Overview

Dataset statistics

Number of variables8
Number of observations141
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory68.9 B

Variable types

Categorical6
Numeric2

Dataset

Description지방세 과세를 위해 세원이 되는 과세 대상 유형별 부과된 현황을 제공함으로써 물건 유형에 따른 세부담 수준의 형평성 검토 및 부동산 등 관련분야 규제정책 대상 확인 시 기초자료로 활용할 수 있도록 함.
Author경기도 포천시
URLhttps://www.data.go.kr/data/15080055/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
부과건수 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 부과건수 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 부과건수 and 2 other fieldsHigh correlation
세원 유형명 is highly overall correlated with 부과건수 and 2 other fieldsHigh correlation
부과건수 has 36 (25.5%) zerosZeros
부과금액 has 36 (25.5%) zerosZeros

Reproduction

Analysis started2023-12-12 02:06:11.221628
Analysis finished2023-12-12 02:06:12.288007
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
경기도
141 

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 141
100.0%

Length

2023-12-12T11:06:12.379548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:06:12.504637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 141
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
포천시
141 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
포천시 141
100.0%

Length

2023-12-12T11:06:12.610844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:06:12.716046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
포천시 141
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
41650
141 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41650
2nd row41650
3rd row41650
4th row41650
5th row41650

Common Values

ValueCountFrequency (%)
41650 141
100.0%

Length

2023-12-12T11:06:12.822519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:06:12.953893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41650 141
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2017
47 
2018
47 
2019
47 

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 47
33.3%
2018 47
33.3%
2019 47
33.3%

Length

2023-12-12T11:06:13.084405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:06:13.217942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 47
33.3%
2018 47
33.3%
2019 47
33.3%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
취득세
27 
주민세
27 
자동차세
21 
재산세
15 
레저세
12 
Other values (8)
39 

Length

Max length7
Median length3
Mean length3.6808511
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row교육세
2nd row취득세
3rd row취득세
4th row취득세
5th row취득세

Common Values

ValueCountFrequency (%)
취득세 27
19.1%
주민세 27
19.1%
자동차세 21
14.9%
재산세 15
10.6%
레저세 12
8.5%
지방소득세 12
8.5%
등록면허세 6
 
4.3%
지역자원시설세 6
 
4.3%
교육세 3
 
2.1%
지방소비세 3
 
2.1%
Other values (3) 9
 
6.4%

Length

2023-12-12T11:06:13.356226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 27
19.1%
주민세 27
19.1%
자동차세 21
14.9%
재산세 15
10.6%
레저세 12
8.5%
지방소득세 12
8.5%
등록면허세 6
 
4.3%
지역자원시설세 6
 
4.3%
교육세 3
 
2.1%
지방소비세 3
 
2.1%
Other values (3) 9
 
6.4%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
교육세
 
3
경륜
 
3
주택(개별)
 
3
주택(단독)
 
3
기타
 
3
Other values (42)
126 

Length

Max length11
Median length8
Mean length6.0425532
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row교육세
2nd row건축물
3rd row주택(개별)
4th row주택(단독)
5th row기타

Common Values

ValueCountFrequency (%)
교육세 3
 
2.1%
경륜 3
 
2.1%
주택(개별) 3
 
2.1%
주택(단독) 3
 
2.1%
기타 3
 
2.1%
항공기 3
 
2.1%
기계장비 3
 
2.1%
차량 3
 
2.1%
선박 3
 
2.1%
토지 3
 
2.1%
Other values (37) 111
78.7%

Length

2023-12-12T11:06:13.487755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교육세 3
 
2.1%
기타승용 3
 
2.1%
주민세(재산분 3
 
2.1%
주민세(종업원분 3
 
2.1%
주민세(특별징수 3
 
2.1%
주민세(법인세분 3
 
2.1%
주민세(양도소득 3
 
2.1%
주민세(종합소득 3
 
2.1%
주민세(법인균등 3
 
2.1%
주민세(개인사업 3
 
2.1%
Other values (37) 111
78.7%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct104
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26631.943
Minimum0
Maximum365786
Zeros36
Zeros (%)25.5%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T11:06:13.630343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1653
Q322682
95-th percentile102569
Maximum365786
Range365786
Interquartile range (IQR)22682

Descriptive statistics

Standard deviation66462.365
Coefficient of variation (CV)2.4955883
Kurtosis15.503305
Mean26631.943
Median Absolute Deviation (MAD)1653
Skewness3.8781657
Sum3755104
Variance4.417246 × 109
MonotonicityNot monotonic
2023-12-12T11:06:13.823014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36
 
25.5%
12 3
 
2.1%
353480 1
 
0.7%
22 1
 
0.7%
14979 1
 
0.7%
693 1
 
0.7%
365 1
 
0.7%
1591 1
 
0.7%
1530 1
 
0.7%
2985 1
 
0.7%
Other values (94) 94
66.7%
ValueCountFrequency (%)
0 36
25.5%
3 1
 
0.7%
6 1
 
0.7%
12 3
 
2.1%
18 1
 
0.7%
19 1
 
0.7%
21 1
 
0.7%
22 1
 
0.7%
51 1
 
0.7%
69 1
 
0.7%
ValueCountFrequency (%)
365786 1
0.7%
362826 1
0.7%
353480 1
0.7%
277213 1
0.7%
272405 1
0.7%
268293 1
0.7%
102928 1
0.7%
102569 1
0.7%
101077 1
0.7%
80886 1
0.7%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct106
Distinct (%)75.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8499053 × 109
Minimum0
Maximum3.8801698 × 1010
Zeros36
Zeros (%)25.5%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T11:06:14.005225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.091432 × 109
Q37.383515 × 109
95-th percentile2.5247373 × 1010
Maximum3.8801698 × 1010
Range3.8801698 × 1010
Interquartile range (IQR)7.383515 × 109

Descriptive statistics

Standard deviation8.8866447 × 109
Coefficient of variation (CV)1.5191092
Kurtosis2.9719922
Mean5.8499053 × 109
Median Absolute Deviation (MAD)1.091432 × 109
Skewness1.844688
Sum8.2483665 × 1011
Variance7.8972455 × 1019
MonotonicityNot monotonic
2023-12-12T11:06:14.183386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36
 
25.5%
24754953000 1
 
0.7%
7936494000 1
 
0.7%
3236000 1
 
0.7%
15038568000 1
 
0.7%
1091432000 1
 
0.7%
1241346000 1
 
0.7%
2648512000 1
 
0.7%
3279086000 1
 
0.7%
13155848000 1
 
0.7%
Other values (96) 96
68.1%
ValueCountFrequency (%)
0 36
25.5%
217000 1
 
0.7%
277000 1
 
0.7%
762000 1
 
0.7%
1301000 1
 
0.7%
1342000 1
 
0.7%
2251000 1
 
0.7%
3236000 1
 
0.7%
3492000 1
 
0.7%
3807000 1
 
0.7%
ValueCountFrequency (%)
38801698000 1
0.7%
37785109000 1
0.7%
37489742000 1
0.7%
30572089000 1
0.7%
28400658000 1
0.7%
27051624000 1
0.7%
26221279000 1
0.7%
25247373000 1
0.7%
25038676000 1
0.7%
24754953000 1
0.7%

Interactions

2023-12-12T11:06:11.734670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:06:11.511461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:06:11.877858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:06:11.616735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:06:14.320716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8920.828
세원 유형명0.0001.0001.0000.9980.964
부과건수0.0000.8920.9981.0000.822
부과금액0.0000.8280.9640.8221.000
2023-12-12T11:06:14.438952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세원 유형명세목명
과세년도1.0000.0000.000
세원 유형명0.0001.0000.857
세목명0.0000.8571.000
2023-12-12T11:06:14.545295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액과세년도세목명세원 유형명
부과건수1.0000.7630.0000.7300.824
부과금액0.7631.0000.0000.5410.665
과세년도0.0000.0001.0000.0000.000
세목명0.7300.5410.0001.0000.857
세원 유형명0.8240.6650.0000.8571.000

Missing values

2023-12-12T11:06:12.050930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:06:12.226879image/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

시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
0경기도포천시416502017교육세교육세35348024754953000
1경기도포천시416502017취득세건축물291112837955000
2경기도포천시416502017취득세주택(개별)16533910708000
3경기도포천시416502017취득세주택(단독)24266427765000
4경기도포천시416502017취득세기타4854094688000
5경기도포천시416502017취득세항공기00
6경기도포천시416502017취득세기계장비8771186840000
7경기도포천시416502017취득세차량1480914437240000
8경기도포천시416502017취득세선박61301000
9경기도포천시416502017취득세토지819538801698000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
131경기도포천시416502019지방소득세지방소득세(양도소득)20455142485000
132경기도포천시416502019지방소득세지방소득세(종합소득)170685065798000
133경기도포천시416502019지방소비세지방소비세00
134경기도포천시416502019도시계획세도시계획세00
135경기도포천시416502019담배소비세담배소비세8417584177000
136경기도포천시416502019등록면허세등록면허세(면허)37944611398000
137경기도포천시416502019등록면허세등록면허세(등록)549127383515000
138경기도포천시416502019지역자원시설세지역자원시설세(소방)682735379891000
139경기도포천시416502019지역자원시설세지역자원시설세(특자)7972597818000
140경기도포천시416502019체납체납27240521431582000