCountFrequency (%)
유통업 18
17.6%
외식업 18
17.6%
서비스업 18
17.6%
전체 18
17.6%
제조업 15
14.7%
건설업 10
9.8%
기타 5
 
4.9%

Length

2023-12-22T20:39:35.344693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T20:39:35.946558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통업 18
17.6%
외식업 18
17.6%
서비스업 18
17.6%
전체 18
17.6%
제조업 15
14.7%
건설업 10
9.8%
기타 5
 
4.9%

평균인건비
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
10000000
102 

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 102
100.0%

Length

2023-12-22T20:39:36.708046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T20:39:37.267881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10000000 102
100.0%

Correlations

2023-12-22T20:39:37.604838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형명시도명업종명
유형명1.0000.6860.682
시도명0.6861.0000.000
업종명0.6820.0001.000
2023-12-22T20:39:38.410403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형명업종명시도명
유형명1.0000.5370.416
업종명0.5371.0000.000
시도명0.4160.0001.000
2023-12-22T20:39:39.497074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형명시도명업종명
유형명1.0000.4160.537
시도명0.4161.0000.000
업종명0.5370.0001.000

Missing values

2023-12-22T20:39:31.698527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-22T20:39:32.206997image/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

유형명년월시도명업종명평균인건비
0업종2023-01-01전국기타10000000
1업종2023-01-01전국유통업10000000
2업종2023-01-01전국외식업10000000
3업종2023-01-01전국제조업10000000
4업종2023-01-01전국건설업10000000
5업종2023-01-01전국서비스업10000000
6지역2023-01-01경상남도전체10000000
7지역2023-01-01부산광역시전체10000000
8지역2023-01-01경기도전체10000000
9지역2023-01-01경상북도전체10000000
유형명년월시도명업종명평균인건비
92지역X업종2023-01-01광주광역시외식업10000000
93지역X업종2023-01-01충청북도외식업10000000
94지역X업종2023-01-01대전광역시서비스업10000000
95지역X업종2023-01-01경기도제조업10000000
96지역X업종2023-01-01서울특별시유통업10000000
97지역X업종2023-01-01경기도유통업10000000
98지역X업종2023-01-01강원도유통업10000000
99지역X업종2023-01-01부산광역시유통업10000000
100지역X업종2023-01-01전라북도외식업10000000
101통합2023-01-01전국전체10000000