Overview

Dataset statistics

Number of variables8
Number of observations97
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory68.4 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description전라남도 영광군의 지방세 납세자 현황 관련 데이터로 세목별 납세 인원 현황을 제공하여 관외 납세자에 대한 부과징수 정책 수립 시 기초자료로 활용함.
Author전라남도 영광군
URLhttps://www.data.go.kr/data/15079911/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 started2023-12-12 09:04:30.365373
Analysis finished2023-12-12 09:04:31.148173
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
전라남도
97 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 97
100.0%

Length

2023-12-12T18:04:31.226225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:04:31.322988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 97
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
영광군
97 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영광군 97
100.0%

Length

2023-12-12T18:04:31.451608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:04:31.577652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영광군 97
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
46870
97 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46870
2nd row46870
3rd row46870
4th row46870
5th row46870

Common Values

ValueCountFrequency (%)
46870 97
100.0%

Length

2023-12-12T18:04:31.697392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:04:31.844445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46870 97
100.0%

과세년도
Categorical

Distinct3
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
2017
33 
2019
33 
2018
31 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2017 33
34.0%
2019 33
34.0%
2018 31
32.0%

Length

2023-12-12T18:04:31.963139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:04:32.066176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 33
34.0%
2019 33
34.0%
2018 31
32.0%

세목명
Categorical

Distinct9
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size908.0 B
등록세
12 
재산세
12 
주민세
12 
취득세
12 
자동차세
12 
Other values (4)
37 

Length

Max length7
Median length5
Mean length4.0309278
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
등록세 12
12.4%
재산세 12
12.4%
주민세 12
12.4%
취득세 12
12.4%
자동차세 12
12.4%
등록면허세 12
12.4%
지방소득세 12
12.4%
지역자원시설세 7
7.2%
담배소비세 6
6.2%

Length

2023-12-12T18:04:32.201050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:04:32.385562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록세 12
12.4%
재산세 12
12.4%
주민세 12
12.4%
취득세 12
12.4%
자동차세 12
12.4%
등록면허세 12
12.4%
지방소득세 12
12.4%
지역자원시설세 7
7.2%
담배소비세 6
6.2%

납세자유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
법인
51 
개인
46 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
법인 51
52.6%
개인 46
47.4%

Length

2023-12-12T18:04:32.587225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:04:32.711229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 51
52.6%
개인 46
47.4%

관내/관외
Boolean

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size229.0 B
True
50 
False
47 
ValueCountFrequency (%)
True 50
51.5%
False 47
48.5%
2023-12-12T18:04:32.813959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

HIGH CORRELATION 

Distinct85
Distinct (%)87.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4421.2371
Minimum1
Maximum32663
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-12T18:04:32.973465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q194
median882
Q32532
95-th percentile30204.4
Maximum32663
Range32662
Interquartile range (IQR)2438

Descriptive statistics

Standard deviation8599.505
Coefficient of variation (CV)1.945045
Kurtosis4.4127656
Mean4421.2371
Median Absolute Deviation (MAD)879
Skewness2.3639081
Sum428860
Variance73951486
MonotonicityNot monotonic
2023-12-12T18:04:33.246874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 6
 
6.2%
3 5
 
5.2%
1 4
 
4.1%
138 1
 
1.0%
952 1
 
1.0%
1998 1
 
1.0%
776 1
 
1.0%
30586 1
 
1.0%
32663 1
 
1.0%
5 1
 
1.0%
Other values (75) 75
77.3%
ValueCountFrequency (%)
1 4
4.1%
2 6
6.2%
3 5
5.2%
4 1
 
1.0%
5 1
 
1.0%
9 1
 
1.0%
12 1
 
1.0%
68 1
 
1.0%
86 1
 
1.0%
88 1
 
1.0%
ValueCountFrequency (%)
32663 1
1.0%
32291 1
1.0%
31918 1
1.0%
30586 1
1.0%
30294 1
1.0%
30182 1
1.0%
25212 1
1.0%
24062 1
1.0%
23410 1
1.0%
16299 1
1.0%

Interactions

2023-12-12T18:04:30.724908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:04:33.435651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명납세자유형관내/관외납세자수
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0000.0000.0000.705
납세자유형0.0000.0001.0000.0000.704
관내/관외0.0000.0000.0001.0000.496
납세자수0.0000.7050.7040.4961.000
2023-12-12T18:04:33.568108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명관내/관외과세년도납세자유형
세목명1.0000.0000.0000.000
관내/관외0.0001.0000.0000.000
과세년도0.0000.0001.0000.000
납세자유형0.0000.0000.0001.000
2023-12-12T18:04:33.706091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수과세년도세목명납세자유형관내/관외
납세자수1.0000.0000.4350.5070.350
과세년도0.0001.0000.0000.0000.000
세목명0.4350.0001.0000.0000.000
납세자유형0.5070.0000.0001.0000.000
관내/관외0.3500.0000.0000.0001.000

Missing values

2023-12-12T18:04:30.901452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:04:31.089108image/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
0전라남도영광군468702017등록세개인N138
1전라남도영광군468702017등록세개인Y93
2전라남도영광군468702017등록세법인N1
3전라남도영광군468702017등록세법인Y3
4전라남도영광군468702017재산세개인N31918
5전라남도영광군468702017재산세개인Y30294
6전라남도영광군468702017재산세법인N666
7전라남도영광군468702017재산세법인Y1956
8전라남도영광군468702017주민세개인N3175
9전라남도영광군468702017주민세개인Y23410
시도명시군구명자치단체코드과세년도세목명납세자유형관내/관외납세자수
87전라남도영광군468702019등록면허세개인Y10936
88전라남도영광군468702019등록면허세법인N1014
89전라남도영광군468702019등록면허세법인Y1010
90전라남도영광군468702019지방소득세개인N805
91전라남도영광군468702019지방소득세개인Y5217
92전라남도영광군468702019지방소득세법인N381
93전라남도영광군468702019지방소득세법인Y949
94전라남도영광군468702019지역자원시설세개인N1
95전라남도영광군468702019지역자원시설세개인Y9
96전라남도영광군468702019지역자원시설세법인Y3