Overview

Dataset statistics

Number of variables8
Number of observations415
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.3 KiB
Average record size in memory67.3 B

Variable types

Categorical5
Numeric2
Boolean1

Dataset

Description관외 납세자에 대한 부과징수 정책 수립시 기초자료로 활용되는 세목별 납세 인원 현황을 제공합니다.(지방세 납세자 현황)
URLhttps://www.data.go.kr/data/15080397/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 00:37:16.363997
Analysis finished2023-12-12 00:37:17.480385
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
경기도
415 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 415
100.0%

Length

2023-12-12T09:37:17.554184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:37:17.680078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 415
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
안양시만안구
209 
안양시동안구
196 
안양시
 
10

Length

Max length6
Median length6
Mean length5.9277108
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row안양시
2nd row안양시
3rd row안양시
4th row안양시
5th row안양시동안구

Common Values

ValueCountFrequency (%)
안양시만안구 209
50.4%
안양시동안구 196
47.2%
안양시 10
 
2.4%

Length

2023-12-12T09:37:17.785924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:37:17.884270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안양시만안구 209
50.4%
안양시동안구 196
47.2%
안양시 10
 
2.4%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
41171
209 
41173
196 
41170
 
10

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41170
2nd row41170
3rd row41170
4th row41170
5th row41173

Common Values

ValueCountFrequency (%)
41171 209
50.4%
41173 196
47.2%
41170 10
 
2.4%

Length

2023-12-12T09:37:17.979644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:37:18.083664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41171 209
50.4%
41173 196
47.2%
41170 10
 
2.4%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.494
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-12T09:37:18.176737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7164556
Coefficient of variation (CV)0.00084994339
Kurtosis-1.2647649
Mean2019.494
Median Absolute Deviation (MAD)2
Skewness-0.0041187323
Sum838090
Variance2.9462197
MonotonicityIncreasing
2023-12-12T09:37:18.280452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2020 73
17.6%
2017 72
17.3%
2022 70
16.9%
2019 68
16.4%
2018 66
15.9%
2021 66
15.9%
ValueCountFrequency (%)
2017 72
17.3%
2018 66
15.9%
2019 68
16.4%
2020 73
17.6%
2021 66
15.9%
2022 70
16.9%
ValueCountFrequency (%)
2022 70
16.9%
2021 66
15.9%
2020 73
17.6%
2019 68
16.4%
2018 66
15.9%
2017 72
17.3%

세목명
Categorical

Distinct11
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
지방소득세
54 
자동차세
49 
재산세
48 
주민세
48 
취득세
48 
Other values (6)
168 

Length

Max length7
Median length5
Mean length4.2216867
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row담배소비세
2nd row지방소득세
3rd row지방소득세
4th row지방소득세
5th row등록세

Common Values

ValueCountFrequency (%)
지방소득세 54
13.0%
자동차세 49
11.8%
재산세 48
11.6%
주민세 48
11.6%
취득세 48
11.6%
등록면허세 48
11.6%
지역자원시설세 48
11.6%
등록세 38
9.2%
담배소비세 28
6.7%
지방소비세 3
 
0.7%

Length

2023-12-12T09:37:18.404917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지방소득세 54
13.0%
자동차세 49
11.8%
재산세 48
11.6%
주민세 48
11.6%
취득세 48
11.6%
등록면허세 48
11.6%
지역자원시설세 48
11.6%
등록세 38
9.2%
담배소비세 28
6.7%
지방소비세 3
 
0.7%

납세자유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
법인
208 
개인
207 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
법인 208
50.1%
개인 207
49.9%

Length

2023-12-12T09:37:18.518969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:37:18.612607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 208
50.1%
개인 207
49.9%

관내_관외
Boolean

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size547.0 B
False
209 
True
206 
ValueCountFrequency (%)
False 209
50.4%
True 206
49.6%
2023-12-12T09:37:18.715988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

HIGH CORRELATION 

Distinct326
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13144.713
Minimum1
Maximum113506
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-12T09:37:18.835241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q126
median1782
Q315449
95-th percentile78366.1
Maximum113506
Range113505
Interquartile range (IQR)15423

Descriptive statistics

Standard deviation23980.502
Coefficient of variation (CV)1.8243458
Kurtosis4.5588898
Mean13144.713
Median Absolute Deviation (MAD)1778
Skewness2.3085125
Sum5455056
Variance5.750645 × 108
MonotonicityNot monotonic
2023-12-12T09:37:18.966394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 28
 
6.7%
2 6
 
1.4%
15 5
 
1.2%
18 5
 
1.2%
24 5
 
1.2%
22 5
 
1.2%
17 5
 
1.2%
3 5
 
1.2%
23 5
 
1.2%
20 4
 
1.0%
Other values (316) 342
82.4%
ValueCountFrequency (%)
1 28
6.7%
2 6
 
1.4%
3 5
 
1.2%
4 3
 
0.7%
5 1
 
0.2%
6 2
 
0.5%
8 3
 
0.7%
10 2
 
0.5%
12 3
 
0.7%
13 2
 
0.5%
ValueCountFrequency (%)
113506 1
0.2%
108978 1
0.2%
102722 1
0.2%
101855 1
0.2%
99624 1
0.2%
96742 1
0.2%
95352 1
0.2%
92862 1
0.2%
91393 1
0.2%
89418 1
0.2%

Interactions

2023-12-12T09:37:16.982883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:37:16.759503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:37:17.095833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:37:16.869875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:37:19.048679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
시군구명1.0001.0000.0670.2620.0000.0000.188
자치단체코드1.0001.0000.0670.2620.0000.0000.188
과세년도0.0670.0671.0000.0000.0000.0000.000
세목명0.2620.2620.0001.0000.0000.0000.419
납세자유형0.0000.0000.0000.0001.0000.0000.769
관내_관외0.0000.0000.0000.0000.0001.0000.405
납세자수0.1880.1880.0000.4190.7690.4051.000
2023-12-12T09:37:19.148243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자치단체코드납세자유형세목명관내_관외시군구명
자치단체코드1.0000.0000.1560.0001.000
납세자유형0.0001.0000.0000.0000.000
세목명0.1560.0001.0000.0000.156
관내_관외0.0000.0000.0001.0000.000
시군구명1.0000.0000.1560.0001.000
2023-12-12T09:37:19.243632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도납세자수시군구명자치단체코드세목명납세자유형관내_관외
과세년도1.000-0.0040.0380.0380.0000.0000.000
납세자수-0.0041.0000.1130.1130.1920.6000.308
시군구명0.0380.1131.0001.0000.1560.0000.000
자치단체코드0.0380.1131.0001.0000.1560.0000.000
세목명0.0000.1920.1560.1561.0000.0000.000
납세자유형0.0000.6000.0000.0000.0001.0000.000
관내_관외0.0000.3080.0000.0000.0000.0001.000

Missing values

2023-12-12T09:37:17.237796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:37:17.412152image/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
0경기도안양시411702017담배소비세법인N1
1경기도안양시411702017지방소득세개인Y1
2경기도안양시411702017지방소득세법인N1
3경기도안양시411702017지방소득세법인Y1
4경기도안양시동안구411732017등록세개인N33
5경기도안양시동안구411732017등록세개인Y15
6경기도안양시동안구411732017등록세법인Y2
7경기도안양시동안구411732017재산세개인N45030
8경기도안양시동안구411732017재산세개인Y75384
9경기도안양시동안구411732017재산세법인N650
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
405경기도안양시만안구411712022등록면허세법인Y2255
406경기도안양시만안구411712022지방소득세개인N13976
407경기도안양시만안구411712022지방소득세개인Y63860
408경기도안양시만안구411712022지방소득세법인N1107
409경기도안양시만안구411712022지방소득세법인Y2447
410경기도안양시만안구411712022지방소비세법인Y1
411경기도안양시만안구411712022지역자원시설세개인N24
412경기도안양시만안구411712022지역자원시설세개인Y39
413경기도안양시만안구411712022지역자원시설세법인N12
414경기도안양시만안구411712022지역자원시설세법인Y25