Overview

Dataset statistics

Number of variables8
Number of observations38
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory70.5 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description2022년 12월 31일 기준 김제시 지방세 납세자 현황입니다.시도명,시군구명,자치단체코드,과세년도,세목명,납세자유형,관내/관외,납세자수를 포함하고 있습니다.
Author전북특별자치도 김제시
URLhttps://www.data.go.kr/data/15080646/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 started2024-04-29 22:47:58.035383
Analysis finished2024-04-29 22:47:59.702420
Duration1.67 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
전북특별자치도
38 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전북특별자치도 38
100.0%

Length

2024-04-30T07:47:59.765595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:47:59.856979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북특별자치도 38
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
김제시
38 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
김제시 38
100.0%

Length

2024-04-30T07:47:59.957639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:48:00.080240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김제시 38
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
45210
38 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row45210
2nd row45210
3rd row45210
4th row45210
5th row45210

Common Values

ValueCountFrequency (%)
45210 38
100.0%

Length

2024-04-30T07:48:00.191332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:48:00.289776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
45210 38
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
2022
38 

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 38
100.0%

Length

2024-04-30T07:48:00.390059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:48:00.503444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 38
100.0%

세목명
Categorical

Distinct11
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
등록세
4 
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
Other values (6)
18 

Length

Max length7
Median length5
Mean length4.1578947
Min length3

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
등록세 4
10.5%
재산세 4
10.5%
주민세 4
10.5%
취득세 4
10.5%
자동차세 4
10.5%
등록면허세 4
10.5%
지방소득세 4
10.5%
지역자원시설세 4
10.5%
담배소비세 3
7.9%
레저세 2
5.3%

Length

2024-04-30T07:48:00.625072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록세 4
10.5%
재산세 4
10.5%
주민세 4
10.5%
취득세 4
10.5%
자동차세 4
10.5%
등록면허세 4
10.5%
지방소득세 4
10.5%
지역자원시설세 4
10.5%
담배소비세 3
7.9%
레저세 2
5.3%

납세자유형
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
법인
20 
개인
18 

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 20
52.6%
개인 18
47.4%

Length

2024-04-30T07:48:00.754941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:48:00.859616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 20
52.6%
개인 18
47.4%

관내_관외
Boolean

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size170.0 B
False
20 
True
18 
ValueCountFrequency (%)
False 20
52.6%
True 18
47.4%
2024-04-30T07:48:00.947142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

Distinct36
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6034.4211
Minimum1
Maximum59167
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-04-30T07:48:01.052956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.85
Q132.25
median918.5
Q32605.5
95-th percentile37647.4
Maximum59167
Range59166
Interquartile range (IQR)2573.25

Descriptive statistics

Standard deviation13194.187
Coefficient of variation (CV)2.1864876
Kurtosis7.9127022
Mean6034.4211
Median Absolute Deviation (MAD)915.5
Skewness2.8529709
Sum229308
Variance1.7408656 × 108
MonotonicityNot monotonic
2024-04-30T07:48:01.182974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 2
 
5.3%
3 2
 
5.3%
470 1
 
2.6%
2337 1
 
2.6%
36 1
 
2.6%
2 1
 
2.6%
6018 1
 
2.6%
10673 1
 
2.6%
1241 1
 
2.6%
1873 1
 
2.6%
Other values (26) 26
68.4%
ValueCountFrequency (%)
1 2
5.3%
2 1
2.6%
3 2
5.3%
4 1
2.6%
8 1
2.6%
9 1
2.6%
15 1
2.6%
31 1
2.6%
36 1
2.6%
67 1
2.6%
ValueCountFrequency (%)
59167 1
2.6%
40636 1
2.6%
37120 1
2.6%
29129 1
2.6%
13602 1
2.6%
10673 1
2.6%
7998 1
2.6%
6018 1
2.6%
3025 1
2.6%
2695 1
2.6%

Interactions

2024-04-30T07:47:59.228723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:48:01.306839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형관내_관외납세자수
세목명1.0000.0000.0000.000
납세자유형0.0001.0000.0000.599
관내_관외0.0000.0001.0000.291
납세자수0.0000.5990.2911.000
2024-04-30T07:48:01.426274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명관내_관외납세자유형
세목명1.0000.0000.000
관내_관외0.0001.0000.000
납세자유형0.0000.0001.000
2024-04-30T07:48:01.508096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수세목명납세자유형관내_관외
납세자수1.0000.0000.4070.188
세목명0.0001.0000.0000.000
납세자유형0.4070.0001.0000.000
관내_관외0.1880.0000.0001.000

Missing values

2024-04-30T07:47:59.534174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:47:59.651681image/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
0전북특별자치도김제시452102022등록세개인N470
1전북특별자치도김제시452102022등록세개인Y516
2전북특별자치도김제시452102022등록세법인N8
3전북특별자치도김제시452102022등록세법인Y9
4전북특별자치도김제시452102022레저세개인N1
5전북특별자치도김제시452102022레저세법인N3
6전북특별자치도김제시452102022재산세개인N59167
7전북특별자치도김제시452102022재산세개인Y40636
8전북특별자치도김제시452102022재산세법인N1186
9전북특별자치도김제시452102022재산세법인Y2695
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
28전북특별자치도김제시452102022등록면허세법인Y1873
29전북특별자치도김제시452102022지방소득세개인N2337
30전북특별자치도김제시452102022지방소득세개인Y13602
31전북특별자치도김제시452102022지방소득세법인N651
32전북특별자치도김제시452102022지방소득세법인Y1879
33전북특별자치도김제시452102022지방소비세법인Y1
34전북특별자치도김제시452102022지역자원시설세개인N15
35전북특별자치도김제시452102022지역자원시설세개인Y67
36전북특별자치도김제시452102022지역자원시설세법인N4
37전북특별자치도김제시452102022지역자원시설세법인Y31