Overview

Dataset statistics

Number of variables9
Number of observations233
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.4 KiB
Average record size in memory76.6 B

Variable types

Categorical7
Numeric2

Dataset

Description강원특별자치도 춘천시의 연도별 세목 및 세원별 부과내역으로 시도명, 시군구명, 자치단체코드, 과세년도, 세목명, 세원 유형명, 부과건수, 부과금액, 데이터기준일에 대한 자료
Author강원특별자치도 춘천시
URLhttps://www.data.go.kr/data/15079762/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
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 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
부과건수 has 56 (24.0%) zerosZeros
부과금액 has 56 (24.0%) zerosZeros

Reproduction

Analysis started2023-12-12 02:20:23.346554
Analysis finished2023-12-12 02:20:24.406941
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
강원특별자치도
233 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원특별자치도 233
100.0%

Length

2023-12-12T11:20:24.471295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:20:24.587639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원특별자치도 233
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
춘천시
233 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
춘천시 233
100.0%

Length

2023-12-12T11:20:24.689184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:20:24.813021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
춘천시 233
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
51110
233 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row51110
2nd row51110
3rd row51110
4th row51110
5th row51110

Common Values

ValueCountFrequency (%)
51110 233
100.0%

Length

2023-12-12T11:20:24.937902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:20:25.066795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
51110 233
100.0%

과세년도
Categorical

Distinct5
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2018
47 
2019
47 
2020
47 
2021
46 
2022
46 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 47
20.2%
2019 47
20.2%
2020 47
20.2%
2021 46
19.7%
2022 46
19.7%

Length

2023-12-12T11:20:25.197599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:20:25.332144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 47
20.2%
2019 47
20.2%
2020 47
20.2%
2021 46
19.7%
2022 46
19.7%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
취득세
45 
주민세
41 
자동차세
35 
재산세
25 
지방소득세
20 
Other values (8)
67 

Length

Max length7
Median length3
Mean length3.72103
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 45
19.3%
주민세 41
17.6%
자동차세 35
15.0%
재산세 25
10.7%
지방소득세 20
8.6%
레저세 20
8.6%
지역자원시설세 12
 
5.2%
등록면허세 10
 
4.3%
교육세 5
 
2.1%
도시계획세 5
 
2.1%
Other values (3) 15
 
6.4%

Length

2023-12-12T11:20:25.496130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 45
19.3%
주민세 41
17.6%
자동차세 35
15.0%
재산세 25
10.7%
지방소득세 20
8.6%
레저세 20
8.6%
지역자원시설세 12
 
5.2%
등록면허세 10
 
4.3%
교육세 5
 
2.1%
도시계획세 5
 
2.1%
Other values (3) 15
 
6.4%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
교육세
 
5
주민세(특별징수)
 
5
기타
 
5
승용
 
5
차량
 
5
Other values (45)
208 

Length

Max length11
Median length8
Mean length6.0343348
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교육세 5
 
2.1%
주민세(특별징수) 5
 
2.1%
기타 5
 
2.1%
승용 5
 
2.1%
차량 5
 
2.1%
선박 5
 
2.1%
토지 5
 
2.1%
재산세(주택) 5
 
2.1%
기타승용 5
 
2.1%
재산세(항공기) 5
 
2.1%
Other values (40) 183
78.5%

Length

2023-12-12T11:20:25.667837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교육세 5
 
2.1%
기계장비 5
 
2.1%
지방소비세 5
 
2.1%
주민세(특별징수 5
 
2.1%
주민세(법인세분 5
 
2.1%
주민세(양도소득 5
 
2.1%
주민세(종합소득 5
 
2.1%
지방소득세(특별징수 5
 
2.1%
지방소득세(법인소득 5
 
2.1%
체납 5
 
2.1%
Other values (40) 183
78.5%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct172
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37030.717
Minimum0
Maximum603510
Zeros56
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T11:20:25.835927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median2115
Q324515
95-th percentile180622.2
Maximum603510
Range603510
Interquartile range (IQR)24506

Descriptive statistics

Standard deviation94339.003
Coefficient of variation (CV)2.5475878
Kurtosis21.905028
Mean37030.717
Median Absolute Deviation (MAD)2115
Skewness4.4065649
Sum8628157
Variance8.8998475 × 109
MonotonicityNot monotonic
2023-12-12T11:20:26.027316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 56
 
24.0%
12 6
 
2.6%
11 2
 
0.9%
1135 1
 
0.4%
104 1
 
0.4%
8660 1
 
0.4%
106518 1
 
0.4%
101382 1
 
0.4%
665 1
 
0.4%
27131 1
 
0.4%
Other values (162) 162
69.5%
ValueCountFrequency (%)
0 56
24.0%
6 1
 
0.4%
7 1
 
0.4%
9 1
 
0.4%
11 2
 
0.9%
12 6
 
2.6%
34 1
 
0.4%
63 1
 
0.4%
68 1
 
0.4%
78 1
 
0.4%
ValueCountFrequency (%)
603510 1
0.4%
594645 1
0.4%
581646 1
0.4%
562065 1
0.4%
557424 1
0.4%
267212 1
0.4%
253036 1
0.4%
204049 1
0.4%
192734 1
0.4%
186869 1
0.4%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct178
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.0569179 × 109
Minimum0
Maximum4.4469202 × 1010
Zeros56
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T11:20:26.196312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19204000
median1.054168 × 109
Q31.5234998 × 1010
95-th percentile3.1366148 × 1010
Maximum4.4469202 × 1010
Range4.4469202 × 1010
Interquartile range (IQR)1.5225794 × 1010

Descriptive statistics

Standard deviation1.1035047 × 1010
Coefficient of variation (CV)1.3696363
Kurtosis0.48861202
Mean8.0569179 × 109
Median Absolute Deviation (MAD)1.054168 × 109
Skewness1.2857503
Sum1.8772619 × 1012
Variance1.2177227 × 1020
MonotonicityNot monotonic
2023-12-12T11:20:26.346869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 56
 
24.0%
25916286000 1
 
0.4%
39951943000 1
 
0.4%
16054899000 1
 
0.4%
28895033000 1
 
0.4%
9322000 1
 
0.4%
7282590000 1
 
0.4%
23022106000 1
 
0.4%
15096000 1
 
0.4%
37962000 1
 
0.4%
Other values (168) 168
72.1%
ValueCountFrequency (%)
0 56
24.0%
8646000 1
 
0.4%
9040000 1
 
0.4%
9204000 1
 
0.4%
9322000 1
 
0.4%
9361000 1
 
0.4%
9729000 1
 
0.4%
10306000 1
 
0.4%
10797000 1
 
0.4%
11813000 1
 
0.4%
ValueCountFrequency (%)
44469202000 1
0.4%
39951943000 1
0.4%
38651605000 1
0.4%
35977947000 1
0.4%
35913323000 1
0.4%
35511802000 1
0.4%
35031797000 1
0.4%
34936200000 1
0.4%
34833856000 1
0.4%
34139193000 1
0.4%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-11-08
233 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-08
2nd row2023-11-08
3rd row2023-11-08
4th row2023-11-08
5th row2023-11-08

Common Values

ValueCountFrequency (%)
2023-11-08 233
100.0%

Length

2023-12-12T11:20:26.486794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:20:26.593927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-08 233
100.0%

Interactions

2023-12-12T11:20:23.906861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:23.642793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:24.005659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:23.766712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:20:26.669849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8440.675
세원 유형명0.0001.0001.0000.9470.919
부과건수0.0000.8440.9471.0000.605
부과금액0.0000.6750.9190.6051.000
2023-12-12T11:20:26.795942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명
과세년도1.0000.0000.000
세목명0.0001.0000.912
세원 유형명0.0000.9121.000
2023-12-12T11:20:27.203861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액과세년도세목명세원 유형명
부과건수1.0000.7440.0000.6160.685
부과금액0.7441.0000.0000.3560.534
과세년도0.0000.0001.0000.0000.000
세목명0.6160.3560.0001.0000.912
세원 유형명0.6850.5340.0000.9121.000

Missing values

2023-12-12T11:20:24.159056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:20:24.344349image/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
0강원특별자치도춘천시511102018교육세교육세557424280945480002023-11-08
1강원특별자치도춘천시511102018도시계획세도시계획세002023-11-08
2강원특별자치도춘천시511102018취득세건축물211584865950002023-11-08
3강원특별자치도춘천시511102018취득세주택(개별)2579104642100002023-11-08
4강원특별자치도춘천시511102018취득세주택(단독)5028165184870002023-11-08
5강원특별자치도춘천시511102018취득세기타19325447530002023-11-08
6강원특별자치도춘천시511102018취득세항공기002023-11-08
7강원특별자치도춘천시511102018취득세기계장비6479492850002023-11-08
8강원특별자치도춘천시511102018취득세차량20323201954860002023-11-08
9강원특별자치도춘천시511102018취득세선박6390400002023-11-08
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액데이터기준일
223강원특별자치도춘천시511102022등록면허세등록면허세(등록)5753267501240002023-11-08
224강원특별자치도춘천시511102022지역자원시설세지역자원시설세(소방)13406257159560002023-11-08
225강원특별자치도춘천시511102022지역자원시설세지역자원시설세(시설)127206330002023-11-08
226강원특별자치도춘천시511102022지역자원시설세지역자원시설세(특자)236826627520002023-11-08
227강원특별자치도춘천시511102022레저세소싸움002023-11-08
228강원특별자치도춘천시511102022레저세경정11436950002023-11-08
229강원특별자치도춘천시511102022레저세경륜341101790002023-11-08
230강원특별자치도춘천시511102022레저세경마002023-11-08
231강원특별자치도춘천시511102022담배소비세담배소비세655198578010002023-11-08
232강원특별자치도춘천시511102022체납체납192734164890080002023-11-08