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

DateTime1
Categorical3
Unsupported2
Text1

Dataset

Description샘플 데이터
Author경기콘텐츠진흥원
URLhttps://www.bigdata-region.kr/#/dataset/8eed2f30-d3b9-48e5-893f-10523e53aa45

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
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 14:17:11.962878
Analysis finished2023-12-10 14:17:12.555836
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2017-01-01 00:00:00
Maximum2017-01-01 00:00:00
2023-12-10T23:17:12.642669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:12.796577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

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

2023-12-10T23:17:12.998293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:13.167265image/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

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
4 
경상남도
4 
강원도
3 
경상북도
3 
광주광역시
3 
Other values (8)
13 

Length

Max length5
Median length4
Mean length4.1
Min length3

Unique

Unique5 ?
Unique (%)16.7%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 4
13.3%
경상남도 4
13.3%
강원도 3
10.0%
경상북도 3
10.0%
광주광역시 3
10.0%
대구광역시 3
10.0%
충청남도 3
10.0%
인천광역시 2
6.7%
부산광역시 1
 
3.3%
서울특별시 1
 
3.3%
Other values (3) 3
10.0%

Length

2023-12-10T23:17:13.313622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 4
13.3%
경상남도 4
13.3%
강원도 3
10.0%
경상북도 3
10.0%
광주광역시 3
10.0%
대구광역시 3
10.0%
충청남도 3
10.0%
인천광역시 2
6.7%
부산광역시 1
 
3.3%
서울특별시 1
 
3.3%
Other values (3) 3
10.0%

유입시군구명
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:17:13.599874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.2
Min length2

Characters and Unicode

Total characters96
Distinct characters41
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

Unique28 ?
Unique (%)93.3%

Sample

1st row양주시
2nd row원주시
3rd row여주시
4th row청도군
5th row거제시
ValueCountFrequency (%)
서구 2
 
6.2%
청주시 1
 
3.1%
논산시 1
 
3.1%
광산구 1
 
3.1%
영양군 1
 
3.1%
하동군 1
 
3.1%
영덕군 1
 
3.1%
마산합포구 1
 
3.1%
창원시 1
 
3.1%
밀양시 1
 
3.1%
Other values (21) 21
65.6%
2023-12-10T23:17:14.108159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 13
 
13.5%
구 13
 
13.5%
군 7
 
7.3%
서 5
 
5.2%
산 5
 
5.2%
주 4
 
4.2%
원 4
 
4.2%
천 3
 
3.1%
청 3
 
3.1%
양 3
 
3.1%
Other values (31) 36
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94
97.9%
Space Separator 2
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 13
 
13.8%
구 13
 
13.8%
군 7
 
7.4%
서 5
 
5.3%
산 5
 
5.3%
주 4
 
4.3%
원 4
 
4.3%
천 3
 
3.2%
청 3
 
3.2%
양 3
 
3.2%
Other values (30) 34
36.2%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 94
97.9%
Common 2
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 13
 
13.8%
구 13
 
13.8%
군 7
 
7.4%
서 5
 
5.3%
산 5
 
5.3%
주 4
 
4.3%
원 4
 
4.3%
천 3
 
3.2%
청 3
 
3.2%
양 3
 
3.2%
Other values (30) 34
36.2%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 94
97.9%
ASCII 2
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 13
 
13.8%
구 13
 
13.8%
군 7
 
7.4%
서 5
 
5.3%
산 5
 
5.3%
주 4
 
4.3%
원 4
 
4.3%
천 3
 
3.2%
청 3
 
3.2%
양 3
 
3.2%
Other values (30) 34
36.2%
ASCII
ValueCountFrequency (%)
2
100.0%

성별코드
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
F
15 
M
15 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
F 15
50.0%
M 15
50.0%

Length

2023-12-10T23:17:14.360965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:14.513359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 15
50.0%
m 15
50.0%

인구평균수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Correlations

2023-12-10T23:17:14.641562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유입시도명유입시군구명성별코드
유입시도명1.0000.9640.614
유입시군구명0.9641.0001.000
성별코드0.6141.0001.000
2023-12-10T23:17:14.832421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별코드유입시도명
성별코드1.0000.439
유입시도명0.4391.000
2023-12-10T23:17:14.957304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유입시도명성별코드
유입시도명1.0000.439
성별코드0.4391.000

Missing values

2023-12-10T23:17:12.290802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:17:12.491652image/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>경기도양주시F<NA>
12017-01경기도<NA>강원도원주시F<NA>
22017-01경기도<NA>경기도여주시F<NA>
32017-01경기도<NA>경상북도청도군M<NA>
42017-01경기도<NA>경상남도거제시F<NA>
52017-01경기도<NA>광주광역시남구M<NA>
62017-01경기도<NA>광주광역시서구M<NA>
72017-01경기도<NA>대구광역시달서구M<NA>
82017-01경기도<NA>대구광역시서구M<NA>
92017-01경기도<NA>부산광역시강서구M<NA>
기준년월시도명시군구명유입시도명유입시군구명성별코드인구평균수
202017-01경기도<NA>강원도홍천군F<NA>
212017-01경기도<NA>경기도구리시F<NA>
222017-01경기도<NA>경기도이천시F<NA>
232017-01경기도<NA>경상남도밀양시F<NA>
242017-01경기도<NA>경상남도창원시 마산합포구M<NA>
252017-01경기도<NA>경상북도영덕군M<NA>
262017-01경기도<NA>경상남도하동군M<NA>
272017-01경기도<NA>경상북도영양군M<NA>
282017-01경기도<NA>광주광역시광산구M<NA>
292017-01경기도<NA>대구광역시수성구F<NA>