Overview

Dataset statistics

Number of variables5
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory46.4 B

Variable types

Text1
Categorical4

Dataset

Description샘플 데이터
Author한국신용데이터
URLhttps://bigdata-region.kr/#/dataset/ed5e6f75-f92a-4331-a896-5627c8381f60

Alerts

사회적 거리두기 단계코드 is highly overall correlated with 시작일자 and 2 other fieldsHigh correlation
시작일자 is highly overall correlated with 종료일자 and 2 other fieldsHigh correlation
종료일자 is highly overall correlated with 시작일자 and 2 other fieldsHigh correlation
차수 is highly overall correlated with 시작일자 and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 13:54:09.653073
Analysis finished2023-12-10 13:54:10.212332
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Text

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:54:10.375512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters60
Distinct characters21
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

Unique7 ?
Unique (%)23.3%

Sample

1st row인천
2nd row전북
3rd row대전
4th row전남
5th row세종
ValueCountFrequency (%)
서울 3
10.0%
경기 3
10.0%
부산 3
10.0%
경북 2
 
6.7%
인천 2
 
6.7%
대구 2
 
6.7%
전북 2
 
6.7%
경남 2
 
6.7%
전남 2
 
6.7%
광주 2
 
6.7%
Other values (7) 7
23.3%
2023-12-10T22:54:10.828151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 7
 
11.7%
북 5
 
8.3%
전 5
 
8.3%
남 5
 
8.3%
산 4
 
6.7%
울 4
 
6.7%
대 3
 
5.0%
서 3
 
5.0%
주 3
 
5.0%
기 3
 
5.0%
Other values (11) 18
30.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 7
 
11.7%
북 5
 
8.3%
전 5
 
8.3%
남 5
 
8.3%
산 4
 
6.7%
울 4
 
6.7%
대 3
 
5.0%
서 3
 
5.0%
주 3
 
5.0%
기 3
 
5.0%
Other values (11) 18
30.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 7
 
11.7%
북 5
 
8.3%
전 5
 
8.3%
남 5
 
8.3%
산 4
 
6.7%
울 4
 
6.7%
대 3
 
5.0%
서 3
 
5.0%
주 3
 
5.0%
기 3
 
5.0%
Other values (11) 18
30.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 7
 
11.7%
북 5
 
8.3%
전 5
 
8.3%
남 5
 
8.3%
산 4
 
6.7%
울 4
 
6.7%
대 3
 
5.0%
서 3
 
5.0%
주 3
 
5.0%
기 3
 
5.0%
Other values (11) 18
30.0%

시작일자
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2020-03-22
17 
2020-08-23
9 
2020-08-16
2 
2020-08-17
 
1
2020-08-18
 
1

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row2020-03-22
2nd row2020-03-22
3rd row2020-03-22
4th row2020-03-22
5th row2020-03-22

Common Values

ValueCountFrequency (%)
2020-03-22 17
56.7%
2020-08-23 9
30.0%
2020-08-16 2
 
6.7%
2020-08-17 1
 
3.3%
2020-08-18 1
 
3.3%

Length

2023-12-10T22:54:11.137629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:11.347240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-03-22 17
56.7%
2020-08-23 9
30.0%
2020-08-16 2
 
6.7%
2020-08-17 1
 
3.3%
2020-08-18 1
 
3.3%

종료일자
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2020-05-06
17 
2020-10-12
6 
2020-08-30
4 
2020-08-23
2 
2020-08-31
 
1

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row2020-05-06
2nd row2020-05-06
3rd row2020-05-06
4th row2020-05-06
5th row2020-05-06

Common Values

ValueCountFrequency (%)
2020-05-06 17
56.7%
2020-10-12 6
 
20.0%
2020-08-30 4
 
13.3%
2020-08-23 2
 
6.7%
2020-08-31 1
 
3.3%

Length

2023-12-10T22:54:11.655713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:11.922236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-05-06 17
56.7%
2020-10-12 6
 
20.0%
2020-08-30 4
 
13.3%
2020-08-23 2
 
6.7%
2020-08-31 1
 
3.3%

차수
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
17 
2
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 17
56.7%
2 13
43.3%

Length

2023-12-10T22:54:12.114602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:12.461046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 17
56.7%
2 13
43.3%

사회적 거리두기 단계코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
17 
2
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 17
56.7%
2 13
43.3%

Length

2023-12-10T22:54:12.758250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:13.350427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 17
56.7%
2 13
43.3%

Correlations

2023-12-10T22:54:13.549145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명시작일자종료일자차수사회적 거리두기 단계코드
시도명1.0000.0000.0000.0000.000
시작일자0.0001.0000.9921.0001.000
종료일자0.0000.9921.0001.0001.000
차수0.0001.0001.0001.0000.994
사회적 거리두기 단계코드0.0001.0001.0000.9941.000
2023-12-10T22:54:13.831429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사회적 거리두기 단계코드시작일자종료일자차수
사회적 거리두기 단계코드1.0000.9450.9450.930
시작일자0.9451.0000.8710.945
종료일자0.9450.8711.0000.945
차수0.9300.9450.9451.000
2023-12-10T22:54:14.016380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시작일자종료일자차수사회적 거리두기 단계코드
시작일자1.0000.8710.9450.945
종료일자0.8711.0000.9450.945
차수0.9450.9451.0000.930
사회적 거리두기 단계코드0.9450.9450.9301.000

Missing values

2023-12-10T22:54:10.000137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:54:10.150496image/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

시도명시작일자종료일자차수사회적 거리두기 단계코드
0인천2020-03-222020-05-0611
1전북2020-03-222020-05-0611
2대전2020-03-222020-05-0611
3전남2020-03-222020-05-0611
4세종2020-03-222020-05-0611
5경기2020-03-222020-05-0611
6제주2020-03-222020-05-0611
7경북2020-03-222020-05-0611
8경남2020-03-222020-05-0611
9강원2020-03-222020-05-0611
시도명시작일자종료일자차수사회적 거리두기 단계코드
20인천2020-08-182020-08-3022
21대구2020-08-232020-10-1222
22전북2020-08-232020-10-1222
23광주2020-08-232020-10-1222
24경남2020-08-232020-10-1222
25경북2020-08-232020-10-1222
26경기2020-08-232020-08-3022
27서울2020-08-232020-08-3022
28부산2020-08-232020-08-3022
29전남2020-08-232020-10-1222