Overview

Dataset statistics

Number of variables7
Number of observations30
Missing cells60
Missing cells (%)28.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory62.4 B

Variable types

Categorical4
Unsupported2
Text1

Dataset

Description샘플 데이터
Author경기콘텐츠진흥원
URLhttps://www.bigdata-region.kr/#/dataset/c876b88a-1609-4f7b-b157-2274d359a771

Alerts

기준년월 has constant value ""Constant
시도명 has constant value ""Constant
시군구명 has 30 (100.0%) missing valuesMissing
인구평균수 has 30 (100.0%) missing valuesMissing
유입시군구명 has unique valuesUnique
시군구명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
인구평균수 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 13:51:09.068241
Analysis finished2023-12-10 13:51:09.768120
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2017-01
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017-01
2nd row2017-01
3rd row2017-01
4th row2017-01
5th row2017-01

Common Values

ValueCountFrequency (%)
2017-01 30
100.0%

Length

2023-12-10T22:51:09.876538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:51:10.053939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017-01 30
100.0%

시도명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 30
100.0%

Length

2023-12-10T22:51:10.229567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:51:10.373061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

유입시도명
Categorical

Distinct12
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
8 
경상남도
4 
경상북도
4 
강원도
3 
대구광역시
2 
Other values (7)
9 

Length

Max length7
Median length5
Mean length3.9333333
Min length3

Unique

Unique5 ?
Unique (%)16.7%

Sample

1st row경기도
2nd row강원도
3rd row경기도
4th row경기도
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 8
26.7%
경상남도 4
13.3%
경상북도 4
13.3%
강원도 3
 
10.0%
대구광역시 2
 
6.7%
전라북도 2
 
6.7%
충청남도 2
 
6.7%
대전광역시 1
 
3.3%
부산광역시 1
 
3.3%
서울특별시 1
 
3.3%
Other values (2) 2
 
6.7%

Length

2023-12-10T22:51:10.571267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 8
26.7%
경상남도 4
13.3%
경상북도 4
13.3%
강원도 3
 
10.0%
대구광역시 2
 
6.7%
전라북도 2
 
6.7%
충청남도 2
 
6.7%
대전광역시 1
 
3.3%
부산광역시 1
 
3.3%
서울특별시 1
 
3.3%
Other values (2) 2
 
6.7%

유입시군구명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:51:10.883444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.5
Min length2

Characters and Unicode

Total characters105
Distinct characters42
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

Unique30 ?
Unique (%)100.0%

Sample

1st row과천시
2nd row철원군
3rd row부천시
4th row의정부시
5th row수원시 팔달구
ValueCountFrequency (%)
남구 2
 
5.9%
과천시 1
 
2.9%
홍성군 1
 
2.9%
부안군 1
 
2.9%
진안군 1
 
2.9%
서귀포시 1
 
2.9%
천안시 1
 
2.9%
동남구 1
 
2.9%
영월군 1
 
2.9%
강북구 1
 
2.9%
Other values (23) 23
67.6%
2023-12-10T22:51:11.455203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 13
 
12.4%
군 13
 
12.4%
구 9
 
8.6%
천 5
 
4.8%
원 4
 
3.8%
부 4
 
3.8%
남 4
 
3.8%
4
 
3.8%
성 4
 
3.8%
안 3
 
2.9%
Other values (32) 42
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 101
96.2%
Space Separator 4
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 13
 
12.9%
군 13
 
12.9%
구 9
 
8.9%
천 5
 
5.0%
원 4
 
4.0%
부 4
 
4.0%
남 4
 
4.0%
성 4
 
4.0%
안 3
 
3.0%
포 3
 
3.0%
Other values (31) 39
38.6%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 101
96.2%
Common 4
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 13
 
12.9%
군 13
 
12.9%
구 9
 
8.9%
천 5
 
5.0%
원 4
 
4.0%
부 4
 
4.0%
남 4
 
4.0%
성 4
 
4.0%
안 3
 
3.0%
포 3
 
3.0%
Other values (31) 39
38.6%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 101
96.2%
ASCII 4
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 13
 
12.9%
군 13
 
12.9%
구 9
 
8.9%
천 5
 
5.0%
원 4
 
4.0%
부 4
 
4.0%
남 4
 
4.0%
성 4
 
4.0%
안 3
 
3.0%
포 3
 
3.0%
Other values (31) 39
38.6%
ASCII
ValueCountFrequency (%)
4
100.0%

성별코드
Categorical

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowM
3rd rowF
4th rowM
5th rowF

Common Values

ValueCountFrequency (%)
F 17
56.7%
M 13
43.3%

Length

2023-12-10T22:51:11.666355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:51:11.841630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 17
56.7%
m 13
43.3%

인구평균수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

Correlations

2023-12-10T22:51:11.967528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유입시도명유입시군구명성별코드
유입시도명1.0001.0000.000
유입시군구명1.0001.0001.000
성별코드0.0001.0001.000
2023-12-10T22:51:12.116593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유입시도명성별코드
유입시도명1.0000.000
성별코드0.0001.000
2023-12-10T22:51:12.234461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유입시도명성별코드
유입시도명1.0000.000
성별코드0.0001.000

Missing values

2023-12-10T22:51:09.422306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:51:09.667117image/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

기준년월시도명시군구명유입시도명유입시군구명성별코드인구평균수
02017-01경기도<NA>경기도과천시M<NA>
12017-01경기도<NA>강원도철원군M<NA>
22017-01경기도<NA>경기도부천시F<NA>
32017-01경기도<NA>경기도의정부시M<NA>
42017-01경기도<NA>경기도수원시 팔달구F<NA>
52017-01경기도<NA>경기도이천시M<NA>
62017-01경기도<NA>경기도포천시F<NA>
72017-01경기도<NA>경상남도고성군F<NA>
82017-01경기도<NA>경상남도산청군M<NA>
92017-01경기도<NA>경상남도창녕군M<NA>
기준년월시도명시군구명유입시도명유입시군구명성별코드인구평균수
202017-01경기도<NA>제주특별자치도서귀포시F<NA>
212017-01경기도<NA>충청남도천안시 동남구F<NA>
222017-01경기도<NA>충청남도홍성군M<NA>
232017-01경기도<NA>강원도영월군F<NA>
242017-01경기도<NA>강원도원주시F<NA>
252017-01경기도<NA>경기도여주시F<NA>
262017-01경기도<NA>경기도성남시 중원구F<NA>
272017-01경기도<NA>경상남도거제시F<NA>
282017-01경기도<NA>경상북도군위군F<NA>
292017-01경기도<NA>경상북도청도군M<NA>