Overview

Dataset statistics

Number of variables9
Number of observations139
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.4 KiB
Average record size in memory76.9 B

Variable types

Categorical6
Numeric2
DateTime1

Dataset

Description상기 데이터는 연도별 지방세 과세를 위해 세원이 되는 과세 대상 유형별 부과된 현황을 제공하는 것으로 물건 유형에 따른 세부담 수준의 형평성 검토 및 부동산 등 관련분야 규제정책 대상 확인 시 기초자료로 활용
Author충청남도 부여군
URLhttps://www.data.go.kr/data/15080010/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일자 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 30 (21.6%) zerosZeros
부과금액 has 30 (21.6%) zerosZeros

Reproduction

Analysis started2023-12-11 23:05:23.196893
Analysis finished2023-12-11 23:05:24.107251
Duration0.91 seconds
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
충청남도
139 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 139
100.0%

Length

2023-12-12T08:05:24.206806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:05:24.324858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 139
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
부여군
139 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부여군 139
100.0%

Length

2023-12-12T08:05:24.450602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:05:24.583961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부여군 139
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
44760
139 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44760
2nd row44760
3rd row44760
4th row44760
5th row44760

Common Values

ValueCountFrequency (%)
44760 139
100.0%

Length

2023-12-12T08:05:24.680411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:05:24.766940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44760 139
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2020
47 
2021
46 
2022
46 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 47
33.8%
2021 46
33.1%
2022 46
33.1%

Length

2023-12-12T08:05:24.870567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:05:24.984271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 47
33.8%
2021 46
33.1%
2022 46
33.1%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
취득세
27 
주민세
23 
자동차세
21 
재산세
15 
지방소득세
12 
Other values (8)
41 

Length

Max length7
Median length3
Mean length3.7482014
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 27
19.4%
주민세 23
16.5%
자동차세 21
15.1%
재산세 15
10.8%
지방소득세 12
8.6%
레저세 12
8.6%
지역자원시설세 8
 
5.8%
등록면허세 6
 
4.3%
교육세 3
 
2.2%
도시계획세 3
 
2.2%
Other values (3) 9
 
6.5%

Length

2023-12-12T08:05:25.118276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 27
19.4%
주민세 23
16.5%
자동차세 21
15.1%
재산세 15
10.8%
지방소득세 12
8.6%
레저세 12
8.6%
지역자원시설세 8
 
5.8%
등록면허세 6
 
4.3%
교육세 3
 
2.2%
도시계획세 3
 
2.2%
Other values (3) 9
 
6.5%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
지방소득세(특별징수)
 
3
3륜이하
 
3
항공기
 
3
재산세(선박)
 
3
지방소득세(종합소득)
 
3
Other values (45)
124 

Length

Max length11
Median length8
Mean length6.028777
Min length2

Unique

Unique4 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세(특별징수) 3
 
2.2%
3륜이하 3
 
2.2%
항공기 3
 
2.2%
재산세(선박) 3
 
2.2%
지방소득세(종합소득) 3
 
2.2%
교육세 3
 
2.2%
도시계획세 3
 
2.2%
건축물 3
 
2.2%
주택(개별) 3
 
2.2%
재산세(토지) 3
 
2.2%
Other values (40) 109
78.4%

Length

2023-12-12T08:05:25.261980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지방소득세(특별징수 3
 
2.2%
지방소득세(양도소득 3
 
2.2%
등록면허세(등록 3
 
2.2%
3륜이하 3
 
2.2%
지방소득세(법인소득 3
 
2.2%
특수 3
 
2.2%
화물 3
 
2.2%
승합 3
 
2.2%
기타승용 3
 
2.2%
체납 3
 
2.2%
Other values (40) 109
78.4%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct102
Distinct (%)73.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10217.77
Minimum0
Maximum171653
Zeros30
Zeros (%)21.6%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T08:05:25.399155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median384
Q37037.5
95-th percentile38586.4
Maximum171653
Range171653
Interquartile range (IQR)7029.5

Descriptive statistics

Standard deviation27493.205
Coefficient of variation (CV)2.6907246
Kurtosis24.10638
Mean10217.77
Median Absolute Deviation (MAD)384
Skewness4.671444
Sum1420270
Variance7.5587631 × 108
MonotonicityNot monotonic
2023-12-12T08:05:25.533181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30
 
21.6%
2 3
 
2.2%
12 3
 
2.2%
36 3
 
2.2%
636 2
 
1.4%
1225 2
 
1.4%
9029 1
 
0.7%
329 1
 
0.7%
1528 1
 
0.7%
625 1
 
0.7%
Other values (92) 92
66.2%
ValueCountFrequency (%)
0 30
21.6%
2 3
 
2.2%
6 1
 
0.7%
7 1
 
0.7%
9 1
 
0.7%
11 1
 
0.7%
12 3
 
2.2%
14 1
 
0.7%
16 1
 
0.7%
17 1
 
0.7%
ValueCountFrequency (%)
171653 1
0.7%
171442 1
0.7%
169969 1
0.7%
71465 1
0.7%
70961 1
0.7%
69836 1
0.7%
41461 1
0.7%
38267 1
0.7%
38238 1
0.7%
35528 1
0.7%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct108
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5089822 × 109
Minimum0
Maximum1.2586534 × 1010
Zeros30
Zeros (%)21.6%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T08:05:25.693652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11812500
median3.53097 × 108
Q31.840323 × 109
95-th percentile5.8035445 × 109
Maximum1.2586534 × 1010
Range1.2586534 × 1010
Interquartile range (IQR)1.8385105 × 109

Descriptive statistics

Standard deviation2.2895289 × 109
Coefficient of variation (CV)1.5172671
Kurtosis3.9702535
Mean1.5089822 × 109
Median Absolute Deviation (MAD)3.53097 × 108
Skewness1.9151454
Sum2.0974852 × 1011
Variance5.2419427 × 1018
MonotonicityNot monotonic
2023-12-12T08:05:25.896701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30
 
21.6%
15000 3
 
2.2%
3371860000 1
 
0.7%
575675000 1
 
0.7%
362431000 1
 
0.7%
542135000 1
 
0.7%
1334098000 1
 
0.7%
2949392000 1
 
0.7%
5716731000 1
 
0.7%
884710000 1
 
0.7%
Other values (98) 98
70.5%
ValueCountFrequency (%)
0 30
21.6%
15000 3
 
2.2%
949000 1
 
0.7%
1601000 1
 
0.7%
2024000 1
 
0.7%
2763000 1
 
0.7%
3320000 1
 
0.7%
3514000 1
 
0.7%
3876000 1
 
0.7%
7058000 1
 
0.7%
ValueCountFrequency (%)
12586534000 1
0.7%
8238544000 1
0.7%
8237900000 1
0.7%
7244352000 1
0.7%
7133482000 1
0.7%
6901766000 1
0.7%
6081766000 1
0.7%
5772631000 1
0.7%
5737601000 1
0.7%
5716731000 1
0.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2023-09-30 00:00:00
Maximum2023-09-30 00:00:00
2023-12-12T08:05:26.040529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:05:26.156314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T08:05:23.672965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:05:23.482715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:05:23.766898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:05:23.578542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:05:26.227298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8310.789
세원 유형명0.0001.0001.0001.0000.907
부과건수0.0000.8311.0001.0000.573
부과금액0.0000.7890.9070.5731.000
2023-12-12T08:05:26.374753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명세원 유형명과세년도
세목명1.0000.8400.000
세원 유형명0.8401.0000.000
과세년도0.0000.0001.000
2023-12-12T08:05:26.471823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액과세년도세목명세원 유형명
부과건수1.0000.7280.0000.6250.815
부과금액0.7281.0000.0000.5040.520
과세년도0.0000.0001.0000.0000.000
세목명0.6250.5040.0001.0000.840
세원 유형명0.8150.5200.0000.8401.000

Missing values

2023-12-12T08:05:23.897036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:05:24.041607image/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 유형명부과건수부과금액데이터기준일자
0충청남도부여군447602020지방소득세지방소득세(특별징수)902933718600002023-09-30
1충청남도부여군447602020지방소득세지방소득세(법인소득)128439569530002023-09-30
2충청남도부여군447602020지방소득세지방소득세(양도소득)10047281480002023-09-30
3충청남도부여군447602020지방소득세지방소득세(종합소득)51058024320002023-09-30
4충청남도부여군447602020교육세교육세17165357726310002023-09-30
5충청남도부여군447602020도시계획세도시계획세002023-09-30
6충청남도부여군447602020취득세건축물72825613370002023-09-30
7충청남도부여군447602020취득세주택(개별)181318210660002023-09-30
8충청남도부여군447602020취득세주택(단독)5078054270002023-09-30
9충청남도부여군447602020취득세기타1151718060002023-09-30
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액데이터기준일자
129충청남도부여군447602022지방소비세지방소비세9125865340002023-09-30
130충청남도부여군447602022담배소비세담배소비세63646151900002023-09-30
131충청남도부여군447602022주민세주민세(사업소분)38384744990002023-09-30
132충청남도부여군447602022주민세주민세(개인분)298022982600002023-09-30
133충청남도부여군447602022주민세주민세(종업원분)3386345360002023-09-30
134충청남도부여군447602022주민세주민세(특별징수)002023-09-30
135충청남도부여군447602022주민세주민세(법인세분)002023-09-30
136충청남도부여군447602022주민세주민세(양도소득)002023-09-30
137충청남도부여군447602022주민세주민세(종합소득)002023-09-30
138충청남도부여군447602022체납체납4146123734330002023-09-30