Overview

Dataset statistics

Number of variables11
Number of observations240
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.9 KiB
Average record size in memory93.5 B

Variable types

Categorical7
Boolean1
Numeric3

Dataset

Description이 데이터는 남원시의 지방세 납부현황에 대하여 2018년부터 2020년까지의 세목명, 납부매체, 납부매체 전자고지여부, 납부건수, 납부금액, 납부매체비율에 대한 데이터입니다.
URLhttps://www.data.go.kr/data/15079841/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일자 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 69 (28.7%) zerosZeros

Reproduction

Analysis started2023-12-12 13:15:31.116757
Analysis finished2023-12-12 13:15:32.865418
Duration1.75 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
전라북도
240 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 240
100.0%

Length

2023-12-12T22:15:32.928937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:15:33.018904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 240
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
남원시
240 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남원시 240
100.0%

Length

2023-12-12T22:15:33.099500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:15:33.181970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남원시 240
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
45190
240 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row45190
2nd row45190
3rd row45190
4th row45190
5th row45190

Common Values

ValueCountFrequency (%)
45190 240
100.0%

Length

2023-12-12T22:15:33.296557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:15:33.399531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
45190 240
100.0%

납부년도
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2020
82 
2018
80 
2019
78 

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 82
34.2%
2018 80
33.3%
2019 78
32.5%

Length

2023-12-12T22:15:33.509912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:15:33.606681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 82
34.2%
2018 80
33.3%
2019 78
32.5%

세목명
Categorical

Distinct13
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
자동차세
32 
재산세
32 
주민세
31 
등록면허세
30 
지방소득세
25 
Other values (8)
90 

Length

Max length7
Median length5
Mean length4.0791667
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 32
13.3%
재산세 32
13.3%
주민세 31
12.9%
등록면허세 30
12.5%
지방소득세 25
10.4%
취득세 25
10.4%
지역자원시설세 21
8.8%
등록세 18
7.5%
면허세 8
 
3.3%
종합토지세 8
 
3.3%
Other values (3) 10
 
4.2%

Length

2023-12-12T22:15:33.737839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자동차세 32
13.3%
재산세 32
13.3%
주민세 31
12.9%
등록면허세 30
12.5%
지방소득세 25
10.4%
취득세 25
10.4%
지역자원시설세 21
8.8%
등록세 18
7.5%
면허세 8
 
3.3%
종합토지세 8
 
3.3%
Other values (3) 10
 
4.2%

납부매체
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
은행창구
32 
가상계좌
31 
ARS
30 
지자체방문
29 
위택스
25 
Other values (5)
93 

Length

Max length5
Median length4
Mean length3.9291667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
은행창구 32
13.3%
가상계좌 31
12.9%
ARS 30
12.5%
지자체방문 29
12.1%
위택스 25
10.4%
자동화기기 25
10.4%
기타 24
10.0%
인터넷지로 24
10.0%
자동이체 12
 
5.0%
페이사납부 8
 
3.3%

Length

2023-12-12T22:15:33.901036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:15:34.021734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
은행창구 32
13.3%
가상계좌 31
12.9%
ars 30
12.5%
지자체방문 29
12.1%
위택스 25
10.4%
자동화기기 25
10.4%
기타 24
10.0%
인터넷지로 24
10.0%
자동이체 12
 
5.0%
페이사납부 8
 
3.3%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size372.0 B
False
129 
True
111 
ValueCountFrequency (%)
False 129
53.8%
True 111
46.2%
2023-12-12T22:15:34.130705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct184
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3321.5917
Minimum1
Maximum34967
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T22:15:34.242830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q114.25
median390.5
Q33133.75
95-th percentile17934.85
Maximum34967
Range34966
Interquartile range (IQR)3119.5

Descriptive statistics

Standard deviation6644.3885
Coefficient of variation (CV)2.0003628
Kurtosis8.7643868
Mean3321.5917
Median Absolute Deviation (MAD)388.5
Skewness2.9271178
Sum797182
Variance44147899
MonotonicityNot monotonic
2023-12-12T22:15:34.370350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 19
 
7.9%
3 10
 
4.2%
2 6
 
2.5%
4 6
 
2.5%
5 6
 
2.5%
6 4
 
1.7%
316 2
 
0.8%
2297 2
 
0.8%
30933 2
 
0.8%
195 2
 
0.8%
Other values (174) 181
75.4%
ValueCountFrequency (%)
1 19
7.9%
2 6
 
2.5%
3 10
4.2%
4 6
 
2.5%
5 6
 
2.5%
6 4
 
1.7%
7 2
 
0.8%
8 2
 
0.8%
9 2
 
0.8%
10 1
 
0.4%
ValueCountFrequency (%)
34967 1
0.4%
34032 1
0.4%
32637 1
0.4%
30933 2
0.8%
29856 1
0.4%
27041 1
0.4%
23824 1
0.4%
21170 1
0.4%
20386 1
0.4%
19813 1
0.4%

납부금액
Real number (ℝ)

HIGH CORRELATION 

Distinct239
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6282321 × 108
Minimum1440
Maximum1.15337 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T22:15:34.495643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1440
5-th percentile27116
Q11212075
median45815345
Q36.8239106 × 108
95-th percentile4.0157761 × 109
Maximum1.15337 × 1010
Range1.1533699 × 1010
Interquartile range (IQR)6.8117899 × 108

Descriptive statistics

Standard deviation1.8403768 × 109
Coefficient of variation (CV)2.1329709
Kurtosis9.8245524
Mean8.6282321 × 108
Median Absolute Deviation (MAD)45774290
Skewness3.0275887
Sum2.0707757 × 1011
Variance3.3869867 × 1018
MonotonicityNot monotonic
2023-12-12T22:15:34.628805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000 2
 
0.8%
476440 1
 
0.4%
834608420 1
 
0.4%
105658590 1
 
0.4%
450130 1
 
0.4%
3172245550 1
 
0.4%
63496070 1
 
0.4%
4834410 1
 
0.4%
204050 1
 
0.4%
98034560 1
 
0.4%
Other values (229) 229
95.4%
ValueCountFrequency (%)
1440 1
0.4%
3840 1
0.4%
6980 1
0.4%
10000 2
0.8%
15000 1
0.4%
15370 1
0.4%
15450 1
0.4%
18140 1
0.4%
18870 1
0.4%
20920 1
0.4%
ValueCountFrequency (%)
11533700000 1
0.4%
8865993750 1
0.4%
7809333600 1
0.4%
7680695440 1
0.4%
7577229020 1
0.4%
7563464110 1
0.4%
7475241150 1
0.4%
7380426700 1
0.4%
7236261740 1
0.4%
6872903590 1
0.4%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.070833
Minimum0
Maximum91
Zeros69
Zeros (%)28.7%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T22:15:34.764066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q318.25
95-th percentile46.05
Maximum91
Range91
Interquartile range (IQR)18.25

Descriptive statistics

Standard deviation16.29331
Coefficient of variation (CV)1.3498082
Kurtosis4.9723268
Mean12.070833
Median Absolute Deviation (MAD)5
Skewness1.9823117
Sum2897
Variance265.47195
MonotonicityNot monotonic
2023-12-12T22:15:34.877560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 69
28.7%
1 25
 
10.4%
2 11
 
4.6%
3 9
 
3.8%
10 8
 
3.3%
18 7
 
2.9%
17 7
 
2.9%
11 6
 
2.5%
19 6
 
2.5%
5 5
 
2.1%
Other values (40) 87
36.2%
ValueCountFrequency (%)
0 69
28.7%
1 25
 
10.4%
2 11
 
4.6%
3 9
 
3.8%
4 5
 
2.1%
5 5
 
2.1%
6 4
 
1.7%
7 4
 
1.7%
8 4
 
1.7%
9 5
 
2.1%
ValueCountFrequency (%)
91 1
0.4%
89 1
0.4%
83 1
0.4%
54 2
0.8%
53 1
0.4%
52 2
0.8%
50 2
0.8%
49 1
0.4%
47 1
0.4%
46 1
0.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2020-12-31
240 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-31
2nd row2020-12-31
3rd row2020-12-31
4th row2020-12-31
5th row2020-12-31

Common Values

ValueCountFrequency (%)
2020-12-31 240
100.0%

Length

2023-12-12T22:15:34.979943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:15:35.055829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-31 240
100.0%

Interactions

2023-12-12T22:15:32.360008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:15:31.756358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:15:32.039474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:15:32.458925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:15:31.855616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:15:32.139880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:15:32.544179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:15:31.957374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:15:32.260005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:15:35.110336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
납부년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.0000.0000.3270.7280.616
납부매체0.0000.0001.0000.9950.5290.3730.490
납부매체전자고지여부0.0000.0000.9951.0000.2560.1860.164
납부건수0.0000.3270.5290.2561.0000.5800.666
납부금액0.0000.7280.3730.1860.5801.0000.369
납부매체비율0.0000.6160.4900.1640.6660.3691.000
2023-12-12T22:15:35.209590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체세목명납부매체전자고지여부납부년도
납부매체1.0000.0000.9210.000
세목명0.0001.0000.0000.000
납부매체전자고지여부0.9210.0001.0000.000
납부년도0.0000.0000.0001.000
2023-12-12T22:15:35.306320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율납부년도세목명납부매체납부매체전자고지여부
납부건수1.0000.8550.8360.0000.1390.1860.193
납부금액0.8551.0000.6740.0000.4360.1860.137
납부매체비율0.8360.6741.0000.0000.3390.2720.173
납부년도0.0000.0000.0001.0000.0000.0000.000
세목명0.1390.4360.3390.0001.0000.0000.000
납부매체0.1860.1860.2720.0000.0001.0000.921
납부매체전자고지여부0.1930.1370.1730.0000.0000.9211.000

Missing values

2023-12-12T22:15:32.658020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:15:32.805379image/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

시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율데이터기준일자
0전라북도남원시451902018등록면허세ARSN2347644022020-12-31
1전라북도남원시451902018등록면허세ARSY11500002020-12-31
2전라북도남원시451902018자동차세ARSN558114265670472020-12-31
3전라북도남원시451902018자동차세ARSY1194732012020-12-31
4전라북도남원시451902018재산세ARSN42745611530362020-12-31
5전라북도남원시451902018재산세ARSY66968012020-12-31
6전라북도남원시451902018주민세ARSN1221892630102020-12-31
7전라북도남원시451902018주민세ARSY44532002020-12-31
8전라북도남원시451902018지방소득세ARSN38518232032020-12-31
9전라북도남원시451902018지역자원시설세ARSN13946002020-12-31
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율데이터기준일자
230전라북도남원시451902020재산세지자체방문N2412484710360172020-12-31
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