Overview

Dataset statistics

Number of variables8
Number of observations702
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory46.7 KiB
Average record size in memory68.2 B

Variable types

Categorical6
Numeric2

Dataset

Description지방세 세원이 되는 과세물건 유형별 부과된 현황 데이터로서, 과세연도, 세목명, 세원 유형명, 부과건수, 부과금액으로 목록이구성되어 있습니다
URLhttps://www.data.go.kr/data/15080590/fileData.do

Alerts

시도명 has constant value ""Constant
세목명 is highly overall correlated with 세원유형명High correlation
시군구명 is highly overall correlated with 자치단체코드High correlation
세원유형명 is highly overall correlated with 세목명High correlation
자치단체코드 is highly overall correlated with 시군구명High correlation
부과건수 is highly overall correlated with 부과금액High correlation
부과금액 is highly overall correlated with 부과건수High correlation
부과건수 has 171 (24.4%) zerosZeros
부과금액 has 171 (24.4%) zerosZeros

Reproduction

Analysis started2023-12-12 04:19:00.127138
Analysis finished2023-12-12 04:19:01.623984
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
경기도
702 

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 702
100.0%

Length

2023-12-12T13:19:01.682008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:19:01.780691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 702
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
성남시수정구
233 
성남시분당구
233 
성남시중원구
232 
성남시
 
4

Length

Max length6
Median length6
Mean length5.982906
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row성남시중원구
2nd row성남시수정구
3rd row성남시수정구
4th row성남시수정구
5th row성남시수정구

Common Values

ValueCountFrequency (%)
성남시수정구 233
33.2%
성남시분당구 233
33.2%
성남시중원구 232
33.0%
성남시 4
 
0.6%

Length

2023-12-12T13:19:01.873943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:19:01.983068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성남시수정구 233
33.2%
성남시분당구 233
33.2%
성남시중원구 232
33.0%
성남시 4
 
0.6%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
41131
233 
41135
233 
41133
232 
41130
 
4

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41133
2nd row41131
3rd row41131
4th row41131
5th row41131

Common Values

ValueCountFrequency (%)
41131 233
33.2%
41135 233
33.2%
41133 232
33.0%
41130 4
 
0.6%

Length

2023-12-12T13:19:02.117924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:19:02.234779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41131 233
33.2%
41135 233
33.2%
41133 232
33.0%
41130 4
 
0.6%

과세년도
Categorical

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2022
142 
2018
141 
2019
141 
2017
140 
2021
138 

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 (%)
2022 142
20.2%
2018 141
20.1%
2019 141
20.1%
2017 140
19.9%
2021 138
19.7%

Length

2023-12-12T13:19:02.342516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:19:02.449983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 142
20.2%
2018 141
20.1%
2019 141
20.1%
2017 140
19.9%
2021 138
19.7%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
취득세
135 
주민세
123 
자동차세
105 
재산세
75 
지방소득세
60 
Other values (8)
204 

Length

Max length7
Median length3
Mean length3.7193732
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 135
19.2%
주민세 123
17.5%
자동차세 105
15.0%
재산세 75
10.7%
지방소득세 60
8.5%
레저세 60
8.5%
지역자원시설세 36
 
5.1%
등록면허세 30
 
4.3%
지방소비세 16
 
2.3%
담배소비세 16
 
2.3%
Other values (3) 46
 
6.6%

Length

2023-12-12T13:19:02.564214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 135
19.2%
주민세 123
17.5%
자동차세 105
15.0%
재산세 75
10.7%
지방소득세 60
8.5%
레저세 60
8.5%
지역자원시설세 36
 
5.1%
등록면허세 30
 
4.3%
지방소비세 16
 
2.3%
담배소비세 16
 
2.3%
Other values (3) 46
 
6.6%

세원유형명
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
교육세
 
16
담배소비세
 
16
체납
 
16
지방소비세
 
16
건축물
 
15
Other values (45)
623 

Length

Max length11
Median length8
Mean length6.022792
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지방소득세(종합소득)
2nd row지방소득세(특별징수)
3rd row지방소득세(법인소득)
4th row지방소득세(양도소득)
5th row지방소득세(종합소득)

Common Values

ValueCountFrequency (%)
교육세 16
 
2.3%
담배소비세 16
 
2.3%
체납 16
 
2.3%
지방소비세 16
 
2.3%
건축물 15
 
2.1%
주택(개별) 15
 
2.1%
지방소득세(법인소득) 15
 
2.1%
지방소득세(양도소득) 15
 
2.1%
등록면허세(면허) 15
 
2.1%
등록면허세(등록) 15
 
2.1%
Other values (40) 548
78.1%

Length

2023-12-12T13:19:02.710488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교육세 16
 
2.3%
체납 16
 
2.3%
지방소비세 16
 
2.3%
담배소비세 16
 
2.3%
재산세(건축물 15
 
2.1%
재산세(주택 15
 
2.1%
재산세(토지 15
 
2.1%
재산세(항공기 15
 
2.1%
재산세(선박 15
 
2.1%
주민세(양도소득 15
 
2.1%
Other values (40) 548
78.1%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct482
Distinct (%)68.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37475.781
Minimum0
Maximum1036481
Zeros171
Zeros (%)24.4%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2023-12-12T13:19:02.867340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.5
median1219.5
Q320695.5
95-th percentile173957.05
Maximum1036481
Range1036481
Interquartile range (IQR)20693

Descriptive statistics

Standard deviation109632.47
Coefficient of variation (CV)2.9254219
Kurtosis44.605568
Mean37475.781
Median Absolute Deviation (MAD)1219.5
Skewness5.9495492
Sum26307998
Variance1.2019278 × 1010
MonotonicityNot monotonic
2023-12-12T13:19:03.043222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 171
 
24.4%
12 20
 
2.8%
88 4
 
0.6%
1 4
 
0.6%
42 4
 
0.6%
10 3
 
0.4%
30 3
 
0.4%
21 3
 
0.4%
7 3
 
0.4%
13 2
 
0.3%
Other values (472) 485
69.1%
ValueCountFrequency (%)
0 171
24.4%
1 4
 
0.6%
2 1
 
0.1%
4 2
 
0.3%
5 1
 
0.1%
6 2
 
0.3%
7 3
 
0.4%
9 1
 
0.1%
10 3
 
0.4%
11 1
 
0.1%
ValueCountFrequency (%)
1036481 1
0.1%
1024812 1
0.1%
1001675 1
0.1%
1001117 1
0.1%
984083 1
0.1%
445956 1
0.1%
429691 1
0.1%
415222 1
0.1%
414726 1
0.1%
411946 1
0.1%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct532
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6560168 × 1010
Minimum0
Maximum3.72624 × 1011
Zeros171
Zeros (%)24.4%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2023-12-12T13:19:03.273772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1251750
median8.25335 × 108
Q31.5334156 × 1010
95-th percentile7.8396373 × 1010
Maximum3.72624 × 1011
Range3.72624 × 1011
Interquartile range (IQR)1.5333904 × 1010

Descriptive statistics

Standard deviation3.8726075 × 1010
Coefficient of variation (CV)2.3385074
Kurtosis27.010193
Mean1.6560168 × 1010
Median Absolute Deviation (MAD)8.25335 × 108
Skewness4.5489062
Sum1.1625238 × 1013
Variance1.4997089 × 1021
MonotonicityNot monotonic
2023-12-12T13:19:03.476986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 171
 
24.4%
3921511000 1
 
0.1%
17402613000 1
 
0.1%
187802000 1
 
0.1%
588396000 1
 
0.1%
198354000000 1
 
0.1%
78410457000 1
 
0.1%
4462000 1
 
0.1%
26844150000 1
 
0.1%
17333357000 1
 
0.1%
Other values (522) 522
74.4%
ValueCountFrequency (%)
0 171
24.4%
50000 1
 
0.1%
70000 1
 
0.1%
168000 1
 
0.1%
184000 1
 
0.1%
247000 1
 
0.1%
266000 1
 
0.1%
288000 1
 
0.1%
308000 1
 
0.1%
328000 1
 
0.1%
ValueCountFrequency (%)
372624000000 1
0.1%
355122000000 1
0.1%
269311000000 1
0.1%
227502000000 1
0.1%
222825000000 1
0.1%
218408000000 1
0.1%
208090000000 1
0.1%
198354000000 1
0.1%
180080000000 1
0.1%
179178000000 1
0.1%

Interactions

2023-12-12T13:19:01.249719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:00.997549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:01.341716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:01.141110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:19:03.626474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드과세년도세목명세원유형명부과건수부과금액
시군구명1.0001.0000.0530.0780.0000.1390.311
자치단체코드1.0001.0000.0530.0780.0000.1390.311
과세년도0.0530.0531.0000.0000.0000.0000.000
세목명0.0780.0780.0001.0001.0000.7200.264
세원유형명0.0000.0000.0001.0001.0000.8170.496
부과건수0.1390.1390.0000.7200.8171.0000.478
부과금액0.3110.3110.0000.2640.4960.4781.000
2023-12-12T13:19:03.764955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명시군구명세원유형명과세년도자치단체코드
세목명1.0000.0450.9730.0000.045
시군구명0.0451.0000.0000.0431.000
세원유형명0.9730.0001.0000.0000.000
과세년도0.0000.0430.0001.0000.043
자치단체코드0.0451.0000.0000.0431.000
2023-12-12T13:19:03.940464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액시군구명자치단체코드과세년도세목명세원유형명
부과건수1.0000.7810.0900.0900.0000.4600.500
부과금액0.7811.0000.2030.2030.0000.1160.195
시군구명0.0900.2031.0001.0000.0430.0450.000
자치단체코드0.0900.2031.0001.0000.0430.0450.000
과세년도0.0000.0000.0430.0431.0000.0000.000
세목명0.4600.1160.0450.0450.0001.0000.973
세원유형명0.5000.1950.0000.0000.0000.9731.000

Missing values

2023-12-12T13:19:01.462276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:19:01.575327image/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

시도명시군구명자치단체코드과세년도세목명세원유형명부과건수부과금액
0경기도성남시중원구411332017지방소득세지방소득세(종합소득)234983921511000
1경기도성남시수정구411312017지방소득세지방소득세(특별징수)277199588859000
2경기도성남시수정구411312017지방소득세지방소득세(법인소득)19247735970000
3경기도성남시수정구411312017지방소득세지방소득세(양도소득)29476451862000
4경기도성남시수정구411312017지방소득세지방소득세(종합소득)243546685518000
5경기도성남시분당구411352017지방소비세지방소비세00
6경기도성남시중원구411332017지방소비세지방소비세00
7경기도성남시수정구411312017지방소비세지방소비세00
8경기도성남시분당구411352017도시계획세도시계획세00
9경기도성남시수정구411312017도시계획세도시계획세00
시도명시군구명자치단체코드과세년도세목명세원유형명부과건수부과금액
692경기도성남시수정구411312022지역자원시설세지역자원시설세(시설)00
693경기도성남시수정구411312022지역자원시설세지역자원시설세(특자)42660000
694경기도성남시분당구411352022담배소비세담배소비세00
695경기도성남시중원구411332022담배소비세담배소비세1266000
696경기도성남시수정구411312022담배소비세담배소비세00
697경기도성남시411302022담배소비세담배소비세64255691081000
698경기도성남시분당구411352022체납체납14885637344016000
699경기도성남시중원구411332022체납체납12160412462904000
700경기도성남시수정구411312022체납체납12445014504047000
701경기도성남시411302022체납체납00