Overview

Dataset statistics

Number of variables10
Number of observations422
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.2 KiB
Average record size in memory85.3 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description납부 매체별 지방세 납부 현황 제공 (시도명, 시군구명, 자치단체코드, 납부연도, 세목명, 납부매체, 납부매체, 전자고지여부, 납부건수, 납부금액, 납부매체비율)
URLhttps://www.data.go.kr/data/15078693/fileData.do

Alerts

시도명 has constant value ""Constant
납부년도 has constant value ""Constant
납부매체전자고지여부 is highly overall correlated with 납부매체High correlation
시군구명 is highly overall correlated with 자치단체코드High correlation
납부매체 is highly overall correlated with 납부매체전자고지여부High correlation
자치단체코드 is highly overall correlated with 시군구명High 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
납부금액 has unique valuesUnique
납부매체비율 has 50 (11.8%) zerosZeros

Reproduction

Analysis started2023-12-12 14:08:53.374631
Analysis finished2023-12-12 14:08:54.943169
Duration1.57 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
창원시
422 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
창원시 422
100.0%

Length

2023-12-12T23:08:55.004129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:08:55.108894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
창원시 422
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
마산합포구
85 
마산회원구
85 
의창구
85 
성산구
84 
진해구
83 

Length

Max length5
Median length3
Mean length3.8056872
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row마산합포구
2nd row마산합포구
3rd row마산합포구
4th row마산합포구
5th row마산회원구

Common Values

ValueCountFrequency (%)
마산합포구 85
20.1%
마산회원구 85
20.1%
의창구 85
20.1%
성산구 84
19.9%
진해구 83
19.7%

Length

2023-12-12T23:08:55.229426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:08:55.397820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마산합포구 85
20.1%
마산회원구 85
20.1%
의창구 85
20.1%
성산구 84
19.9%
진해구 83
19.7%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
48125
85 
48127
85 
48121
85 
48123
84 
48129
83 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48125
2nd row48125
3rd row48125
4th row48125
5th row48127

Common Values

ValueCountFrequency (%)
48125 85
20.1%
48127 85
20.1%
48121 85
20.1%
48123 84
19.9%
48129 83
19.7%

Length

2023-12-12T23:08:55.537994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:08:55.655488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48125 85
20.1%
48127 85
20.1%
48121 85
20.1%
48123 84
19.9%
48129 83
19.7%

납부년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2021
422 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 422
100.0%

Length

2023-12-12T23:08:55.801116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:08:55.915597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 422
100.0%

세목명
Categorical

Distinct15
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
등록면허세
55 
자동차세
55 
재산세
55 
주민세
55 
지방소득세
49 
Other values (10)
153 

Length

Max length7
Median length5
Mean length4.1042654
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row지방소득세
2nd row지방소비세
3rd row지역자원시설세
4th row취득세
5th row등록면허세

Common Values

ValueCountFrequency (%)
등록면허세 55
13.0%
자동차세 55
13.0%
재산세 55
13.0%
주민세 55
13.0%
지방소득세 49
11.6%
취득세 45
10.7%
지역자원시설세 40
9.5%
등록세 27
6.4%
면허세 15
 
3.6%
종합토지세 11
 
2.6%
Other values (5) 15
 
3.6%

Length

2023-12-12T23:08:56.050580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록면허세 55
13.0%
자동차세 55
13.0%
재산세 55
13.0%
주민세 55
13.0%
지방소득세 49
11.6%
취득세 45
10.7%
지역자원시설세 40
9.5%
등록세 27
6.4%
면허세 15
 
3.6%
종합토지세 11
 
2.6%
Other values (5) 15
 
3.6%

납부매체
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
ARS
58 
기타
52 
가상계좌
49 
위택스
45 
지자체방문
44 
Other values (5)
174 

Length

Max length5
Median length4
Mean length3.8791469
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
ARS 58
13.7%
기타 52
12.3%
가상계좌 49
11.6%
위택스 45
10.7%
지자체방문 44
10.4%
은행창구 42
10.0%
자동화기기 42
10.0%
인터넷지로 38
9.0%
페이사납부 32
7.6%
자동이체 20
 
4.7%

Length

2023-12-12T23:08:56.226038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:08:56.439091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ars 58
13.7%
기타 52
12.3%
가상계좌 49
11.6%
위택스 45
10.7%
지자체방문 44
10.4%
은행창구 42
10.0%
자동화기기 42
10.0%
인터넷지로 38
9.0%
페이사납부 32
7.6%
자동이체 20
 
4.7%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size554.0 B
False
214 
True
208 
ValueCountFrequency (%)
False 214
50.7%
True 208
49.3%
2023-12-12T23:08:56.569998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct326
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6858.1161
Minimum1
Maximum103309
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-12T23:08:56.714594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q133
median1491
Q36973.25
95-th percentile29754.45
Maximum103309
Range103308
Interquartile range (IQR)6940.25

Descriptive statistics

Standard deviation14121.391
Coefficient of variation (CV)2.0590773
Kurtosis15.931392
Mean6858.1161
Median Absolute Deviation (MAD)1487
Skewness3.7366013
Sum2894125
Variance1.9941368 × 108
MonotonicityNot monotonic
2023-12-12T23:08:56.877567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 16
 
3.8%
2 15
 
3.6%
7 9
 
2.1%
4 7
 
1.7%
3 6
 
1.4%
10 6
 
1.4%
40 5
 
1.2%
11 5
 
1.2%
6 4
 
0.9%
9 4
 
0.9%
Other values (316) 345
81.8%
ValueCountFrequency (%)
1 16
3.8%
2 15
3.6%
3 6
 
1.4%
4 7
1.7%
5 3
 
0.7%
6 4
 
0.9%
7 9
2.1%
8 1
 
0.2%
9 4
 
0.9%
10 6
 
1.4%
ValueCountFrequency (%)
103309 1
0.2%
87811 1
0.2%
84779 1
0.2%
79320 1
0.2%
76459 1
0.2%
75476 1
0.2%
67197 1
0.2%
62369 1
0.2%
61943 1
0.2%
60731 1
0.2%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct422
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4886693 × 109
Minimum3030
Maximum9.7719815 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-12T23:08:57.026602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3030
5-th percentile77803
Q15381580
median2.7273301 × 108
Q33.0260518 × 109
95-th percentile1.6215941 × 1010
Maximum9.7719815 × 1010
Range9.7719812 × 1010
Interquartile range (IQR)3.0206702 × 109

Descriptive statistics

Standard deviation8.2579608 × 109
Coefficient of variation (CV)2.3670804
Kurtosis45.483159
Mean3.4886693 × 109
Median Absolute Deviation (MAD)2.7261486 × 108
Skewness5.4114706
Sum1.4722184 × 1012
Variance6.8193916 × 1019
MonotonicityNot monotonic
2023-12-12T23:08:57.173994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2240059160 1
 
0.2%
3573230 1
 
0.2%
7545200 1
 
0.2%
55249800 1
 
0.2%
96870 1
 
0.2%
847620 1
 
0.2%
19505840 1
 
0.2%
301894190 1
 
0.2%
468402150 1
 
0.2%
6019810 1
 
0.2%
Other values (412) 412
97.6%
ValueCountFrequency (%)
3030 1
0.2%
6180 1
0.2%
7400 1
0.2%
15750 1
0.2%
15900 1
0.2%
18900 1
0.2%
27810 1
0.2%
31200 1
0.2%
40320 1
0.2%
41890 1
0.2%
ValueCountFrequency (%)
97719815010 1
0.2%
48369558070 1
0.2%
45269765630 1
0.2%
41915823740 1
0.2%
34733100240 1
0.2%
34013318630 1
0.2%
33314219050 1
0.2%
32970180250 1
0.2%
28080018300 1
0.2%
25478824930 1
0.2%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct247
Distinct (%)58.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3695498
Minimum0
Maximum16.4
Zeros50
Zeros (%)11.8%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-12T23:08:57.307002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.03
median1.305
Q33.655
95-th percentile8.229
Maximum16.4
Range16.4
Interquartile range (IQR)3.625

Descriptive statistics

Standard deviation3.0089745
Coefficient of variation (CV)1.2698507
Kurtosis3.7229601
Mean2.3695498
Median Absolute Deviation (MAD)1.295
Skewness1.7800135
Sum999.95
Variance9.0539274
MonotonicityNot monotonic
2023-12-12T23:08:57.477549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 50
 
11.8%
0.01 25
 
5.9%
0.03 17
 
4.0%
0.02 16
 
3.8%
0.05 7
 
1.7%
0.07 7
 
1.7%
0.04 6
 
1.4%
0.09 6
 
1.4%
0.13 5
 
1.2%
3.63 3
 
0.7%
Other values (237) 280
66.4%
ValueCountFrequency (%)
0.0 50
11.8%
0.01 25
5.9%
0.02 16
 
3.8%
0.03 17
 
4.0%
0.04 6
 
1.4%
0.05 7
 
1.7%
0.06 2
 
0.5%
0.07 7
 
1.7%
0.08 3
 
0.7%
0.09 6
 
1.4%
ValueCountFrequency (%)
16.4 1
0.2%
15.82 1
0.2%
15.55 1
0.2%
14.12 1
0.2%
13.12 1
0.2%
12.84 1
0.2%
12.82 1
0.2%
12.49 1
0.2%
11.13 1
0.2%
10.97 1
0.2%

Interactions

2023-12-12T23:08:54.281980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:53.745085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:54.000628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:54.382766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:53.820203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:54.079852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:54.480135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:53.909503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:54.169523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:08:57.592461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
시군구명1.0001.0000.0000.0000.0000.0000.0910.000
자치단체코드1.0001.0000.0000.0000.0000.0000.0910.000
세목명0.0000.0001.0000.1790.0000.1520.6180.536
납부매체0.0000.0000.1791.0000.9940.5050.2750.436
납부매체전자고지여부0.0000.0000.0000.9941.0000.2580.1390.055
납부건수0.0000.0000.1520.5050.2581.0000.4190.725
납부금액0.0910.0910.6180.2750.1390.4191.0000.153
납부매체비율0.0000.0000.5360.4360.0550.7250.1531.000
2023-12-12T23:08:57.724035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체전자고지여부시군구명세목명납부매체자치단체코드
납부매체전자고지여부1.0000.0000.0000.9200.000
시군구명0.0001.0000.0000.0001.000
세목명0.0000.0001.0000.0660.000
납부매체0.9200.0000.0661.0000.000
자치단체코드0.0001.0000.0000.0001.000
2023-12-12T23:08:58.110694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율시군구명자치단체코드세목명납부매체납부매체전자고지여부
납부건수1.0000.8270.8740.0000.0000.0560.1760.196
납부금액0.8271.0000.7160.0600.0600.3410.1470.100
납부매체비율0.8740.7161.0000.0180.0180.2320.1280.000
시군구명0.0000.0600.0181.0001.0000.0000.0000.000
자치단체코드0.0000.0600.0181.0001.0000.0000.0000.000
세목명0.0560.3410.2320.0000.0001.0000.0660.000
납부매체0.1760.1470.1280.0000.0000.0661.0000.920
납부매체전자고지여부0.1960.1000.0000.0000.0000.0000.9201.000

Missing values

2023-12-12T23:08:54.624059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:08:54.870819image/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
0창원시마산합포구481252021지방소득세기타N382022400591608.95
1창원시마산합포구481252021지방소비세기타N217542211700.0
2창원시마산합포구481252021지역자원시설세기타N42673500.01
3창원시마산합포구481252021취득세기타N12550933100.03
4창원시마산회원구481272021등록면허세기타N25043119800.59
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