Overview

Dataset statistics

Number of variables8
Number of observations234
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.4 KiB
Average record size in memory67.6 B

Variable types

Categorical6
Numeric1
Text1

Dataset

Description지방세 개방형 데이터 구축자료중 2017년 ~ 2021년도에 대한 경상남도 진주시 세원유형별과세현황에 대한 자료제공입니다.
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15080406

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 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 세목명 and 1 other fieldsHigh correlation
부과건수 has 57 (24.4%) zerosZeros

Reproduction

Analysis started2024-04-06 08:01:37.236421
Analysis finished2024-04-06 08:01:38.216978
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
경상남도
234 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 234
100.0%

Length

2024-04-06T17:01:38.325902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:01:38.500474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 234
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
진주시
234 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진주시 234
100.0%

Length

2024-04-06T17:01:38.662862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:01:38.823395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진주시 234
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
48170
234 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48170
2nd row48170
3rd row48170
4th row48170
5th row48170

Common Values

ValueCountFrequency (%)
48170 234
100.0%

Length

2024-04-06T17:01:38.996006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:01:39.159869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48170 234
100.0%

과세년도
Categorical

Distinct5
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2017
47 
2018
47 
2019
47 
2020
47 
2021
46 

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
20.1%
2018 47
20.1%
2019 47
20.1%
2020 47
20.1%
2021 46
19.7%

Length

2024-04-06T17:01:39.351134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:01:39.536399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 47
20.1%
2018 47
20.1%
2019 47
20.1%
2020 47
20.1%
2021 46
19.7%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
취득세
45 
주민세
43 
자동차세
35 
재산세
25 
지방소득세
20 
Other values (8)
66 

Length

Max length7
Median length3
Mean length3.7008547
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 45
19.2%
주민세 43
18.4%
자동차세 35
15.0%
재산세 25
10.7%
지방소득세 20
8.5%
레저세 20
8.5%
지역자원시설세 11
 
4.7%
등록면허세 10
 
4.3%
담배소비세 5
 
2.1%
교육세 5
 
2.1%
Other values (3) 15
 
6.4%

Length

2024-04-06T17:01:39.741743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 45
19.2%
주민세 43
18.4%
자동차세 35
15.0%
재산세 25
10.7%
지방소득세 20
8.5%
레저세 20
8.5%
지역자원시설세 11
 
4.7%
등록면허세 10
 
4.3%
담배소비세 5
 
2.1%
교육세 5
 
2.1%
Other values (3) 15
 
6.4%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
지방소득세(특별징수)
 
5
자동차세(주행)
 
5
항공기
 
5
재산세(항공기)
 
5
지방소득세(종합소득)
 
5
Other values (45)
209 

Length

Max length11
Median length8
Mean length6.0384615
Min length2

Unique

Unique3 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세(특별징수) 5
 
2.1%
자동차세(주행) 5
 
2.1%
항공기 5
 
2.1%
재산세(항공기) 5
 
2.1%
지방소득세(종합소득) 5
 
2.1%
담배소비세 5
 
2.1%
교육세 5
 
2.1%
도시계획세 5
 
2.1%
건축물 5
 
2.1%
주택(개별) 5
 
2.1%
Other values (40) 184
78.6%

Length

2024-04-06T17:01:39.981736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지방소득세(특별징수 5
 
2.1%
지방소득세(양도소득 5
 
2.1%
주민세(종업원분 5
 
2.1%
자동차세(주행 5
 
2.1%
지방소득세(법인소득 5
 
2.1%
3륜이하 5
 
2.1%
특수 5
 
2.1%
화물 5
 
2.1%
승합 5
 
2.1%
체납 5
 
2.1%
Other values (40) 184
78.6%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct173
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42907.38
Minimum0
Maximum713811
Zeros57
Zeros (%)24.4%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-06T17:01:40.215605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.75
median2157
Q332770.5
95-th percentile216005.4
Maximum713811
Range713811
Interquartile range (IQR)32766.75

Descriptive statistics

Standard deviation112384.89
Coefficient of variation (CV)2.6192437
Kurtosis22.942839
Mean42907.38
Median Absolute Deviation (MAD)2157
Skewness4.5144403
Sum10040327
Variance1.2630363 × 1010
MonotonicityNot monotonic
2024-04-06T17:01:40.534276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 57
 
24.4%
12 5
 
2.1%
49 2
 
0.9%
34069 1
 
0.4%
46 1
 
0.4%
817 1
 
0.4%
26889 1
 
0.4%
43 1
 
0.4%
6471 1
 
0.4%
135088 1
 
0.4%
Other values (163) 163
69.7%
ValueCountFrequency (%)
0 57
24.4%
1 1
 
0.4%
3 1
 
0.4%
6 1
 
0.4%
7 1
 
0.4%
12 5
 
2.1%
24 1
 
0.4%
43 1
 
0.4%
46 1
 
0.4%
49 2
 
0.9%
ValueCountFrequency (%)
713811 1
0.4%
711558 1
0.4%
702055 1
0.4%
695932 1
0.4%
669157 1
0.4%
249633 1
0.4%
245115 1
0.4%
244492 1
0.4%
236661 1
0.4%
230480 1
0.4%

부과금액
Text

Distinct176
Distinct (%)75.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-06T17:01:40.992460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.8760684
Min length2

Characters and Unicode

Total characters1843
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)74.8%

Sample

1st row17826764000
2nd row34110164000
3rd row6994793000
4th row11365918000
5th row22997391000
ValueCountFrequency (%)
17826764000 1
 
0.6%
3263000 1
 
0.6%
25229047000 1
 
0.6%
8886097000 1
 
0.6%
47739628000 1
 
0.6%
1862728000 1
 
0.6%
745306000 1
 
0.6%
27377947000 1
 
0.6%
7771000 1
 
0.6%
24668900000 1
 
0.6%
Other values (165) 165
94.3%
2024-04-06T17:01:41.666860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 629
34.1%
2 162
 
8.8%
1 153
 
8.3%
3 132
 
7.2%
7 123
 
6.7%
5 119
 
6.5%
118
 
6.4%
6 110
 
6.0%
9 103
 
5.6%
8 99
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1725
93.6%
Space Separator 118
 
6.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 629
36.5%
2 162
 
9.4%
1 153
 
8.9%
3 132
 
7.7%
7 123
 
7.1%
5 119
 
6.9%
6 110
 
6.4%
9 103
 
6.0%
8 99
 
5.7%
4 95
 
5.5%
Space Separator
ValueCountFrequency (%)
118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1843
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 629
34.1%
2 162
 
8.8%
1 153
 
8.3%
3 132
 
7.2%
7 123
 
6.7%
5 119
 
6.5%
118
 
6.4%
6 110
 
6.0%
9 103
 
5.6%
8 99
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1843
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 629
34.1%
2 162
 
8.8%
1 153
 
8.3%
3 132
 
7.2%
7 123
 
6.7%
5 119
 
6.5%
118
 
6.4%
6 110
 
6.0%
9 103
 
5.6%
8 99
 
5.4%

Interactions

2024-04-06T17:01:37.654694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:01:41.850120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수
과세년도1.0000.0000.0000.000
세목명0.0001.0001.0000.885
세원 유형명0.0001.0001.0000.998
부과건수0.0000.8850.9981.000
2024-04-06T17:01:42.029100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세원 유형명세목명과세년도
세원 유형명1.0000.9120.000
세목명0.9121.0000.000
과세년도0.0000.0001.000
2024-04-06T17:01:42.199722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수과세년도세목명세원 유형명
부과건수1.0000.0000.7250.843
과세년도0.0001.0000.0000.000
세목명0.7250.0001.0000.912
세원 유형명0.8430.0000.9121.000

Missing values

2024-04-06T17:01:37.910226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:01:38.130877image/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
0경상남도진주시481702017지방소득세지방소득세(특별징수)3159517826764000
1경상남도진주시481702017지방소득세지방소득세(법인소득)372234110164000
2경상남도진주시481702017지방소득세지방소득세(양도소득)62386994793000
3경상남도진주시481702017지방소득세지방소득세(종합소득)2820711365918000
4경상남도진주시481702017담배소비세담배소비세10722997391000
5경상남도진주시481702017교육세교육세70205533328066000
6경상남도진주시481702017도시계획세도시계획세0
7경상남도진주시481702017취득세건축물201819776786000
8경상남도진주시481702017취득세주택(개별)374118284465000
9경상남도진주시481702017취득세주택(단독)593620124139000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
224경상남도진주시481702021주민세주민세(법인세분)0
225경상남도진주시481702021주민세주민세(양도소득)0
226경상남도진주시481702021주민세주민세(종합소득)0
227경상남도진주시481702021등록면허세등록면허세(면허)42122850081000
228경상남도진주시481702021등록면허세등록면허세(등록)7190124253635000
229경상남도진주시481702021지역자원시설세지역자원시설세(소방)1651029086307000
230경상남도진주시481702021지역자원시설세지역자원시설세(시설)35104000
231경상남도진주시481702021지역자원시설세지역자원시설세(특자)1014320491000
232경상남도진주시481702021지방소비세지방소비세710585560000
233경상남도진주시481702021체납체납23048021558021000