Overview

Dataset statistics

Number of variables10
Number of observations1259
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory104.6 KiB
Average record size in memory85.1 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description납부 매체별 지방세 납부 현황으로, 과세연도, 세목명, 납부매체(가상계좌/신용카드/지로/지역페이/포인트 등), 납부매체 전자고지 여부, 납부 건수, 납부금액, 납부 매체 비율 항목으로 구성되어 있습니다. ※ 납부 매체 비율 : 세목별 전체 납부 건수 대비 납부 매체별 납부 비율로서, 납부 매체별 건수/전체 납부 건수*100
URLhttps://www.data.go.kr/data/15080595/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 is highly overall correlated with 자치단체코드High correlation
자치단체코드 is highly overall correlated with 시군구명High correlation
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 467 (37.1%) zerosZeros

Reproduction

Analysis started2023-12-12 18:07:19.439558
Analysis finished2023-12-12 18:07:21.265146
Duration1.83 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
경기도
1259 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 1259
100.0%

Length

2023-12-13T03:07:21.346575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:07:21.442287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 1259
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
성남시분당구
428 
성남시중원구
422 
성남시수정구
404 
성남시
 
5

Length

Max length6
Median length6
Mean length5.9880858
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성남시분당구 428
34.0%
성남시중원구 422
33.5%
성남시수정구 404
32.1%
성남시 5
 
0.4%

Length

2023-12-13T03:07:21.549270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:07:21.679109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성남시분당구 428
34.0%
성남시중원구 422
33.5%
성남시수정구 404
32.1%
성남시 5
 
0.4%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
41135
428 
41133
422 
41131
404 
41130
 
5

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41135
2nd row41135
3rd row41135
4th row41135
5th row41135

Common Values

ValueCountFrequency (%)
41135 428
34.0%
41133 422
33.5%
41131 404
32.1%
41130 5
 
0.4%

Length

2023-12-13T03:07:21.800030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:07:21.900934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41135 428
34.0%
41133 422
33.5%
41131 404
32.1%
41130 5
 
0.4%

납부년도
Categorical

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
2019
259 
2017
254 
2022
250 
2018
248 
2021
248 

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 (%)
2019 259
20.6%
2017 254
20.2%
2022 250
19.9%
2018 248
19.7%
2021 248
19.7%

Length

2023-12-13T03:07:21.997998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:07:22.096704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 259
20.6%
2017 254
20.2%
2022 250
19.9%
2018 248
19.7%
2021 248
19.7%

세목명
Categorical

Distinct15
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
자동차세
160 
주민세
160 
재산세
158 
등록면허세
157 
지방소득세
143 
Other values (10)
481 

Length

Max length7
Median length5
Mean length3.9912629
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 160
12.7%
주민세 160
12.7%
재산세 158
12.5%
등록면허세 157
12.5%
지방소득세 143
11.4%
취득세 131
10.4%
면허세 84
6.7%
등록세 82
6.5%
지역자원시설세 80
6.4%
종합토지세 52
 
4.1%
Other values (5) 52
 
4.1%

Length

2023-12-13T03:07:22.220431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자동차세 160
12.7%
주민세 160
12.7%
재산세 158
12.5%
등록면허세 157
12.5%
지방소득세 143
11.4%
취득세 131
10.4%
면허세 84
6.7%
등록세 82
6.5%
지역자원시설세 80
6.4%
종합토지세 52
 
4.1%
Other values (5) 52
 
4.1%

납부매체
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
ARS
180 
가상계좌
164 
기타
147 
은행창구
138 
자동화기기
135 
Other values (7)
495 

Length

Max length5
Median length4
Mean length3.8610008
Min length2

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
ARS 180
14.3%
가상계좌 164
13.0%
기타 147
11.7%
은행창구 138
11.0%
자동화기기 135
10.7%
위택스 134
10.6%
지자체방문 134
10.6%
인터넷지로 113
9.0%
자동이체 60
 
4.8%
페이사납부 52
 
4.1%
Other values (2) 2
 
0.2%

Length

2023-12-13T03:07:22.348904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ars 180
14.3%
가상계좌 164
13.0%
기타 147
11.7%
은행창구 138
11.0%
자동화기기 135
10.7%
위택스 134
10.6%
지자체방문 134
10.6%
인터넷지로 113
9.0%
자동이체 60
 
4.8%
페이사납부 52
 
4.1%
Other values (2) 2
 
0.2%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
False
660 
True
599 
ValueCountFrequency (%)
False 660
52.4%
True 599
47.6%
2023-12-13T03:07:22.442272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct840
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9882.9706
Minimum1
Maximum218565
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2023-12-13T03:07:22.543672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q113
median1435
Q37247
95-th percentile56700.4
Maximum218565
Range218564
Interquartile range (IQR)7234

Descriptive statistics

Standard deviation24010.74
Coefficient of variation (CV)2.4295063
Kurtosis25.724894
Mean9882.9706
Median Absolute Deviation (MAD)1433
Skewness4.5693615
Sum12442660
Variance5.7651562 × 108
MonotonicityNot monotonic
2023-12-13T03:07:22.668368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 83
 
6.6%
3 42
 
3.3%
2 41
 
3.3%
4 25
 
2.0%
6 20
 
1.6%
8 18
 
1.4%
10 17
 
1.4%
5 17
 
1.4%
11 15
 
1.2%
9 12
 
1.0%
Other values (830) 969
77.0%
ValueCountFrequency (%)
1 83
6.6%
2 41
3.3%
3 42
3.3%
4 25
 
2.0%
5 17
 
1.4%
6 20
 
1.6%
7 9
 
0.7%
8 18
 
1.4%
9 12
 
1.0%
10 17
 
1.4%
ValueCountFrequency (%)
218565 1
0.1%
210200 1
0.1%
190528 1
0.1%
186514 1
0.1%
176720 1
0.1%
169993 1
0.1%
166376 1
0.1%
166211 1
0.1%
165044 1
0.1%
161933 1
0.1%

납부금액
Real number (ℝ)

HIGH CORRELATION 

Distinct1247
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.1567659 × 109
Minimum1000
Maximum4.39503 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2023-12-13T03:07:22.793922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile46350
Q11576790
median2.6000629 × 108
Q34.1722116 × 109
95-th percentile4.3683325 × 1010
Maximum4.39503 × 1011
Range4.39503 × 1011
Interquartile range (IQR)4.1706348 × 109

Descriptive statistics

Standard deviation2.9742531 × 1010
Coefficient of variation (CV)3.248148
Kurtosis67.473645
Mean9.1567659 × 109
Median Absolute Deviation (MAD)2.5995994 × 108
Skewness7.0289616
Sum1.1528368 × 1013
Variance8.8461816 × 1020
MonotonicityNot monotonic
2023-12-13T03:07:22.942578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37800 5
 
0.4%
18540 3
 
0.2%
46350 3
 
0.2%
113400 2
 
0.2%
65250 2
 
0.2%
18900 2
 
0.2%
27810 2
 
0.2%
459010 1
 
0.1%
687020 1
 
0.1%
22642460 1
 
0.1%
Other values (1237) 1237
98.3%
ValueCountFrequency (%)
1000 1
0.1%
2220 1
0.1%
2320 1
0.1%
2590 1
0.1%
3880 1
0.1%
5000 1
0.1%
6980 1
0.1%
7200 1
0.1%
7550 1
0.1%
10000 1
0.1%
ValueCountFrequency (%)
439503000000 1
0.1%
330062000000 1
0.1%
297475000000 1
0.1%
283566000000 1
0.1%
219685000000 1
0.1%
208757000000 1
0.1%
195573000000 1
0.1%
188232000000 1
0.1%
186588000000 1
0.1%
179369000000 1
0.1%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct199
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9530977
Minimum0
Maximum100
Zeros467
Zeros (%)37.1%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2023-12-13T03:07:23.075597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.94
Q35.32
95-th percentile15
Maximum100
Range100
Interquartile range (IQR)5.32

Descriptive statistics

Standard deviation7.0551494
Coefficient of variation (CV)1.7847141
Kurtosis59.855774
Mean3.9530977
Median Absolute Deviation (MAD)1.94
Skewness5.7485102
Sum4976.95
Variance49.775132
MonotonicityNot monotonic
2023-12-13T03:07:23.209043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 467
37.1%
1.0 85
 
6.8%
2.0 85
 
6.8%
3.0 68
 
5.4%
4.0 62
 
4.9%
6.0 54
 
4.3%
5.0 41
 
3.3%
7.0 34
 
2.7%
9.0 21
 
1.7%
10.0 19
 
1.5%
Other values (189) 323
25.7%
ValueCountFrequency (%)
0.0 467
37.1%
0.01 14
 
1.1%
0.02 11
 
0.9%
0.03 7
 
0.6%
0.04 3
 
0.2%
0.05 1
 
0.1%
0.06 1
 
0.1%
0.07 3
 
0.2%
0.08 1
 
0.1%
0.11 1
 
0.1%
ValueCountFrequency (%)
100.0 2
0.2%
54.0 1
 
0.1%
51.0 1
 
0.1%
45.0 1
 
0.1%
35.0 1
 
0.1%
34.0 3
0.2%
32.01 1
 
0.1%
32.0 1
 
0.1%
28.42 1
 
0.1%
28.0 1
 
0.1%

Interactions

2023-12-13T03:07:20.707422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:20.103782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:20.405725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:20.807065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:20.200369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:20.497818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:20.902021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:20.299960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:20.599756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:07:23.295984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
시군구명1.0001.0000.0630.4790.0000.0000.1450.2650.248
자치단체코드1.0001.0000.0630.4790.0000.0000.1450.2650.248
납부년도0.0630.0631.0000.0000.0500.0120.0000.0000.000
세목명0.4790.4790.0001.0000.3190.1200.3030.2470.349
납부매체0.0000.0000.0500.3191.0000.9110.3590.1600.681
납부매체전자고지여부0.0000.0000.0120.1200.9111.0000.2630.0980.055
납부건수0.1450.1450.0000.3030.3590.2631.0000.5670.431
납부금액0.2650.2650.0000.2470.1600.0980.5671.0000.239
납부매체비율0.2480.2480.0000.3490.6810.0550.4310.2391.000
2023-12-13T03:07:23.409209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명세목명자치단체코드납부매체납부매체전자고지여부납부년도
시군구명1.0000.2901.0000.0000.0000.051
세목명0.2901.0000.2900.1280.1080.000
자치단체코드1.0000.2901.0000.0000.0000.051
납부매체0.0000.1280.0001.0000.9240.027
납부매체전자고지여부0.0000.1080.0000.9241.0000.015
납부년도0.0510.0000.0510.0270.0151.000
2023-12-13T03:07:23.507437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부
납부건수1.0000.8500.8530.0870.0870.0000.1170.1610.201
납부금액0.8501.0000.7030.1210.1210.0000.1070.0750.073
납부매체비율0.8530.7031.0000.1710.1710.0000.1590.4210.080
시군구명0.0870.1210.1711.0001.0000.0510.2900.0000.000
자치단체코드0.0870.1210.1711.0001.0000.0510.2900.0000.000
납부년도0.0000.0000.0000.0510.0511.0000.0000.0270.015
세목명0.1170.1070.1590.2900.2900.0001.0000.1280.108
납부매체0.1610.0750.4210.0000.0000.0270.1281.0000.924
납부매체전자고지여부0.2010.0730.0800.0000.0000.0150.1080.9241.000

Missing values

2023-12-13T03:07:21.052637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:07:21.200577image/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
0경기도성남시분당구411352017등록면허세ARSN19370158201.0
1경기도성남시분당구411352017등록면허세ARSY41007800.0
2경기도성남시분당구411352017면허세ARSN62088900.0
3경기도성남시분당구411352017자동차세ARSN6408145301883021.0
4경기도성남시분당구411352017자동차세ARSY103217900.0
5경기도성남시분당구411352017재산세ARSN8063280763934027.0
6경기도성남시분당구411352017재산세ARSY2136500.0
7경기도성남시분당구411352017종합토지세ARSN3643900.0
8경기도성남시분당구411352017주민세ARSN2308242181408.0
9경기도성남시분당구411352017주민세ARSY1288255400.0
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
1249경기도성남시수정구411312022재산세페이사납부Y699425323852507.66
1250경기도성남시수정구411312022주민세페이사납부Y5424268949205.94
1251경기도성남시수정구411312022지방소득세페이사납부Y65112608400.07
1252경기도성남시수정구411312022취득세페이사납부Y14254384000.02
1253경기도성남시중원구411332022등록면허세페이사납부Y529165416000.58
1254경기도성남시중원구411332022자동차세페이사납부Y49138585644105.38
1255경기도성남시중원구411332022재산세페이사납부Y622612001349306.82
1256경기도성남시중원구411332022주민세페이사납부Y3801205440604.17
1257경기도성남시중원구411332022지방소득세페이사납부Y6233227500.07
1258경기도성남시중원구411332022취득세페이사납부Y14250476500.02