Overview

Dataset statistics

Number of variables10
Number of observations166
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.9 KiB
Average record size in memory85.8 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description신용카드,가상계좌 등 지방세 납부매체별 납부 현황 (가상계좌,신용카드,지로,신용카드포인트 등)을 제공하는 데이터이며, 전자송달 시장 규모 및 편익 분석, 수수료 산정시 기초자료로 활용됩니다.
Author인천광역시 연수구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15079002&srcSe=7661IVAWM27C61E190

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 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 17 (10.2%) zerosZeros

Reproduction

Analysis started2024-01-28 05:59:51.890409
Analysis finished2024-01-28 05:59:53.373780
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
인천광역시
166 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 166
100.0%

Length

2024-01-28T14:59:53.427583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:59:53.510594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 166
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
연수구
166 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연수구 166
100.0%

Length

2024-01-28T14:59:53.596283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:59:53.685092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
연수구 166
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
28185
166 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28185
2nd row28185
3rd row28185
4th row28185
5th row28185

Common Values

ValueCountFrequency (%)
28185 166
100.0%

Length

2024-01-28T14:59:53.773494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:59:53.855242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28185 166
100.0%

납부년도
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2020
85 
2021
81 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 85
51.2%
2021 81
48.8%

Length

2024-01-28T14:59:53.942260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:59:54.067542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 85
51.2%
2021 81
48.8%

세목명
Categorical

Distinct13
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
재산세
21 
주민세
21 
등록면허세
20 
자동차세
20 
지방소득세
18 
Other values (8)
66 

Length

Max length7
Median length6
Mean length4
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 21
12.7%
주민세 21
12.7%
등록면허세 20
12.0%
자동차세 20
12.0%
지방소득세 18
10.8%
취득세 18
10.8%
면허세 12
7.2%
지역자원시설세 12
7.2%
등록세 9
5.4%
종합토지세 7
 
4.2%
Other values (3) 8
 
4.8%

Length

2024-01-28T14:59:54.281233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재산세 21
12.7%
주민세 21
12.7%
등록면허세 20
12.0%
자동차세 20
12.0%
지방소득세 18
10.8%
취득세 18
10.8%
면허세 12
7.2%
지역자원시설세 12
7.2%
등록세 9
5.4%
종합토지세 7
 
4.2%
Other values (3) 8
 
4.8%

납부매체
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
가상계좌
21 
은행창구
20 
기타
19 
위택스
19 
지자체방문
19 
Other values (6)
68 

Length

Max length5
Median length4
Mean length3.939759
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가상계좌 21
12.7%
은행창구 20
12.0%
기타 19
11.4%
위택스 19
11.4%
지자체방문 19
11.4%
자동화기기 18
10.8%
ARS 14
8.4%
인터넷지로 14
8.4%
페이사납부 12
7.2%
자동이체 8
 
4.8%

Length

2024-01-28T14:59:54.435410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가상계좌 21
12.7%
은행창구 20
12.0%
기타 19
11.4%
위택스 19
11.4%
지자체방문 19
11.4%
자동화기기 18
10.8%
ars 14
8.4%
인터넷지로 14
8.4%
페이사납부 12
7.2%
자동이체 8
 
4.8%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size298.0 B
False
90 
True
76 
ValueCountFrequency (%)
False 90
54.2%
True 76
45.8%
2024-01-28T14:59:54.580447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct133
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13399.235
Minimum1
Maximum218556
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-28T14:59:54.689690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q114.5
median2503.5
Q311332.75
95-th percentile61306.75
Maximum218556
Range218555
Interquartile range (IQR)11318.25

Descriptive statistics

Standard deviation32736.132
Coefficient of variation (CV)2.4431344
Kurtosis21.782821
Mean13399.235
Median Absolute Deviation (MAD)2501.5
Skewness4.4422948
Sum2224273
Variance1.0716544 × 109
MonotonicityNot monotonic
2024-01-28T14:59:54.839534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 10
 
6.0%
7 8
 
4.8%
4 5
 
3.0%
3 5
 
3.0%
12 5
 
3.0%
2 4
 
2.4%
16 2
 
1.2%
2456 2
 
1.2%
18662 1
 
0.6%
36 1
 
0.6%
Other values (123) 123
74.1%
ValueCountFrequency (%)
1 10
6.0%
2 4
 
2.4%
3 5
3.0%
4 5
3.0%
5 1
 
0.6%
6 1
 
0.6%
7 8
4.8%
8 1
 
0.6%
11 1
 
0.6%
12 5
3.0%
ValueCountFrequency (%)
218556 1
0.6%
200008 1
0.6%
187299 1
0.6%
164828 1
0.6%
94059 1
0.6%
83888 1
0.6%
80269 1
0.6%
63842 1
0.6%
61373 1
0.6%
61108 1
0.6%

납부금액
Real number (ℝ)

HIGH CORRELATION 

Distinct163
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3832305 × 109
Minimum12350
Maximum7.8204738 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-28T14:59:54.968622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12350
5-th percentile113637.5
Q12230800
median6.4338524 × 108
Q35.2147261 × 109
95-th percentile4.6314274 × 1010
Maximum7.8204738 × 1010
Range7.8204725 × 1010
Interquartile range (IQR)5.2124953 × 109

Descriptive statistics

Standard deviation1.734445 × 1010
Coefficient of variation (CV)2.0689458
Kurtosis5.6771904
Mean8.3832305 × 109
Median Absolute Deviation (MAD)6.4318306 × 108
Skewness2.5127975
Sum1.3916163 × 1012
Variance3.0082994 × 1020
MonotonicityNot monotonic
2024-01-28T14:59:55.107841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16330148930 3
 
1.8%
75807602490 2
 
1.2%
7903940 1
 
0.6%
66229400190 1
 
0.6%
844720250 1
 
0.6%
24723036850 1
 
0.6%
16740 1
 
0.6%
1181310430 1
 
0.6%
19594413790 1
 
0.6%
633270 1
 
0.6%
Other values (153) 153
92.2%
ValueCountFrequency (%)
12350 1
0.6%
16740 1
0.6%
28350 1
0.6%
38500 1
0.6%
41120 1
0.6%
67480 1
0.6%
85600 1
0.6%
103950 1
0.6%
111960 1
0.6%
118670 1
0.6%
ValueCountFrequency (%)
78204737690 1
0.6%
75807602490 2
1.2%
66229400190 1
0.6%
66001634670 1
0.6%
65796969790 1
0.6%
62800133710 1
0.6%
55424250260 1
0.6%
46974028320 1
0.6%
44335011960 1
0.6%
44308894450 1
0.6%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct122
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.650783
Minimum0
Maximum75
Zeros17
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-28T14:59:55.266511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.04
median6.98
Q320.22
95-th percentile42.165
Maximum75
Range75
Interquartile range (IQR)20.18

Descriptive statistics

Standard deviation15.958623
Coefficient of variation (CV)1.2614732
Kurtosis2.8500082
Mean12.650783
Median Absolute Deviation (MAD)6.97
Skewness1.6546956
Sum2100.03
Variance254.67766
MonotonicityNot monotonic
2024-01-28T14:59:55.442932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 17
 
10.2%
0.01 13
 
7.8%
0.02 8
 
4.8%
0.03 3
 
1.8%
0.05 3
 
1.8%
11.38 2
 
1.2%
0.04 2
 
1.2%
0.1 2
 
1.2%
0.08 2
 
1.2%
6.98 2
 
1.2%
Other values (112) 112
67.5%
ValueCountFrequency (%)
0.0 17
10.2%
0.01 13
7.8%
0.02 8
4.8%
0.03 3
 
1.8%
0.04 2
 
1.2%
0.05 3
 
1.8%
0.07 1
 
0.6%
0.08 2
 
1.2%
0.09 1
 
0.6%
0.1 2
 
1.2%
ValueCountFrequency (%)
75.0 1
0.6%
73.71 1
0.6%
66.74 1
0.6%
62.19 1
0.6%
60.51 1
0.6%
52.56 1
0.6%
47.94 1
0.6%
43.29 1
0.6%
42.86 1
0.6%
40.08 1
0.6%

Interactions

2024-01-28T14:59:52.916527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:59:52.170013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:59:52.382931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:59:52.992239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:59:52.237350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:59:52.456608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:59:53.081916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:59:52.310684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:59:52.816057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T14:59:55.553266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
납부년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.0000.0000.0000.1520.522
납부매체0.0000.0001.0001.0000.3050.2690.531
납부매체전자고지여부0.0000.0001.0001.0000.3320.1290.090
납부건수0.0000.0000.3050.3321.0000.7080.422
납부금액0.0000.1520.2690.1290.7081.0000.408
납부매체비율0.0000.5220.5310.0900.4220.4081.000
2024-01-28T14:59:55.647166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납부년도납부매체전자고지여부납부매체
세목명1.0000.0000.0000.000
납부년도0.0001.0000.0000.000
납부매체전자고지여부0.0000.0001.0000.972
납부매체0.0000.0000.9721.000
2024-01-28T14:59:55.763225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율납부년도세목명납부매체납부매체전자고지여부
납부건수1.0000.8570.8320.0000.0000.1460.245
납부금액0.8571.0000.7170.0000.0640.1180.086
납부매체비율0.8320.7171.0000.0000.2430.2570.065
납부년도0.0000.0000.0001.0000.0000.0000.000
세목명0.0000.0640.2430.0001.0000.0000.000
납부매체0.1460.1180.2570.0000.0001.0000.972
납부매체전자고지여부0.2450.0860.0650.0000.0000.9721.000

Missing values

2024-01-28T14:59:53.206136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T14:59:53.326225image/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
0인천광역시연수구281852020등록면허세ARSN26479039401.28
1인천광역시연수구281852020면허세ARSN41221300.02
2인천광역시연수구281852020사업소세ARSN11996200.0
3인천광역시연수구281852020자동차세ARSN7607158703671037.0
4인천광역시연수구281852020재산세ARSN10807270233032052.56
5인천광역시연수구281852020주민세ARSN1522265161307.4
6인천광역시연수구281852020지방소득세ARSN2731320408801.33
7인천광역시연수구281852020취득세ARSN842538104900.41
8인천광역시연수구281852020등록면허세가상계좌Y2674011693796704.96
9인천광역시연수구281852020등록세가상계좌Y1385000.0
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
156인천광역시연수구281852021주민세ARSN1490260662006.98
157인천광역시연수구281852021지방소득세ARSN2392471918601.12
158인천광역시연수구281852021취득세ARSN4757757682602.23
159인천광역시연수구281852021등록면허세가상계좌Y288309214355204.71
160인천광역시연수구281852021면허세가상계좌Y389000900.01
161인천광역시연수구281852021사업소세가상계좌Y27618100.0
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