Overview

Dataset statistics

Number of variables10
Number of observations241
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.1 KiB
Average record size in memory85.5 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description신용카드,가상계좌 등 지방세 납부매체별 납부 현황자료로서 전자송달 시장 규모 및 편익 분석, 수수료 산정시 기초자료 활용된다.
Author강원도 화천군
URLhttps://www.data.go.kr/data/15080135/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
납부매체 is highly overall correlated with 납부매체전자고지여부High correlation
납부매체전자고지여부 is highly overall correlated with 납부매체High correlation
납부건수 is highly overall correlated with 납부금액 and 1 other fieldsHigh correlation
납부금액 is highly overall correlated with 납부건수 and 1 other fieldsHigh correlation
납부매체비율 is highly overall correlated with 납부건수 and 1 other fieldsHigh correlation
납부매체비율 has 5 (2.1%) zerosZeros

Reproduction

Analysis started2023-12-12 07:28:18.625694
Analysis finished2023-12-12 07:28:20.065169
Duration1.44 second
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
강원도
241 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원도 241
100.0%

Length

2023-12-12T16:28:20.143970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:28:20.244977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 241
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
화천군
241 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
화천군 241
100.0%

Length

2023-12-12T16:28:20.582814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:28:20.669683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화천군 241
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
42790
241 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row42790
2nd row42790
3rd row42790
4th row42790
5th row42790

Common Values

ValueCountFrequency (%)
42790 241
100.0%

Length

2023-12-12T16:28:20.756651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:28:20.862927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
42790 241
100.0%

납부년도
Categorical

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2020
65 
2019
62 
2017
57 
2018
57 

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 (%)
2020 65
27.0%
2019 62
25.7%
2017 57
23.7%
2018 57
23.7%

Length

2023-12-12T16:28:20.946423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:28:21.038570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 65
27.0%
2019 62
25.7%
2017 57
23.7%
2018 57
23.7%

세목명
Categorical

Distinct12
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
자동차세
34 
재산세
34 
주민세
34 
등록면허세
33 
지방소득세
29 
Other values (7)
77 

Length

Max length7
Median length3
Mean length3.8962656
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row등록면허세
2nd row등록세
3rd row면허세
4th row자동차세
5th row재산세

Common Values

ValueCountFrequency (%)
자동차세 34
14.1%
재산세 34
14.1%
주민세 34
14.1%
등록면허세 33
13.7%
지방소득세 29
12.0%
취득세 28
11.6%
등록세 19
7.9%
종합토지세 11
 
4.6%
담배소비세 7
 
2.9%
면허세 6
 
2.5%
Other values (2) 6
 
2.5%

Length

2023-12-12T16:28:21.157215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자동차세 34
14.1%
재산세 34
14.1%
주민세 34
14.1%
등록면허세 33
13.7%
지방소득세 29
12.0%
취득세 28
11.6%
등록세 19
7.9%
종합토지세 11
 
4.6%
담배소비세 7
 
2.9%
면허세 6
 
2.5%
Other values (2) 6
 
2.5%

납부매체
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
가상계좌
38 
은행창구
37 
지자체방문
31 
기타
29 
위택스
29 
Other values (4)
77 

Length

Max length5
Median length4
Mean length4.0207469
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가상계좌 38
15.8%
은행창구 37
15.4%
지자체방문 31
12.9%
기타 29
12.0%
위택스 29
12.0%
자동화기기 29
12.0%
인터넷지로 24
10.0%
자동이체 16
6.6%
페이사납부 8
 
3.3%

Length

2023-12-12T16:28:21.287749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:28:21.433584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가상계좌 38
15.8%
은행창구 37
15.4%
지자체방문 31
12.9%
기타 29
12.0%
위택스 29
12.0%
자동화기기 29
12.0%
인터넷지로 24
10.0%
자동이체 16
6.6%
페이사납부 8
 
3.3%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size373.0 B
False
126 
True
115 
ValueCountFrequency (%)
False 126
52.3%
True 115
47.7%
2023-12-12T16:28:21.531270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct201
Distinct (%)83.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1318.4025
Minimum1
Maximum12064
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:28:21.630139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q141
median454
Q31313
95-th percentile6404
Maximum12064
Range12063
Interquartile range (IQR)1272

Descriptive statistics

Standard deviation2259.147
Coefficient of variation (CV)1.7135488
Kurtosis7.5061784
Mean1318.4025
Median Absolute Deviation (MAD)439
Skewness2.6935014
Sum317735
Variance5103745.4
MonotonicityNot monotonic
2023-12-12T16:28:21.819553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 10
 
4.1%
2 6
 
2.5%
15 4
 
1.7%
13 4
 
1.7%
4 4
 
1.7%
48 3
 
1.2%
3 3
 
1.2%
12 3
 
1.2%
6 3
 
1.2%
19 2
 
0.8%
Other values (191) 199
82.6%
ValueCountFrequency (%)
1 10
4.1%
2 6
2.5%
3 3
 
1.2%
4 4
 
1.7%
5 2
 
0.8%
6 3
 
1.2%
7 1
 
0.4%
9 1
 
0.4%
11 1
 
0.4%
12 3
 
1.2%
ValueCountFrequency (%)
12064 1
0.4%
11598 1
0.4%
10877 1
0.4%
10609 1
0.4%
9493 1
0.4%
9357 1
0.4%
9309 1
0.4%
8705 1
0.4%
7700 1
0.4%
7134 1
0.4%

납부금액
Real number (ℝ)

HIGH CORRELATION 

Distinct240
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6995236 × 108
Minimum3050
Maximum6.4318029 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:28:22.059866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3050
5-th percentile27060
Q14761050
median56648880
Q33.4572083 × 108
95-th percentile1.5115295 × 109
Maximum6.4318029 × 109
Range6.4317998 × 109
Interquartile range (IQR)3.4095978 × 108

Descriptive statistics

Standard deviation8.3175498 × 108
Coefficient of variation (CV)2.2482759
Kurtosis28.415314
Mean3.6995236 × 108
Median Absolute Deviation (MAD)56433450
Skewness4.7668463
Sum8.915852 × 1010
Variance6.9181635 × 1017
MonotonicityNot monotonic
2023-12-12T16:28:22.245839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6180 2
 
0.8%
35473940 1
 
0.4%
210831750 1
 
0.4%
53916490 1
 
0.4%
4747000 1
 
0.4%
48281970 1
 
0.4%
2553110 1
 
0.4%
361651120 1
 
0.4%
339606420 1
 
0.4%
22035040 1
 
0.4%
Other values (230) 230
95.4%
ValueCountFrequency (%)
3050 1
0.4%
4790 1
0.4%
6060 1
0.4%
6180 2
0.8%
6830 1
0.4%
12030 1
0.4%
14810 1
0.4%
15770 1
0.4%
18190 1
0.4%
18540 1
0.4%
ValueCountFrequency (%)
6431802870 1
0.4%
6171882620 1
0.4%
5758374640 1
0.4%
3756375690 1
0.4%
2298987740 1
0.4%
2212578620 1
0.4%
1914172470 1
0.4%
1869321580 1
0.4%
1864462610 1
0.4%
1648334760 1
0.4%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct209
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.107676
Minimum0
Maximum89.09
Zeros5
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:28:22.418068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02
Q11.25
median10.34
Q321.88
95-th percentile43.48
Maximum89.09
Range89.09
Interquartile range (IQR)20.63

Descriptive statistics

Standard deviation15.934175
Coefficient of variation (CV)1.1294684
Kurtosis5.9013335
Mean14.107676
Median Absolute Deviation (MAD)9.62
Skewness1.9627552
Sum3399.95
Variance253.89792
MonotonicityNot monotonic
2023-12-12T16:28:22.576260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.04 7
 
2.9%
0.01 6
 
2.5%
0.0 5
 
2.1%
0.05 4
 
1.7%
0.02 4
 
1.7%
0.09 3
 
1.2%
1.32 2
 
0.8%
0.03 2
 
0.8%
4.74 2
 
0.8%
0.07 2
 
0.8%
Other values (199) 204
84.6%
ValueCountFrequency (%)
0.0 5
2.1%
0.01 6
2.5%
0.02 4
1.7%
0.03 2
 
0.8%
0.04 7
2.9%
0.05 4
1.7%
0.06 1
 
0.4%
0.07 2
 
0.8%
0.09 3
1.2%
0.1 1
 
0.4%
ValueCountFrequency (%)
89.09 1
0.4%
89.0 1
0.4%
88.18 1
0.4%
85.18 1
0.4%
47.4 1
0.4%
47.37 1
0.4%
47.2 1
0.4%
47.0 1
0.4%
46.85 1
0.4%
44.79 1
0.4%

Interactions

2023-12-12T16:28:19.492004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:28:18.981483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:28:19.238019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:28:19.587489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:28:19.068564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:28:19.331870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:28:19.696238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:28:19.159858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:28:19.418205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:28:22.677176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
납부년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.0000.0000.3010.6230.638
납부매체0.0000.0001.0001.0000.4430.2140.485
납부매체전자고지여부0.0000.0001.0001.0000.3290.0790.236
납부건수0.0000.3010.4430.3291.0000.1510.614
납부금액0.0000.6230.2140.0790.1511.0000.232
납부매체비율0.0000.6380.4850.2360.6140.2321.000
2023-12-12T16:28:22.782482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납부매체납부매체전자고지여부납부년도
세목명1.0000.0000.0000.000
납부매체0.0001.0000.9850.000
납부매체전자고지여부0.0000.9851.0000.000
납부년도0.0000.0000.0001.000
2023-12-12T16:28:22.882328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율납부년도세목명납부매체납부매체전자고지여부
납부건수1.0000.6840.8010.0000.1290.2190.248
납부금액0.6841.0000.5070.0000.3580.1080.081
납부매체비율0.8010.5071.0000.0000.3740.2800.250
납부년도0.0000.0000.0001.0000.0000.0000.000
세목명0.1290.3580.3740.0001.0000.0000.000
납부매체0.2190.1080.2800.0000.0001.0000.985
납부매체전자고지여부0.2480.0810.2500.0000.0000.9851.000

Missing values

2023-12-12T16:28:19.832456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:28:20.006744image/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

시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
0강원도화천군427902017등록면허세가상계좌Y2319354739408.33
1강원도화천군427902017등록세가상계좌Y1720000.0
2강원도화천군427902017면허세가상계좌Y2216300.01
3강원도화천군427902017자동차세가상계좌Y8705123698366031.25
4강원도화천군427902017재산세가상계좌Y935752380708033.6
5강원도화천군427902017종합토지세가상계좌Y3270600.01
6강원도화천군427902017주민세가상계좌Y664813700830023.87
7강원도화천군427902017지방소득세가상계좌Y6047388443502.17
8강원도화천군427902017지역자원시설세가상계좌Y123214857200.04
9강원도화천군427902017취득세가상계좌Y2011307173400.72
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
231강원도화천군427902020자동차세지자체방문N116519799727033.22
232강원도화천군427902020재산세지자체방문N5895802753016.79
233강원도화천군427902020주민세지자체방문N360639170010.27
234강원도화천군427902020지방소득세지자체방문N84212354302.4
235강원도화천군427902020취득세지자체방문N708131481497020.19
236강원도화천군427902020등록면허세페이사납부Y131801202.36
237강원도화천군427902020자동차세페이사납부Y2614372949047.37
238강원도화천군427902020재산세페이사납부Y186764295033.76
239강원도화천군427902020주민세페이사납부Y90115748016.33
240강원도화천군427902020지방소득세페이사납부Y168300.18