Overview

Dataset statistics

Number of variables10
Number of observations420
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.0 KiB
Average record size in memory85.3 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description지방세 개방형 데이터 구축된 자료중 2017년 ~ 2021년도에 대한 경상남도 진주시 지방세 납부현황에 대한 자료제공입니다.
Author경상남도 진주시
URLhttps://www.data.go.kr/data/15080409/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 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 25 (6.0%) zerosZeros

Reproduction

Analysis started2024-04-06 08:22:21.811202
Analysis finished2024-04-06 08:22:24.984789
Duration3.17 seconds
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
경상남도
420 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 420
100.0%

Length

2024-04-06T17:22:25.109394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:22:25.299150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 420
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
진주시
420 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진주시 420
100.0%

Length

2024-04-06T17:22:25.495671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:22:25.699151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진주시 420
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
48170
420 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48170
2nd row48170
3rd row48170
4th row48170
5th row48170

Common Values

ValueCountFrequency (%)
48170 420
100.0%

Length

2024-04-06T17:22:25.905372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:22:26.467998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48170 420
100.0%

납부년도
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2020
88 
2021
84 
2017
83 
2019
83 
2018
82 

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 (%)
2020 88
21.0%
2021 84
20.0%
2017 83
19.8%
2019 83
19.8%
2018 82
19.5%

Length

2024-04-06T17:22:27.093866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:22:27.447768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 88
21.0%
2021 84
20.0%
2017 83
19.8%
2019 83
19.8%
2018 82
19.5%

세목명
Categorical

Distinct14
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
자동차세
53 
재산세
53 
주민세
53 
등록면허세
52 
지방소득세
48 
Other values (9)
161 

Length

Max length7
Median length5
Mean length4.102381
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 53
12.6%
재산세 53
12.6%
주민세 53
12.6%
등록면허세 52
12.4%
지방소득세 48
11.4%
취득세 42
10.0%
지역자원시설세 38
9.0%
등록세 29
6.9%
면허세 22
5.2%
종합토지세 13
 
3.1%
Other values (4) 17
 
4.0%

Length

2024-04-06T17:22:27.727281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자동차세 53
12.6%
재산세 53
12.6%
주민세 53
12.6%
등록면허세 52
12.4%
지방소득세 48
11.4%
취득세 42
10.0%
지역자원시설세 38
9.0%
등록세 29
6.9%
면허세 22
5.2%
종합토지세 13
 
3.1%
Other values (4) 17
 
4.0%

납부매체
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
가상계좌
59 
ARS
58 
기타
49 
지자체방문
48 
은행창구
45 
Other values (5)
161 

Length

Max length5
Median length4
Mean length3.8785714
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가상계좌 59
14.0%
ARS 58
13.8%
기타 49
11.7%
지자체방문 48
11.4%
은행창구 45
10.7%
자동화기기 43
10.2%
위택스 42
10.0%
인터넷지로 38
9.0%
자동이체 20
 
4.8%
페이사납부 18
 
4.3%

Length

2024-04-06T17:22:27.993271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:22:28.245096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가상계좌 59
14.0%
ars 58
13.8%
기타 49
11.7%
지자체방문 48
11.4%
은행창구 45
10.7%
자동화기기 43
10.2%
위택스 42
10.0%
인터넷지로 38
9.0%
자동이체 20
 
4.8%
페이사납부 18
 
4.3%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size552.0 B
False
219 
True
201 
ValueCountFrequency (%)
False 219
52.1%
True 201
47.9%
2024-04-06T17:22:28.583809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct337
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10804.914
Minimum1
Maximum133186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-04-06T17:22:28.882884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q131.75
median1599.5
Q310666.75
95-th percentile56000
Maximum133186
Range133185
Interquartile range (IQR)10635

Descriptive statistics

Standard deviation21648.967
Coefficient of variation (CV)2.0036223
Kurtosis11.443575
Mean10804.914
Median Absolute Deviation (MAD)1597.5
Skewness3.2440066
Sum4538064
Variance4.6867778 × 108
MonotonicityNot monotonic
2024-04-06T17:22:29.199677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 20
 
4.8%
1 12
 
2.9%
4 10
 
2.4%
3 8
 
1.9%
8 6
 
1.4%
12 4
 
1.0%
28 3
 
0.7%
7 3
 
0.7%
10 3
 
0.7%
26 3
 
0.7%
Other values (327) 348
82.9%
ValueCountFrequency (%)
1 12
2.9%
2 20
4.8%
3 8
 
1.9%
4 10
2.4%
5 2
 
0.5%
6 2
 
0.5%
7 3
 
0.7%
8 6
 
1.4%
9 2
 
0.5%
10 3
 
0.7%
ValueCountFrequency (%)
133186 1
0.2%
127512 1
0.2%
123153 1
0.2%
113755 1
0.2%
112328 1
0.2%
103481 1
0.2%
103165 1
0.2%
99751 1
0.2%
98143 1
0.2%
92942 1
0.2%

납부금액
Real number (ℝ)

HIGH CORRELATION 

Distinct419
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.99841 × 109
Minimum250
Maximum6.1702093 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-04-06T17:22:29.489409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum250
5-th percentile30645
Q15738370
median2.2994678 × 108
Q33.794218 × 109
95-th percentile3.0611235 × 1010
Maximum6.1702093 × 1010
Range6.1702093 × 1010
Interquartile range (IQR)3.7884796 × 109

Descriptive statistics

Standard deviation1.0689662 × 1010
Coefficient of variation (CV)2.1386124
Kurtosis8.9089995
Mean4.99841 × 109
Median Absolute Deviation (MAD)2.2992642 × 108
Skewness2.928198
Sum2.0993322 × 1012
Variance1.1426887 × 1020
MonotonicityNot monotonic
2024-04-06T17:22:30.312742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10500 2
 
0.5%
1638630 1
 
0.2%
11681420 1
 
0.2%
1693513310 1
 
0.2%
9240226770 1
 
0.2%
4505549210 1
 
0.2%
36185180 1
 
0.2%
6535754540 1
 
0.2%
19499948380 1
 
0.2%
5548740 1
 
0.2%
Other values (409) 409
97.4%
ValueCountFrequency (%)
250 1
0.2%
10500 2
0.5%
12160 1
0.2%
12480 1
0.2%
13240 1
0.2%
13830 1
0.2%
14490 1
0.2%
15000 1
0.2%
15610 1
0.2%
16030 1
0.2%
ValueCountFrequency (%)
61702093470 1
0.2%
58476107500 1
0.2%
54437647050 1
0.2%
53679261780 1
0.2%
52438340300 1
0.2%
52103117000 1
0.2%
50260833250 1
0.2%
48840978990 1
0.2%
45912725470 1
0.2%
43636707890 1
0.2%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct286
Distinct (%)68.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.428571
Minimum0
Maximum76.83
Zeros25
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-04-06T17:22:30.578701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0975
median5.695
Q319.48
95-th percentile38.0545
Maximum76.83
Range76.83
Interquartile range (IQR)19.3825

Descriptive statistics

Standard deviation14.438267
Coefficient of variation (CV)1.2633484
Kurtosis1.8651743
Mean11.428571
Median Absolute Deviation (MAD)5.665
Skewness1.4353253
Sum4800
Variance208.46356
MonotonicityNot monotonic
2024-04-06T17:22:30.913593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 25
 
6.0%
0.03 15
 
3.6%
0.01 14
 
3.3%
0.02 12
 
2.9%
0.1 10
 
2.4%
0.04 9
 
2.1%
0.08 8
 
1.9%
0.05 8
 
1.9%
0.11 8
 
1.9%
0.09 7
 
1.7%
Other values (276) 304
72.4%
ValueCountFrequency (%)
0.0 25
6.0%
0.01 14
3.3%
0.02 12
2.9%
0.03 15
3.6%
0.04 9
 
2.1%
0.05 8
 
1.9%
0.06 2
 
0.5%
0.07 5
 
1.2%
0.08 8
 
1.9%
0.09 7
 
1.7%
ValueCountFrequency (%)
76.83 1
0.2%
72.15 1
0.2%
66.58 1
0.2%
57.45 1
0.2%
51.65 1
0.2%
51.36 1
0.2%
50.55 1
0.2%
49.98 1
0.2%
49.79 1
0.2%
49.65 1
0.2%

Interactions

2024-04-06T17:22:23.840600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:22:22.571135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:22:23.177292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:22:24.067936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:22:22.773678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:22:23.348322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:22:24.285987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:22:23.008592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:22:23.528698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:22:31.120301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
납부년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.1720.1210.3370.4610.600
납부매체0.0000.1721.0000.9940.5320.4570.528
납부매체전자고지여부0.0000.1210.9941.0000.1280.1670.110
납부건수0.0000.3370.5320.1281.0000.7250.680
납부금액0.0000.4610.4570.1670.7251.0000.454
납부매체비율0.0000.6000.5280.1100.6800.4541.000
2024-04-06T17:22:31.345113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납부매체납부매체전자고지여부납부년도
세목명1.0000.0690.0930.000
납부매체0.0691.0000.9200.000
납부매체전자고지여부0.0930.9201.0000.000
납부년도0.0000.0000.0001.000
2024-04-06T17:22:31.537824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율납부년도세목명납부매체납부매체전자고지여부
납부건수1.0000.8550.8720.0000.1420.1880.097
납부금액0.8551.0000.7100.0000.2040.1550.127
납부매체비율0.8720.7101.0000.0000.2900.1860.083
납부년도0.0000.0000.0001.0000.0000.0000.000
세목명0.1420.2040.2900.0001.0000.0690.093
납부매체0.1880.1550.1860.0000.0691.0000.920
납부매체전자고지여부0.0970.1270.0830.0000.0930.9201.000

Missing values

2024-04-06T17:22:24.579144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:22:24.875144image/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
0경상남도진주시481702017등록면허세ARSN11116386301.47
1경상남도진주시481702017면허세ARSN2472400.03
2경상남도진주시481702017자동차세ARSN376270132575049.98
3경상남도진주시481702017자동차세ARSY42020500.05
4경상남도진주시481702017재산세ARSN269840331310035.84
5경상남도진주시481702017재산세ARSY2968400.03
6경상남도진주시481702017주민세ARSN8541235373011.35
7경상남도진주시481702017주민세ARSY111176400.15
8경상남도진주시481702017지방소득세ARSN79277386801.05
9경상남도진주시481702017지방소득세ARSY2660500.03
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
410경상남도진주시481702021주민세지자체방문N57101257698808.99
411경상남도진주시481702021지방소득세지자체방문N17258379090302.72
412경상남도진주시481702021지역자원시설세지자체방문N5820793000.09
413경상남도진주시481702021취득세지자체방문N108721514642415017.12
414경상남도진주시481702021등록면허세페이사납부Y43967927803.79
415경상남도진주시481702021자동차세페이사납부Y478986368555041.35
416경상남도진주시481702021재산세페이사납부Y383063541976033.07
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