Overview

Dataset statistics

Number of variables8
Number of observations513
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.7 KiB
Average record size in memory67.3 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description세목별 납세 인원 현황에 대한 데이터로서, 과세연도, 세목명, 납세자유형(개인/법인/사업자/기타), 관내/관내, 납세자수 항목으로 구성되어 있습니다
URLhttps://www.data.go.kr/data/15080591/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 06:51:33.461642
Analysis finished2023-12-12 06:51:34.172014
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
경기도
513 

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 513
100.0%

Length

2023-12-12T15:51:34.231042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:51:34.322145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 513
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
성남시분당구
174 
성남시수정구
168 
성남시중원구
168 
성남시
 
3

Length

Max length6
Median length6
Mean length5.9824561
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성남시분당구 174
33.9%
성남시수정구 168
32.7%
성남시중원구 168
32.7%
성남시 3
 
0.6%

Length

2023-12-12T15:51:34.417076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:51:34.513923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성남시분당구 174
33.9%
성남시수정구 168
32.7%
성남시중원구 168
32.7%
성남시 3
 
0.6%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
41135
174 
41131
168 
41133
168 
41130
 
3

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41135
2nd row41135
3rd row41135
4th row41135
5th row41135

Common Values

ValueCountFrequency (%)
41135 174
33.9%
41131 168
32.7%
41133 168
32.7%
41130 3
 
0.6%

Length

2023-12-12T15:51:34.625470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:51:34.732560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41135 174
33.9%
41131 168
32.7%
41133 168
32.7%
41130 3
 
0.6%

과세년도
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2019
108 
2017
107 
2018
105 
2021
98 
2022
95 

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 (%)
2019 108
21.1%
2017 107
20.9%
2018 105
20.5%
2021 98
19.1%
2022 95
18.5%

Length

2023-12-12T15:51:34.854775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:51:34.959841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 108
21.1%
2017 107
20.9%
2018 105
20.5%
2021 98
19.1%
2022 95
18.5%

세목명
Categorical

Distinct11
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
재산세
60 
주민세
60 
취득세
60 
자동차세
60 
등록면허세
60 
Other values (6)
213 

Length

Max length7
Median length5
Mean length4.1851852
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 60
11.7%
주민세 60
11.7%
취득세 60
11.7%
자동차세 60
11.7%
등록면허세 60
11.7%
지방소득세 60
11.7%
지역자원시설세 58
11.3%
등록세 46
9.0%
담배소비세 36
7.0%
레저세 11
 
2.1%

Length

2023-12-12T15:51:35.097544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재산세 60
11.7%
주민세 60
11.7%
취득세 60
11.7%
자동차세 60
11.7%
등록면허세 60
11.7%
지방소득세 60
11.7%
지역자원시설세 58
11.3%
등록세 46
9.0%
담배소비세 36
7.0%
레저세 11
 
2.1%

납세자유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
개인
259 
법인
254 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 259
50.5%
법인 254
49.5%

Length

2023-12-12T15:51:35.234327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:51:35.346990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 259
50.5%
법인 254
49.5%

관내_관외
Boolean

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size645.0 B
False
257 
True
256 
ValueCountFrequency (%)
False 257
50.1%
True 256
49.9%
2023-12-12T15:51:35.435906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

HIGH CORRELATION 

Distinct383
Distinct (%)74.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14936.271
Minimum1
Maximum169504
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-12T15:51:35.579442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q114
median1674
Q313937
95-th percentile83464.8
Maximum169504
Range169503
Interquartile range (IQR)13923

Descriptive statistics

Standard deviation29491.003
Coefficient of variation (CV)1.9744555
Kurtosis8.907863
Mean14936.271
Median Absolute Deviation (MAD)1673
Skewness2.9191094
Sum7662307
Variance8.6971923 × 108
MonotonicityNot monotonic
2023-12-12T15:51:35.759990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 35
 
6.8%
2 14
 
2.7%
3 10
 
1.9%
13 9
 
1.8%
4 8
 
1.6%
14 8
 
1.6%
5 8
 
1.6%
12 7
 
1.4%
8 7
 
1.4%
6 7
 
1.4%
Other values (373) 400
78.0%
ValueCountFrequency (%)
1 35
6.8%
2 14
 
2.7%
3 10
 
1.9%
4 8
 
1.6%
5 8
 
1.6%
6 7
 
1.4%
7 5
 
1.0%
8 7
 
1.4%
9 4
 
0.8%
10 4
 
0.8%
ValueCountFrequency (%)
169504 1
0.2%
166250 1
0.2%
158159 1
0.2%
153253 1
0.2%
143546 1
0.2%
143210 1
0.2%
141417 1
0.2%
140639 1
0.2%
132424 1
0.2%
128895 1
0.2%

Interactions

2023-12-12T15:51:33.847090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:51:35.863429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
시군구명1.0001.0000.0400.3810.0000.0000.241
자치단체코드1.0001.0000.0400.3810.0000.0000.241
과세년도0.0400.0401.0000.0000.0000.0000.000
세목명0.3810.3810.0001.0000.0000.0000.429
납세자유형0.0000.0000.0000.0001.0000.0000.672
관내_관외0.0000.0000.0000.0000.0001.0000.368
납세자수0.2410.2410.0000.4290.6720.3681.000
2023-12-12T15:51:36.302850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관내_관외시군구명자치단체코드과세년도세목명납세자유형
관내_관외1.0000.0000.0000.0000.0000.000
시군구명0.0001.0001.0000.0320.2370.000
자치단체코드0.0001.0001.0000.0320.2370.000
과세년도0.0000.0320.0321.0000.0000.000
세목명0.0000.2370.2370.0001.0000.000
납세자유형0.0000.0000.0000.0000.0001.000
2023-12-12T15:51:36.429909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수시군구명자치단체코드과세년도세목명납세자유형관내_관외
납세자수1.0000.1450.1450.0000.1980.5190.280
시군구명0.1451.0001.0000.0320.2370.0000.000
자치단체코드0.1451.0001.0000.0320.2370.0000.000
과세년도0.0000.0320.0321.0000.0000.0000.000
세목명0.1980.2370.2370.0001.0000.0000.000
납세자유형0.5190.0000.0000.0000.0001.0000.000
관내_관외0.2800.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T15:51:33.980500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:51:34.124573image/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
0경기도성남시분당구411352017등록세개인N43
1경기도성남시분당구411352017등록세개인Y29
2경기도성남시분당구411352017등록세법인N2
3경기도성남시분당구411352017등록세법인Y3
4경기도성남시분당구411352017레저세법인N4
5경기도성남시분당구411352017재산세개인N77380
6경기도성남시분당구411352017재산세개인Y109805
7경기도성남시분당구411352017재산세법인N1072
8경기도성남시분당구411352017재산세법인Y1041
9경기도성남시분당구411352017주민세개인N51185
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
503경기도성남시중원구411332022등록면허세법인N1821
504경기도성남시중원구411332022등록면허세법인Y4166
505경기도성남시중원구411332022지방소득세개인N11620
506경기도성남시중원구411332022지방소득세개인Y57947
507경기도성남시중원구411332022지방소득세법인N1238
508경기도성남시중원구411332022지방소득세법인Y4468
509경기도성남시중원구411332022지역자원시설세개인N2
510경기도성남시중원구411332022지역자원시설세개인Y12
511경기도성남시중원구411332022지역자원시설세법인N4
512경기도성남시중원구411332022지역자원시설세법인Y6