Overview

Dataset statistics

Number of variables11
Number of observations456
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.5 KiB
Average record size in memory93.3 B

Variable types

Categorical6
Boolean1
Numeric3
DateTime1

Dataset

Description강원특별자치도 춘천시의 지방세 납부매체별 납부 현황으로, 시도명, 시군구명, 자치단체코드, 납부년도, 세목명, 납부매체, 납부매체전자고지여부, 납부건수, 납부금액, 납부매체비율, 데이터기준일에 대한 자료를 제공합니다.
Author강원특별자치도 춘천시
URLhttps://www.data.go.kr/data/15079786/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
납부매체전자고지여부 is highly overall correlated with 납부매체High correlation
납부매체 is highly overall correlated with 납부매체전자고지여부High 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 25 (5.5%) zerosZeros

Reproduction

Analysis started2023-12-12 12:50:36.466303
Analysis finished2023-12-12 12:50:38.253412
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
강원특별자치도
456 

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 456
100.0%

Length

2023-12-12T21:50:38.340109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:50:38.442036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원특별자치도 456
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
춘천시
456 

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 456
100.0%

Length

2023-12-12T21:50:38.556817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:50:38.667133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
춘천시 456
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
51110
456 

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 456
100.0%

Length

2023-12-12T21:50:38.783775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:50:38.895993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
51110 456
100.0%

납부년도
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2020
98 
2021
95 
2022
90 
2019
88 
2018
85 

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 (%)
2020 98
21.5%
2021 95
20.8%
2022 90
19.7%
2019 88
19.3%
2018 85
18.6%

Length

2023-12-12T21:50:39.011301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:50:39.137357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 98
21.5%
2021 95
20.8%
2022 90
19.7%
2019 88
19.3%
2018 85
18.6%

세목명
Categorical

Distinct15
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
등록면허세
55 
자동차세
54 
재산세
54 
주민세
54 
지방소득세
49 
Other values (10)
190 

Length

Max length7
Median length5
Mean length4.1381579
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
등록면허세 55
12.1%
자동차세 54
11.8%
재산세 54
11.8%
주민세 54
11.8%
지방소득세 49
10.7%
지역자원시설세 44
9.6%
취득세 44
9.6%
등록세 30
6.6%
면허세 29
6.4%
종합토지세 21
 
4.6%
Other values (5) 22
 
4.8%

Length

2023-12-12T21:50:39.261058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록면허세 55
12.1%
자동차세 54
11.8%
재산세 54
11.8%
주민세 54
11.8%
지방소득세 49
10.7%
지역자원시설세 44
9.6%
취득세 44
9.6%
등록세 30
6.6%
면허세 29
6.4%
종합토지세 21
 
4.6%
Other values (5) 22
 
4.8%

납부매체
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
ARS
70 
기타
56 
가상계좌
53 
은행창구
52 
자동화기기
47 
Other values (6)
178 

Length

Max length5
Median length4
Mean length3.8464912
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
ARS 70
15.4%
기타 56
12.3%
가상계좌 53
11.6%
은행창구 52
11.4%
자동화기기 47
10.3%
지자체방문 47
10.3%
위택스 46
10.1%
인터넷지로 38
8.3%
페이사납부 26
 
5.7%
자동이체 20
 
4.4%

Length

2023-12-12T21:50:39.399391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ars 70
15.4%
기타 56
12.3%
가상계좌 53
11.6%
은행창구 52
11.4%
자동화기기 47
10.3%
지자체방문 47
10.3%
위택스 46
10.1%
인터넷지로 38
8.3%
페이사납부 26
 
5.7%
자동이체 20
 
4.4%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size588.0 B
False
246 
True
210 
ValueCountFrequency (%)
False 246
53.9%
True 210
46.1%
2023-12-12T21:50:39.497040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct353
Distinct (%)77.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8664.7325
Minimum1
Maximum124713
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-12T21:50:39.604289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.75
Q128.25
median1290.5
Q38146
95-th percentile37753.75
Maximum124713
Range124712
Interquartile range (IQR)8117.75

Descriptive statistics

Standard deviation18635.306
Coefficient of variation (CV)2.1507076
Kurtosis17.615053
Mean8664.7325
Median Absolute Deviation (MAD)1287.5
Skewness3.9351094
Sum3951118
Variance3.4727462 × 108
MonotonicityNot monotonic
2023-12-12T21:50:39.737802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 12
 
2.6%
3 11
 
2.4%
1 11
 
2.4%
4 9
 
2.0%
12 6
 
1.3%
18 6
 
1.3%
6 6
 
1.3%
10 5
 
1.1%
5 5
 
1.1%
19 4
 
0.9%
Other values (343) 381
83.6%
ValueCountFrequency (%)
1 11
2.4%
2 12
2.6%
3 11
2.4%
4 9
2.0%
5 5
1.1%
6 6
1.3%
7 2
 
0.4%
8 2
 
0.4%
9 4
 
0.9%
10 5
1.1%
ValueCountFrequency (%)
124713 1
0.2%
120666 1
0.2%
116595 1
0.2%
115114 1
0.2%
113183 1
0.2%
106992 1
0.2%
103008 1
0.2%
96986 1
0.2%
93881 1
0.2%
88171 1
0.2%

납부금액
Real number (ℝ)

HIGH CORRELATION 

Distinct455
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0145103 × 109
Minimum8850
Maximum6.8591775 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-12T21:50:39.882209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8850
5-th percentile64155
Q13228370
median3.8513379 × 108
Q32.2719945 × 109
95-th percentile2.4510055 × 1010
Maximum6.8591775 × 1010
Range6.8591766 × 1010
Interquartile range (IQR)2.2687661 × 109

Descriptive statistics

Standard deviation8.215545 × 109
Coefficient of variation (CV)2.0464626
Kurtosis11.878969
Mean4.0145103 × 109
Median Absolute Deviation (MAD)3.8500818 × 108
Skewness2.989612
Sum1.8306167 × 1012
Variance6.749518 × 1019
MonotonicityNot monotonic
2023-12-12T21:50:40.316441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
280170 2
 
0.4%
23129970110 1
 
0.2%
14168835180 1
 
0.2%
5688698800 1
 
0.2%
30082770 1
 
0.2%
5330024540 1
 
0.2%
26654265590 1
 
0.2%
60045140 1
 
0.2%
3256440 1
 
0.2%
7415889000 1
 
0.2%
Other values (445) 445
97.6%
ValueCountFrequency (%)
8850 1
0.2%
10500 1
0.2%
15000 1
0.2%
15100 1
0.2%
15830 1
0.2%
16800 1
0.2%
18000 1
0.2%
19570 1
0.2%
20480 1
0.2%
20950 1
0.2%
ValueCountFrequency (%)
68591775170 1
0.2%
43689656870 1
0.2%
39550834450 1
0.2%
39205067220 1
0.2%
33818391140 1
0.2%
31245214840 1
0.2%
28592941980 1
0.2%
27955541610 1
0.2%
27598575390 1
0.2%
27468661870 1
0.2%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct309
Distinct (%)67.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.965022
Minimum0
Maximum100
Zeros25
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-12T21:50:40.472964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.12
median4.06
Q317.0425
95-th percentile38.3875
Maximum100
Range100
Interquartile range (IQR)16.9225

Descriptive statistics

Standard deviation14.819988
Coefficient of variation (CV)1.3515694
Kurtosis5.3208236
Mean10.965022
Median Absolute Deviation (MAD)4.05
Skewness1.9626208
Sum5000.05
Variance219.63205
MonotonicityNot monotonic
2023-12-12T21:50:40.640980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 25
 
5.5%
0.01 24
 
5.3%
0.03 13
 
2.9%
0.02 11
 
2.4%
0.04 11
 
2.4%
0.09 6
 
1.3%
0.06 6
 
1.3%
0.2 6
 
1.3%
0.11 5
 
1.1%
0.1 4
 
0.9%
Other values (299) 345
75.7%
ValueCountFrequency (%)
0.0 25
5.5%
0.01 24
5.3%
0.02 11
2.4%
0.03 13
2.9%
0.04 11
2.4%
0.05 2
 
0.4%
0.06 6
 
1.3%
0.07 2
 
0.4%
0.08 4
 
0.9%
0.09 6
 
1.3%
ValueCountFrequency (%)
100.0 1
0.2%
80.58 1
0.2%
76.33 1
0.2%
71.78 1
0.2%
70.2 1
0.2%
67.57 1
0.2%
51.33 1
0.2%
51.32 1
0.2%
50.95 1
0.2%
50.6 1
0.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-12T21:50:40.837683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:40.971216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T21:50:37.599459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:36.924671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:37.292904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:37.718630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:37.042115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:37.391922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:37.825260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:37.159022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:37.488204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:50:41.061256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
납부년도1.0000.0000.0000.0000.0000.0530.000
세목명0.0001.0000.0660.1580.2730.4650.581
납부매체0.0000.0661.0000.9920.4240.2360.407
납부매체전자고지여부0.0000.1580.9921.0000.1520.0610.192
납부건수0.0000.2730.4240.1521.0000.4440.543
납부금액0.0530.4650.2360.0610.4441.0000.305
납부매체비율0.0000.5810.4070.1920.5430.3051.000
2023-12-12T21:50:41.183382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부년도납부매체전자고지여부납부매체세목명
납부년도1.0000.0000.0000.000
납부매체전자고지여부0.0001.0000.9140.142
납부매체0.0000.9141.0000.023
세목명0.0000.1420.0231.000
2023-12-12T21:50:41.327735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율납부년도세목명납부매체납부매체전자고지여부
납부건수1.0000.8250.8900.0000.1130.2080.151
납부금액0.8251.0000.7190.0310.2180.1140.045
납부매체비율0.8900.7191.0000.0000.2570.1980.146
납부년도0.0000.0310.0001.0000.0000.0000.000
세목명0.1130.2180.2570.0001.0000.0230.142
납부매체0.2080.1140.1980.0000.0231.0000.914
납부매체전자고지여부0.1510.0450.1460.0000.1420.9141.000

Missing values

2023-12-12T21:50:37.965676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:50:38.156382image/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

시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율데이터기준일
0강원특별자치도춘천시511102018등록면허세ARSN14623069601.692022-12-31
1강원특별자치도춘천시511102018등록면허세ARSY132801700.152022-12-31
2강원특별자치도춘천시511102018면허세ARSN2168000.022022-12-31
3강원특별자치도춘천시511102018자동차세ARSN442777510877051.322022-12-31
4강원특별자치도춘천시511102018자동차세ARSY7484592500.862022-12-31
5강원특별자치도춘천시511102018재산세ARSN252543244996029.272022-12-31
6강원특별자치도춘천시511102018재산세ARSY1716695900.22022-12-31
7강원특별자치도춘천시511102018종합토지세ARSN96914900.12022-12-31
8강원특별자치도춘천시511102018주민세ARSN12041876033013.962022-12-31
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