Overview

Dataset statistics

Number of variables8
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory70.9 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description세목별 납세 인원 및 종류(거주자, 비거주자, 법인 등) 현황을 제공하며관외 납세자에 대한 부과징수 정책 수립시 기초자료로 활용될 수 있습니다.
Author부산광역시 부산진구
URLhttps://www.data.go.kr/data/15079274/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant

Reproduction

Analysis started2024-04-21 01:51:15.008799
Analysis finished2024-04-21 01:51:16.769519
Duration1.76 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
부산광역시
34 

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 34
100.0%

Length

2024-04-21T10:51:16.836756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:51:16.934248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 34
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
부산진구
34 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산진구 34
100.0%

Length

2024-04-21T10:51:17.038747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:51:17.132204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산진구 34
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
26230
34 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26230
2nd row26230
3rd row26230
4th row26230
5th row26230

Common Values

ValueCountFrequency (%)
26230 34
100.0%

Length

2024-04-21T10:51:17.228304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:51:17.324857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26230 34
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
2022
34 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 34
100.0%

Length

2024-04-21T10:51:17.427249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:51:17.520028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 34
100.0%

세목명
Categorical

Distinct10
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Memory size404.0 B
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
등록면허세
4 
Other values (5)
14 

Length

Max length7
Median length6
Mean length4.1176471
Min length3

Unique

Unique1 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 4
11.8%
주민세 4
11.8%
취득세 4
11.8%
자동차세 4
11.8%
등록면허세 4
11.8%
지방소득세 4
11.8%
지역자원시설세 4
11.8%
등록세 3
8.8%
레저세 2
5.9%
지방소비세 1
 
2.9%

Length

2024-04-21T10:51:17.635731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:51:17.786647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 4
11.8%
주민세 4
11.8%
취득세 4
11.8%
자동차세 4
11.8%
등록면허세 4
11.8%
지방소득세 4
11.8%
지역자원시설세 4
11.8%
등록세 3
8.8%
레저세 2
5.9%
지방소비세 1
 
2.9%

납세자유형
Categorical

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
개인
17 
법인
17 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 17
50.0%
법인 17
50.0%

Length

2024-04-21T10:51:17.959713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:51:18.074655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 17
50.0%
법인 17
50.0%

관내_관외
Boolean

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size166.0 B
False
18 
True
16 
ValueCountFrequency (%)
False 18
52.9%
True 16
47.1%
2024-04-21T10:51:18.177106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17664.118
Minimum1
Maximum137015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-04-21T10:51:18.291926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q174.5
median2306.5
Q314398.5
95-th percentile95757.4
Maximum137015
Range137014
Interquartile range (IQR)14324

Descriptive statistics

Standard deviation33856.731
Coefficient of variation (CV)1.9166953
Kurtosis4.9073996
Mean17664.118
Median Absolute Deviation (MAD)2278
Skewness2.3437952
Sum600580
Variance1.1462782 × 109
MonotonicityNot monotonic
2024-04-21T10:51:18.422076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 3
 
8.8%
67 1
 
2.9%
72043 1
 
2.9%
2457 1
 
2.9%
21294 1
 
2.9%
31159 1
 
2.9%
2954 1
 
2.9%
3523 1
 
2.9%
21971 1
 
2.9%
2126 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
1 3
8.8%
3 1
 
2.9%
14 1
 
2.9%
43 1
 
2.9%
56 1
 
2.9%
62 1
 
2.9%
67 1
 
2.9%
97 1
 
2.9%
256 1
 
2.9%
372 1
 
2.9%
ValueCountFrequency (%)
137015 1
2.9%
101376 1
2.9%
92732 1
2.9%
72043 1
2.9%
55902 1
2.9%
31159 1
2.9%
21971 1
2.9%
21294 1
2.9%
15536 1
2.9%
10986 1
2.9%

Interactions

2024-04-21T10:51:16.257810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:51:18.539569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형관내_관외납세자수
세목명1.0000.0000.0000.000
납세자유형0.0001.0000.0000.583
관내_관외0.0000.0001.0000.386
납세자수0.0000.5830.3861.000
2024-04-21T10:51:18.652574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형관내_관외세목명
납세자유형1.0000.0000.000
관내_관외0.0001.0000.000
세목명0.0000.0001.000
2024-04-21T10:51:18.752797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수세목명납세자유형관내_관외
납세자수1.0000.0000.3910.250
세목명0.0001.0000.0000.000
납세자유형0.3910.0001.0000.000
관내_관외0.2500.0000.0001.000

Missing values

2024-04-21T10:51:16.586520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:51:16.712891image/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
0부산광역시부산진구262302022등록세개인N67
1부산광역시부산진구262302022등록세개인Y43
2부산광역시부산진구262302022등록세법인N1
3부산광역시부산진구262302022레저세개인N1
4부산광역시부산진구262302022레저세법인N3
5부산광역시부산진구262302022재산세개인N55902
6부산광역시부산진구262302022재산세개인Y101376
7부산광역시부산진구262302022재산세법인N1349
8부산광역시부산진구262302022재산세법인Y1118
9부산광역시부산진구262302022주민세개인N15536
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
24부산광역시부산진구262302022등록면허세법인Y3523
25부산광역시부산진구262302022지방소득세개인N21971
26부산광역시부산진구262302022지방소득세개인Y72043
27부산광역시부산진구262302022지방소득세법인N2126
28부산광역시부산진구262302022지방소득세법인Y3586
29부산광역시부산진구262302022지방소비세법인Y1
30부산광역시부산진구262302022지역자원시설세개인N56
31부산광역시부산진구262302022지역자원시설세개인Y97
32부산광역시부산진구262302022지역자원시설세법인N14
33부산광역시부산진구262302022지역자원시설세법인Y62