Overview

Dataset statistics

Number of variables9
Number of observations279
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.8 KiB
Average record size in memory76.5 B

Variable types

Categorical6
Numeric3

Dataset

Description지방세 과세를 위해 세원이 되는 과세 대상 유형별 부과된 현황을 제공(물건 유형에 따른 세부담 수준의 형평성 검토 및 부동산 등 관련분야 규제정책 대상 확인 시 기초자료 활용)
Author전라남도 담양군
URLhttps://www.data.go.kr/data/15079474/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
세원 유형명 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
부과건수 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 부과건수High correlation
부과건수 has 61 (21.9%) zerosZeros
부과금액 has 62 (22.2%) zerosZeros

Reproduction

Analysis started2023-12-12 13:04:24.646435
Analysis finished2023-12-12 13:04:25.947516
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
전라남도
279 

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 279
100.0%

Length

2023-12-12T22:04:26.009023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:04:26.116091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 279
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
담양군
279 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
담양군 279
100.0%

Length

2023-12-12T22:04:26.207138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:04:26.339492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
담양군 279
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
46710
279 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46710
2nd row46710
3rd row46710
4th row46710
5th row46710

Common Values

ValueCountFrequency (%)
46710 279
100.0%

Length

2023-12-12T22:04:26.513865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:04:26.622774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46710 279
100.0%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.4946
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T22:04:26.708676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2019
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7045664
Coefficient of variation (CV)0.00084405591
Kurtosis-1.2604133
Mean2019.4946
Median Absolute Deviation (MAD)1
Skewness0.0070616543
Sum563439
Variance2.9055465
MonotonicityIncreasing
2023-12-12T22:04:26.823866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2018 47
16.8%
2019 47
16.8%
2020 47
16.8%
2017 46
16.5%
2021 46
16.5%
2022 46
16.5%
ValueCountFrequency (%)
2017 46
16.5%
2018 47
16.8%
2019 47
16.8%
2020 47
16.8%
2021 46
16.5%
2022 46
16.5%
ValueCountFrequency (%)
2022 46
16.5%
2021 46
16.5%
2020 47
16.8%
2019 47
16.8%
2018 47
16.8%
2017 46
16.5%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
취득세
54 
주민세
50 
자동차세
42 
재산세
30 
지방소득세
24 
Other values (8)
79 

Length

Max length7
Median length3
Mean length3.7096774
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 54
19.4%
주민세 50
17.9%
자동차세 42
15.1%
재산세 30
10.8%
지방소득세 24
8.6%
레저세 24
8.6%
지역자원시설세 14
 
5.0%
등록면허세 12
 
4.3%
담배소비세 6
 
2.2%
지방소비세 6
 
2.2%
Other values (3) 17
 
6.1%

Length

2023-12-12T22:04:26.957247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 54
19.4%
주민세 50
17.9%
자동차세 42
15.1%
재산세 30
10.8%
지방소득세 24
8.6%
레저세 24
8.6%
지역자원시설세 14
 
5.0%
등록면허세 12
 
4.3%
담배소비세 6
 
2.2%
지방소비세 6
 
2.2%
Other values (3) 17
 
6.1%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
담배소비세
 
6
기타
 
6
지방소득세(법인소득)
 
6
주민세(종업원분)
 
6
지방소득세(종합소득)
 
6
Other values (45)
249 

Length

Max length11
Median length8
Mean length6.0394265
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
담배소비세 6
 
2.2%
기타 6
 
2.2%
지방소득세(법인소득) 6
 
2.2%
주민세(종업원분) 6
 
2.2%
지방소득세(종합소득) 6
 
2.2%
지방소비세 6
 
2.2%
교육세 6
 
2.2%
건축물 6
 
2.2%
재산세(주택) 6
 
2.2%
주택(단독) 6
 
2.2%
Other values (40) 219
78.5%

Length

2023-12-12T22:04:27.107769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
담배소비세 6
 
2.2%
승합 6
 
2.2%
재산세(건축물 6
 
2.2%
기타 6
 
2.2%
3륜이하 6
 
2.2%
특수 6
 
2.2%
화물 6
 
2.2%
재산세(선박 6
 
2.2%
기타승용 6
 
2.2%
승용 6
 
2.2%
Other values (40) 219
78.5%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct199
Distinct (%)71.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8375.3728
Minimum0
Maximum147742
Zeros61
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T22:04:27.256843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median420
Q36066
95-th percentile35784.1
Maximum147742
Range147742
Interquartile range (IQR)6060

Descriptive statistics

Standard deviation22592.672
Coefficient of variation (CV)2.6975124
Kurtosis23.474025
Mean8375.3728
Median Absolute Deviation (MAD)420
Skewness4.6320249
Sum2336729
Variance5.1042884 × 108
MonotonicityNot monotonic
2023-12-12T22:04:27.416600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 61
 
21.9%
12 8
 
2.9%
5 5
 
1.8%
9 4
 
1.4%
2 2
 
0.7%
6 2
 
0.7%
8 2
 
0.7%
23 2
 
0.7%
11 2
 
0.7%
1620 2
 
0.7%
Other values (189) 189
67.7%
ValueCountFrequency (%)
0 61
21.9%
1 1
 
0.4%
2 2
 
0.7%
5 5
 
1.8%
6 2
 
0.7%
7 1
 
0.4%
8 2
 
0.7%
9 4
 
1.4%
10 1
 
0.4%
11 2
 
0.7%
ValueCountFrequency (%)
147742 1
0.4%
145474 1
0.4%
143094 1
0.4%
137213 1
0.4%
134333 1
0.4%
133182 1
0.4%
63429 1
0.4%
62591 1
0.4%
60516 1
0.4%
59162 1
0.4%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct218
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4478467 × 109
Minimum0
Maximum1.8460856 × 1010
Zeros62
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T22:04:27.595943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1230000
median2.2181 × 108
Q31.9883165 × 109
95-th percentile5.8185493 × 109
Maximum1.8460856 × 1010
Range1.8460856 × 1010
Interquartile range (IQR)1.9880865 × 109

Descriptive statistics

Standard deviation2.6619196 × 109
Coefficient of variation (CV)1.8385368
Kurtosis13.595732
Mean1.4478467 × 109
Median Absolute Deviation (MAD)2.2181 × 108
Skewness3.2645533
Sum4.0394924 × 1011
Variance7.0858157 × 1018
MonotonicityNot monotonic
2023-12-12T22:04:27.821273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 62
 
22.2%
2584928000 1
 
0.4%
859333000 1
 
0.4%
81315000 1
 
0.4%
210169000 1
 
0.4%
144532000 1
 
0.4%
2017534000 1
 
0.4%
751580000 1
 
0.4%
29764000 1
 
0.4%
2054000000 1
 
0.4%
Other values (208) 208
74.6%
ValueCountFrequency (%)
0 62
22.2%
136000 1
 
0.4%
144000 1
 
0.4%
154000 1
 
0.4%
162000 1
 
0.4%
165000 1
 
0.4%
186000 1
 
0.4%
191000 1
 
0.4%
229000 1
 
0.4%
231000 1
 
0.4%
ValueCountFrequency (%)
18460856000 1
0.4%
16326601000 1
0.4%
15857844000 1
0.4%
12526534000 1
0.4%
10654939000 1
0.4%
10431301000 1
0.4%
10391833000 1
0.4%
10071405000 1
0.4%
8582452000 1
0.4%
8309677000 1
0.4%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-09-26
279 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-26
2nd row2023-09-26
3rd row2023-09-26
4th row2023-09-26
5th row2023-09-26

Common Values

ValueCountFrequency (%)
2023-09-26 279
100.0%

Length

2023-12-12T22:04:27.996072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:04:28.094060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-26 279
100.0%

Interactions

2023-12-12T22:04:25.440760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:04:24.910836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:04:25.159852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:04:25.523732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:04:24.982327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:04:25.264660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:04:25.609473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:04:25.065535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:04:25.349609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:04:28.172274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8390.531
세원 유형명0.0001.0001.0000.9660.837
부과건수0.0000.8390.9661.0000.482
부과금액0.0000.5310.8370.4821.000
2023-12-12T22:04:28.286424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세원 유형명세목명
세원 유형명1.0000.928
세목명0.9281.000
2023-12-12T22:04:28.376374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도부과건수부과금액세목명세원 유형명
과세년도1.0000.0230.0610.0000.000
부과건수0.0231.0000.7720.6090.755
부과금액0.0610.7721.0000.2580.449
세목명0.0000.6090.2581.0000.928
세원 유형명0.0000.7550.4490.9281.000

Missing values

2023-12-12T22:04:25.734627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:04:25.892559image/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 유형명부과건수부과금액데이터기준일
0전라남도담양군467102017담배소비세담배소비세10825849280002023-09-26
1전라남도담양군467102017지방소득세지방소득세(특별징수)809325162480002023-09-26
2전라남도담양군467102017지방소득세지방소득세(법인소득)131325740150002023-09-26
3전라남도담양군467102017지방소득세지방소득세(양도소득)9539021210002023-09-26
4전라남도담양군467102017지방소득세지방소득세(종합소득)28058153750002023-09-26
5전라남도담양군467102017지방소비세지방소비세002023-09-26
6전라남도담양군467102017교육세교육세13318246196930002023-09-26
7전라남도담양군467102017취득세건축물81219590990002023-09-26
8전라남도담양군467102017취득세주택(개별)148818024050002023-09-26
9전라남도담양군467102017취득세주택(단독)862231250002023-09-26
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액데이터기준일
269전라남도담양군467102022주민세주민세(특별징수)002023-09-26
270전라남도담양군467102022주민세주민세(법인세분)002023-09-26
271전라남도담양군467102022주민세주민세(양도소득)002023-09-26
272전라남도담양군467102022주민세주민세(종합소득)002023-09-26
273전라남도담양군467102022등록면허세등록면허세(면허)109171620440002023-09-26
274전라남도담양군467102022등록면허세등록면허세(등록)1440716395450002023-09-26
275전라남도담양군467102022지역자원시설세지역자원시설세(소방)117568959270002023-09-26
276전라남도담양군467102022지역자원시설세지역자원시설세(시설)002023-09-26
277전라남도담양군467102022지역자원시설세지역자원시설세(특자)206329500002023-09-26
278전라남도담양군467102022체납체납3464921183340002023-09-26