Overview

Dataset statistics

Number of variables8
Number of observations65
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory69.0 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description세목별 납세자 유형, 관내/관외 인원 현황을 제공합니다.특히 관외 납세자에 대한 부과징수 정책 수립시 기초자료로 활용할수 있습니다.
Author부산광역시 사상구
URLhttps://www.data.go.kr/data/15079687/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
납세자수 is highly overall correlated with 납세자유형High correlation
납세자유형 is highly overall correlated with 납세자수High correlation

Reproduction

Analysis started2024-04-21 01:52:19.240101
Analysis finished2024-04-21 01:52:21.016673
Duration1.78 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
부산광역시
65 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 65
100.0%

Length

2024-04-21T10:52:21.093960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:52:21.215299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 65
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
사상구
65 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사상구 65
100.0%

Length

2024-04-21T10:52:21.310611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:52:21.413781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사상구 65
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
26530
65 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26530
2nd row26530
3rd row26530
4th row26530
5th row26530

Common Values

ValueCountFrequency (%)
26530 65
100.0%

Length

2024-04-21T10:52:21.511764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:52:21.626666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26530 65
100.0%

과세년도
Categorical

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size652.0 B
2020
33 
2021
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 33
50.8%
2021 32
49.2%

Length

2024-04-21T10:52:21.733887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:52:21.835081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 33
50.8%
2021 32
49.2%

세목명
Categorical

Distinct9
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size652.0 B
재산세
8 
주민세
8 
취득세
8 
자동차세
8 
등록면허세
8 
Other values (4)
25 

Length

Max length7
Median length5
Mean length4.1692308
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row등록세
2nd row재산세
3rd row재산세
4th row재산세
5th row재산세

Common Values

ValueCountFrequency (%)
재산세 8
12.3%
주민세 8
12.3%
취득세 8
12.3%
자동차세 8
12.3%
등록면허세 8
12.3%
지방소득세 8
12.3%
지역자원시설세 8
12.3%
등록세 7
10.8%
지방소비세 2
 
3.1%

Length

2024-04-21T10:52:21.977919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:52:22.121087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 8
12.3%
주민세 8
12.3%
취득세 8
12.3%
자동차세 8
12.3%
등록면허세 8
12.3%
지방소득세 8
12.3%
지역자원시설세 8
12.3%
등록세 7
10.8%
지방소비세 2
 
3.1%

납세자유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size652.0 B
법인
33 
개인
32 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row법인
2nd row개인
3rd row개인
4th row법인
5th row법인

Common Values

ValueCountFrequency (%)
법인 33
50.8%
개인 32
49.2%

Length

2024-04-21T10:52:22.268478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:52:22.361714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 33
50.8%
개인 32
49.2%

관내_관외
Boolean

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size197.0 B
True
34 
False
31 
ValueCountFrequency (%)
True 34
52.3%
False 31
47.7%
2024-04-21T10:52:22.436587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

HIGH CORRELATION 

Distinct62
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10468.431
Minimum1
Maximum78347
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-04-21T10:52:22.542825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q160
median1882
Q312148
95-th percentile56834.2
Maximum78347
Range78346
Interquartile range (IQR)12088

Descriptive statistics

Standard deviation18712.686
Coefficient of variation (CV)1.787535
Kurtosis4.8322395
Mean10468.431
Median Absolute Deviation (MAD)1854
Skewness2.3376792
Sum680448
Variance3.5016463 × 108
MonotonicityNot monotonic
2024-04-21T10:52:22.689025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3
 
4.6%
36 2
 
3.1%
2 1
 
1.5%
47 1
 
1.5%
25469 1
 
1.5%
57136 1
 
1.5%
771 1
 
1.5%
1336 1
 
1.5%
14172 1
 
1.5%
78347 1
 
1.5%
Other values (52) 52
80.0%
ValueCountFrequency (%)
1 3
4.6%
2 1
 
1.5%
3 1
 
1.5%
4 1
 
1.5%
5 1
 
1.5%
23 1
 
1.5%
28 1
 
1.5%
33 1
 
1.5%
36 2
3.1%
39 1
 
1.5%
ValueCountFrequency (%)
78347 1
1.5%
75361 1
1.5%
57136 1
1.5%
57111 1
1.5%
55727 1
1.5%
54021 1
1.5%
31184 1
1.5%
28515 1
1.5%
26012 1
1.5%
25469 1
1.5%

Interactions

2024-04-21T10:52:20.554618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:52:22.798068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명납세자유형관내_관외납세자수
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0000.0000.0000.421
납세자유형0.0000.0001.0000.0000.564
관내_관외0.0000.0000.0001.0000.305
납세자수0.0000.4210.5640.3051.000
2024-04-21T10:52:22.910986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관내_관외과세년도세목명납세자유형
관내_관외1.0000.0000.0000.000
과세년도0.0001.0000.0000.000
세목명0.0000.0001.0000.000
납세자유형0.0000.0000.0001.000
2024-04-21T10:52:23.025367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수과세년도세목명납세자유형관내_관외
납세자수1.0000.0000.2290.5810.312
과세년도0.0001.0000.0000.0000.000
세목명0.2290.0001.0000.0000.000
납세자유형0.5810.0000.0001.0000.000
관내_관외0.3120.0000.0000.0001.000

Missing values

2024-04-21T10:52:20.858589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:52:20.963123image/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

시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
0부산광역시사상구265302020등록세법인Y2
1부산광역시사상구265302020재산세개인N26012
2부산광역시사상구265302020재산세개인Y55727
3부산광역시사상구265302020재산세법인N728
4부산광역시사상구265302020재산세법인Y1290
5부산광역시사상구265302020주민세개인N17989
6부산광역시사상구265302020주민세개인Y75361
7부산광역시사상구265302020주민세법인N1288
8부산광역시사상구265302020주민세법인Y4058
9부산광역시사상구265302020취득세개인N2298
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
55부산광역시사상구265302021등록면허세법인Y3066
56부산광역시사상구265302021지방소득세개인N12148
57부산광역시사상구265302021지방소득세개인Y31184
58부산광역시사상구265302021지방소득세법인N1284
59부산광역시사상구265302021지방소득세법인Y3537
60부산광역시사상구265302021지방소비세법인Y1
61부산광역시사상구265302021지역자원시설세개인N36
62부산광역시사상구265302021지역자원시설세개인Y59
63부산광역시사상구265302021지역자원시설세법인N3
64부산광역시사상구265302021지역자원시설세법인Y39