Overview

Dataset statistics

Number of variables8
Number of observations140
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 KiB
Average record size in memory68.9 B

Variable types

Categorical6
Numeric2

Dataset

Description지방세 세원이 되는 과세물건 유형별 부과된 현황을 표준지방세정보시스템을 활용하여 세목명, 세원 유형명, 부과건수, 부과금액을 조회 및 열람할 수 있음
Author전라남도 고흥군
URLhttps://www.data.go.kr/data/15079090/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 1 other fieldsHigh correlation
세목명 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
세원 유형명 is highly overall correlated with 부과건수 and 2 other fieldsHigh correlation
부과건수 has 29 (20.7%) zerosZeros
부과금액 has 29 (20.7%) zerosZeros

Reproduction

Analysis started2023-12-12 17:56:28.367401
Analysis finished2023-12-12 17:56:29.783141
Duration1.42 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
전라남도
140 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 140
100.0%

Length

2023-12-13T02:56:29.866866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:56:30.006607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 140
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
고흥군
140 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고흥군 140
100.0%

Length

2023-12-13T02:56:30.155523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:56:30.292715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고흥군 140
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
46770
140 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46770
2nd row46770
3rd row46770
4th row46770
5th row46770

Common Values

ValueCountFrequency (%)
46770 140
100.0%

Length

2023-12-13T02:56:30.427492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:56:30.570601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46770 140
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2019
47 
2017
47 
2018
46 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 47
33.6%
2017 47
33.6%
2018 46
32.9%

Length

2023-12-13T02:56:30.709199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:56:30.820035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 47
33.6%
2017 47
33.6%
2018 46
32.9%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
주민세
27 
취득세
27 
자동차세
21 
재산세
15 
지방소득세
12 
Other values (8)
38 

Length

Max length7
Median length3
Mean length3.6714286
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자동차세
2nd row주민세
3rd row주민세
4th row주민세
5th row주민세

Common Values

ValueCountFrequency (%)
주민세 27
19.3%
취득세 27
19.3%
자동차세 21
15.0%
재산세 15
10.7%
지방소득세 12
8.6%
레저세 12
8.6%
등록면허세 6
 
4.3%
지역자원시설세 6
 
4.3%
지방소비세 3
 
2.1%
담배소비세 3
 
2.1%
Other values (3) 8
 
5.7%

Length

2023-12-13T02:56:30.983549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주민세 27
19.3%
취득세 27
19.3%
자동차세 21
15.0%
재산세 15
10.7%
지방소득세 12
8.6%
레저세 12
8.6%
등록면허세 6
 
4.3%
지역자원시설세 6
 
4.3%
지방소비세 3
 
2.1%
담배소비세 3
 
2.1%
Other values (3) 8
 
5.7%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)33.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
승용
 
3
지방소득세(양도소득)
 
3
주민세(종업원분)
 
3
주민세(특별징수)
 
3
주민세(법인세분)
 
3
Other values (42)
125 

Length

Max length11
Median length8
Mean length6.05
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row승용
2nd row주민세(재산분)
3rd row주민세(종업원분)
4th row주민세(특별징수)
5th row주민세(법인세분)

Common Values

ValueCountFrequency (%)
승용 3
 
2.1%
지방소득세(양도소득) 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%
주민세(개인균등) 3
 
2.1%
Other values (37) 110
78.6%

Length

2023-12-13T02:56:31.120990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
승용 3
 
2.1%
주택(개별 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%
소싸움 3
 
2.1%
경정 3
 
2.1%
Other values (37) 110
78.6%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct106
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9973.6714
Minimum0
Maximum171530
Zeros29
Zeros (%)20.7%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:56:31.302246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.5
median373
Q36257.25
95-th percentile43140.3
Maximum171530
Range171530
Interquartile range (IQR)6247.75

Descriptive statistics

Standard deviation27437.535
Coefficient of variation (CV)2.7509965
Kurtosis22.050158
Mean9973.6714
Median Absolute Deviation (MAD)373
Skewness4.505314
Sum1396314
Variance7.5281833 × 108
MonotonicityNot monotonic
2023-12-13T02:56:31.495550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 29
 
20.7%
12 5
 
3.6%
2 2
 
1.4%
175 2
 
1.4%
29468 1
 
0.7%
180 1
 
0.7%
31653 1
 
0.7%
1407 1
 
0.7%
1409 1
 
0.7%
318 1
 
0.7%
Other values (96) 96
68.6%
ValueCountFrequency (%)
0 29
20.7%
1 1
 
0.7%
2 2
 
1.4%
3 1
 
0.7%
4 1
 
0.7%
5 1
 
0.7%
11 1
 
0.7%
12 5
 
3.6%
26 1
 
0.7%
27 1
 
0.7%
ValueCountFrequency (%)
171530 1
0.7%
165880 1
0.7%
161700 1
0.7%
85322 1
0.7%
83589 1
0.7%
81878 1
0.7%
43146 1
0.7%
43140 1
0.7%
32887 1
0.7%
31809 1
0.7%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct112
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.9843205 × 108
Minimum0
Maximum6.079926 × 109
Zeros29
Zeros (%)20.7%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:56:31.696967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1986000
median2.117375 × 108
Q31.039582 × 109
95-th percentile4.3343453 × 109
Maximum6.079926 × 109
Range6.079926 × 109
Interquartile range (IQR)1.038596 × 109

Descriptive statistics

Standard deviation1.426866 × 109
Coefficient of variation (CV)1.5881735
Kurtosis2.3181769
Mean8.9843205 × 108
Median Absolute Deviation (MAD)2.117375 × 108
Skewness1.8472788
Sum1.2578049 × 1011
Variance2.0359465 × 1018
MonotonicityNot monotonic
2023-12-13T02:56:31.860519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 29
 
20.7%
4149179000 1
 
0.7%
5976000 1
 
0.7%
527825000 1
 
0.7%
1330054000 1
 
0.7%
2006581000 1
 
0.7%
314882000 1
 
0.7%
70706000 1
 
0.7%
86636000 1
 
0.7%
244775000 1
 
0.7%
Other values (102) 102
72.9%
ValueCountFrequency (%)
0 29
20.7%
130000 1
 
0.7%
640000 1
 
0.7%
646000 1
 
0.7%
660000 1
 
0.7%
685000 1
 
0.7%
707000 1
 
0.7%
1079000 1
 
0.7%
1373000 1
 
0.7%
1713000 1
 
0.7%
ValueCountFrequency (%)
6079926000 1
0.7%
4832975000 1
0.7%
4808111000 1
0.7%
4682637000 1
0.7%
4539553000 1
0.7%
4500293000 1
0.7%
4406590000 1
0.7%
4330543000 1
0.7%
4324931000 1
0.7%
4311148000 1
0.7%

Interactions

2023-12-13T02:56:28.939396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:28.695799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:29.372535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:28.817788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:56:31.967850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8520.659
세원 유형명0.0001.0001.0000.9880.935
부과건수0.0000.8520.9881.0000.606
부과금액0.0000.6590.9350.6061.000
2023-12-13T02:56:32.064033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명
과세년도1.0000.0000.000
세목명0.0001.0000.856
세원 유형명0.0000.8561.000
2023-12-13T02:56:32.153580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액과세년도세목명세원 유형명
부과건수1.0000.7850.0000.6580.768
부과금액0.7851.0000.0000.3640.588
과세년도0.0000.0001.0000.0000.000
세목명0.6580.3640.0001.0000.856
세원 유형명0.7680.5880.0000.8561.000

Missing values

2023-12-13T02:56:29.557300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:56:29.724833image/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
0전라남도고흥군467702019자동차세승용294684149179000
1전라남도고흥군467702019주민세주민세(재산분)530223234000
2전라남도고흥군467702019주민세주민세(종업원분)215278395000
3전라남도고흥군467702019주민세주민세(특별징수)00
4전라남도고흥군467702019주민세주민세(법인세분)00
5전라남도고흥군467702019주민세주민세(양도소득)00
6전라남도고흥군467702019주민세주민세(종합소득)00
7전라남도고흥군467702019주민세주민세(법인균등)162492005000
8전라남도고흥군467702019주민세주민세(개인사업)188494578000
9전라남도고흥군467702019주민세주민세(개인균등)31809308481000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
130전라남도고흥군467702019재산세재산세(토지)853221949303000
131전라남도고흥군467702019재산세재산세(항공기)4646000
132전라남도고흥군467702019재산세재산세(선박)23523375000
133전라남도고흥군467702019재산세재산세(건축물)6414852104000
134전라남도고흥군467702019자동차세자동차세(주행)124311148000
135전라남도고흥군467702019자동차세3륜이하901079000
136전라남도고흥군467702019자동차세특수1756001000
137전라남도고흥군467702019자동차세화물12550339731000
138전라남도고흥군467702019자동차세승합132368953000
139전라남도고흥군467702019자동차세기타승용453412000