Overview

Dataset statistics

Number of variables8
Number of observations234
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.2 KiB
Average record size in memory66.6 B

Variable types

Categorical6
Text2

Dataset

Description2017~2021년도 충청남도 보령시 지방세 세원이 되는 과세물건에 대한 데이터로 건축물, 항공기 등의 유형별로 부과된 현황을 제공합니다.
URLhttps://www.data.go.kr/data/15078789/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
세원 유형명 is highly overall correlated with 세목명High correlation
세목명 is highly overall correlated with 세원 유형명High correlation

Reproduction

Analysis started2023-12-12 22:37:52.493113
Analysis finished2023-12-12 22:37:52.918218
Duration0.43 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
충청남도
234 

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 234
100.0%

Length

2023-12-13T07:37:52.987890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:37:53.088327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 234
100.0%

시군구명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보령시 234
100.0%

Length

2023-12-13T07:37:53.194037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:37:53.284385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보령시 234
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
44180
234 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44180
2nd row44180
3rd row44180
4th row44180
5th row44180

Common Values

ValueCountFrequency (%)
44180 234
100.0%

Length

2023-12-13T07:37:53.712679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:37:53.815551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44180 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

2023-12-13T07:37:53.899655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:37:54.011621image/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 
레저세
20 
Other values (8)
66 

Length

Max length7
Median length3
Mean length3.7008547
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 45
19.2%
주민세 43
18.4%
자동차세 35
15.0%
재산세 25
10.7%
레저세 20
8.5%
지방소득세 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

2023-12-13T07:37:54.115476image/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%
레저세 20
8.5%
지방소득세 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
담배소비세
 
5
승합
 
5
선박
 
5
3륜이하
 
5
건축물
 
5
Other values (45)
209 

Length

Max length11
Median length8
Mean length6.0384615
Min length2

Unique

Unique3 ?
Unique (%)1.3%

Sample

1st row담배소비세
2nd row교육세
3rd row도시계획세
4th row건축물
5th row주택(개별)

Common Values

ValueCountFrequency (%)
담배소비세 5
 
2.1%
승합 5
 
2.1%
선박 5
 
2.1%
3륜이하 5
 
2.1%
건축물 5
 
2.1%
주택(개별) 5
 
2.1%
주택(단독) 5
 
2.1%
기타 5
 
2.1%
항공기 5
 
2.1%
재산세(건축물) 5
 
2.1%
Other values (40) 184
78.6%

Length

2023-12-13T07:37:54.252834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
담배소비세 5
 
2.1%
도시계획세 5
 
2.1%
지역자원시설세(특자 5
 
2.1%
승합 5
 
2.1%
교육세 5
 
2.1%
기타승용 5
 
2.1%
승용 5
 
2.1%
지방소비세 5
 
2.1%
등록면허세(면허 5
 
2.1%
체납 5
 
2.1%
Other values (40) 184
78.6%

부과건수
Text

Distinct175
Distinct (%)74.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-13T07:37:54.568278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.3632479
Min length1

Characters and Unicode

Total characters787
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

Unique171 ?
Unique (%)73.1%

Sample

1st row109
2nd row237516
3rd row
4th row1102
5th row1567
ValueCountFrequency (%)
0 10
 
5.3%
12 4
 
2.1%
40 2
 
1.1%
9255 1
 
0.5%
71 1
 
0.5%
14097 1
 
0.5%
109 1
 
0.5%
14603 1
 
0.5%
5775 1
 
0.5%
38116 1
 
0.5%
Other values (164) 164
87.7%
2023-12-13T07:37:55.034548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 121
15.4%
94
11.9%
2 82
10.4%
3 80
10.2%
0 73
9.3%
4 67
8.5%
7 60
7.6%
9 57
7.2%
5 54
6.9%
8 51
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 693
88.1%
Space Separator 94
 
11.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 121
17.5%
2 82
11.8%
3 80
11.5%
0 73
10.5%
4 67
9.7%
7 60
8.7%
9 57
8.2%
5 54
7.8%
8 51
7.4%
6 48
 
6.9%
Space Separator
ValueCountFrequency (%)
94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 787
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 121
15.4%
94
11.9%
2 82
10.4%
3 80
10.2%
0 73
9.3%
4 67
8.5%
7 60
7.6%
9 57
7.2%
5 54
6.9%
8 51
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 787
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 121
15.4%
94
11.9%
2 82
10.4%
3 80
10.2%
0 73
9.3%
4 67
8.5%
7 60
7.6%
9 57
7.2%
5 54
6.9%
8 51
6.5%

부과금액
Text

Distinct178
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-13T07:37:55.276730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.5940171
Min length1

Characters and Unicode

Total characters1777
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

Unique176 ?
Unique (%)75.2%

Sample

1st row8657779000
2nd row11244463000
3rd row
4th row10969346000
5th row2262291000
ValueCountFrequency (%)
0 10
 
5.4%
8350759000 1
 
0.5%
3416491000 1
 
0.5%
8657779000 1
 
0.5%
19105000 1
 
0.5%
70768000 1
 
0.5%
13102387000 1
 
0.5%
3232623000 1
 
0.5%
9587304000 1
 
0.5%
58678000 1
 
0.5%
Other values (167) 167
89.8%
2023-12-13T07:37:55.626341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 642
36.1%
1 148
 
8.3%
2 128
 
7.2%
9 117
 
6.6%
3 116
 
6.5%
6 112
 
6.3%
5 112
 
6.3%
8 110
 
6.2%
4 98
 
5.5%
7 98
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1681
94.6%
Space Separator 96
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 642
38.2%
1 148
 
8.8%
2 128
 
7.6%
9 117
 
7.0%
3 116
 
6.9%
6 112
 
6.7%
5 112
 
6.7%
8 110
 
6.5%
4 98
 
5.8%
7 98
 
5.8%
Space Separator
ValueCountFrequency (%)
96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1777
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 642
36.1%
1 148
 
8.3%
2 128
 
7.2%
9 117
 
6.6%
3 116
 
6.5%
6 112
 
6.3%
5 112
 
6.3%
8 110
 
6.2%
4 98
 
5.5%
7 98
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1777
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 642
36.1%
1 148
 
8.3%
2 128
 
7.2%
9 117
 
6.6%
3 116
 
6.5%
6 112
 
6.3%
5 112
 
6.3%
8 110
 
6.2%
4 98
 
5.5%
7 98
 
5.5%

Correlations

2023-12-13T07:37:55.721428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명
과세년도1.0000.0000.000
세목명0.0001.0001.000
세원 유형명0.0001.0001.000
2023-12-13T07:37:55.814384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세원 유형명세목명과세년도
세원 유형명1.0000.9120.000
세목명0.9121.0000.000
과세년도0.0000.0001.000
2023-12-13T07:37:55.889054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명
과세년도1.0000.0000.000
세목명0.0001.0000.912
세원 유형명0.0000.9121.000

Missing values

2023-12-13T07:37:52.739808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:37:52.869924image/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
0충청남도보령시441802017담배소비세담배소비세1098657779000
1충청남도보령시441802017교육세교육세23751611244463000
2충청남도보령시441802017도시계획세도시계획세
3충청남도보령시441802017취득세건축물110210969346000
4충청남도보령시441802017취득세주택(개별)15672262291000
5충청남도보령시441802017취득세주택(단독)21849745162000
6충청남도보령시441802017취득세기타383333409000
7충청남도보령시441802017취득세항공기
8충청남도보령시441802017취득세기계장비390494132000
9충청남도보령시441802017취득세차량83237159463000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
224충청남도보령시441802021지방소득세지방소득세(양도소득)17652367027000
225충청남도보령시441802021지방소득세지방소득세(종합소득)131702265166000
226충청남도보령시441802021주민세주민세(사업소분)6425935516000
227충청남도보령시441802021주민세주민세(개인분)43419334645000
228충청남도보령시441802021주민세주민세(종업원분)7892326228000
229충청남도보령시441802021주민세주민세(특별징수)00
230충청남도보령시441802021주민세주민세(법인세분)00
231충청남도보령시441802021주민세주민세(양도소득)00
232충청남도보령시441802021주민세주민세(종합소득)00
233충청남도보령시441802021체납체납742945210469000