Overview

Dataset statistics

Number of variables4
Number of observations66
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory35.0 B

Variable types

Numeric1
Categorical2
Text1

Dataset

Description부산광역시기장군_의원(의회)_현황_20221013
Author부산광역시 기장군
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15084350

Alerts

코드 is highly overall correlated with 대수High correlation
대수 is highly overall correlated with 코드High correlation

Reproduction

Analysis started2023-12-10 16:16:42.809306
Analysis finished2023-12-10 16:16:43.278032
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

코드
Real number (ℝ)

HIGH CORRELATION 

Distinct49
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4960.7576
Minimum1010
Maximum9050
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2023-12-11T01:16:43.345785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1010
5-th percentile1042.5
Q12060
median5045
Q37047.5
95-th percentile9017.5
Maximum9050
Range8040
Interquartile range (IQR)4987.5

Descriptive statistics

Standard deviation2627.5788
Coefficient of variation (CV)0.52967288
Kurtosis-1.3231947
Mean4960.7576
Median Absolute Deviation (MAD)2965
Skewness-0.055815027
Sum327410
Variance6904170.2
MonotonicityNot monotonic
2023-12-11T01:16:43.502384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
6060 3
 
4.5%
2060 3
 
4.5%
1060 3
 
4.5%
3010 2
 
3.0%
6040 2
 
3.0%
3020 2
 
3.0%
5030 2
 
3.0%
6010 2
 
3.0%
2010 2
 
3.0%
6070 2
 
3.0%
Other values (39) 43
65.2%
ValueCountFrequency (%)
1010 1
 
1.5%
1020 1
 
1.5%
1030 1
 
1.5%
1040 1
 
1.5%
1050 1
 
1.5%
1060 3
4.5%
2010 2
3.0%
2020 1
 
1.5%
2030 1
 
1.5%
2040 1
 
1.5%
ValueCountFrequency (%)
9050 1
1.5%
9040 1
1.5%
9030 1
1.5%
9020 1
1.5%
9010 1
1.5%
8080 1
1.5%
8070 1
1.5%
8060 1
1.5%
8050 2
3.0%
8040 1
1.5%

대수
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size660.0 B
9 대
9 
8 대
8 
7 대
8 
6 대
7 
5 대
7 
Other values (4)
27 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9 대
2nd row9 대
3rd row9 대
4th row9 대
5th row9 대

Common Values

ValueCountFrequency (%)
9 대 9
13.6%
8 대 8
12.1%
7 대 8
12.1%
6 대 7
10.6%
5 대 7
10.6%
4 대 7
10.6%
3 대 7
10.6%
2 대 7
10.6%
1 대 6
9.1%

Length

2023-12-11T01:16:43.646029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:16:43.768206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 66
50.0%
9 9
 
6.8%
8 8
 
6.1%
7 8
 
6.1%
6 7
 
5.3%
5 7
 
5.3%
4 7
 
5.3%
3 7
 
5.3%
2 7
 
5.3%
1 6
 
4.5%

이름
Text

Distinct45
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Memory size660.0 B
2023-12-11T01:16:44.023559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.969697
Min length2

Characters and Unicode

Total characters196
Distinct characters69
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

Unique29 ?
Unique (%)43.9%

Sample

1st row박기조
2nd row허준섭
3rd row박홍복
4th row황운철
5th row구본영
ValueCountFrequency (%)
박홍복 3
 
4.5%
김대군 3
 
4.5%
문장호 3
 
4.5%
정종복 3
 
4.5%
최영환 3
 
4.5%
황운철 2
 
3.0%
이정택 2
 
3.0%
김만선 2
 
3.0%
김쌍우 2
 
3.0%
김정우 2
 
3.0%
Other values (35) 41
62.1%
2023-12-11T01:16:44.378081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 18
 
9.2%
정 14
 
7.1%
박 8
 
4.1%
우 8
 
4.1%
복 6
 
3.1%
영 6
 
3.1%
호 5
 
2.6%
이 5
 
2.6%
종 5
 
2.6%
원 4
 
2.0%
Other values (59) 117
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 196
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 18
 
9.2%
정 14
 
7.1%
박 8
 
4.1%
우 8
 
4.1%
복 6
 
3.1%
영 6
 
3.1%
호 5
 
2.6%
이 5
 
2.6%
종 5
 
2.6%
원 4
 
2.0%
Other values (59) 117
59.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 196
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 18
 
9.2%
정 14
 
7.1%
박 8
 
4.1%
우 8
 
4.1%
복 6
 
3.1%
영 6
 
3.1%
호 5
 
2.6%
이 5
 
2.6%
종 5
 
2.6%
원 4
 
2.0%
Other values (59) 117
59.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 196
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 18
 
9.2%
정 14
 
7.1%
박 8
 
4.1%
우 8
 
4.1%
복 6
 
3.1%
영 6
 
3.1%
호 5
 
2.6%
이 5
 
2.6%
종 5
 
2.6%
원 4
 
2.0%
Other values (59) 117
59.7%

선거구
Categorical

Distinct5
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size660.0 B
<NA>
27 
가 선거구
14 
나 선거구
11 
다 선거구
9 
비례대표
5 

Length

Max length5
Median length5
Mean length4.5151515
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가 선거구
2nd row가 선거구
3rd row나 선거구
4th row나 선거구
5th row다 선거구

Common Values

ValueCountFrequency (%)
<NA> 27
40.9%
가 선거구 14
21.2%
나 선거구 11
16.7%
다 선거구 9
 
13.6%
비례대표 5
 
7.6%

Length

2023-12-11T01:16:44.548083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:16:44.680623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
선거구 34
34.0%
na 27
27.0%
가 14
14.0%
나 11
 
11.0%
다 9
 
9.0%
비례대표 5
 
5.0%

Interactions

2023-12-11T01:16:43.003934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:16:44.787993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
코드대수이름선거구
코드1.0000.9130.9830.307
대수0.9131.0000.0000.000
이름0.9830.0001.0000.996
선거구0.3070.0000.9961.000
2023-12-11T01:16:44.890964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
선거구대수
선거구1.0000.000
대수0.0001.000
2023-12-11T01:16:44.973754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
코드대수선거구
코드1.0000.7250.195
대수0.7251.0000.000
선거구0.1950.0001.000

Missing values

2023-12-11T01:16:43.160542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:16:43.244912image/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

코드대수이름선거구
090109 대박기조가 선거구
190509 대허준섭가 선거구
260609 대박홍복나 선거구
380109 대황운철나 선거구
490309 대구본영다 선거구
590409 대김원일다 선거구
680509 대박우식다 선거구
780309 대맹승자다 선거구
890209 대구혜진비례대표
980708 대김대군나 선거구
코드대수이름선거구
5620302 대박재호<NA>
5720402 대이재종<NA>
5820502 대이정택<NA>
5920602 대최영환<NA>
6010201 대권성학<NA>
6110601 대문장호<NA>
6210401 대손무헌<NA>
6310301 대원성태<NA>
6410501 대정창조<NA>
6510101 대최원구<NA>