Overview

Dataset statistics

Number of variables9
Number of observations35
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory81.8 B

Variable types

Categorical5
Numeric4

Dataset

Description과세액 중 비과세액과 감면액이 차지하는 비율 현화에 대한 데이터로 시도명, 시군구명, 자치단체코드, 세목명, 과세년도, 비과세금액, 감면금액, 부과금액, 비과세감면율의 항목을 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15079607

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
비과세금액 is highly overall correlated with 감면금액 and 2 other fieldsHigh correlation
감면금액 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
부과금액 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
비과세감면율(퍼센트) is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 감면금액 and 2 other fieldsHigh correlation
비과세금액 has 1 (2.9%) missing valuesMissing
감면금액 has unique valuesUnique
부과금액 has unique valuesUnique
비과세금액 has 4 (11.4%) zerosZeros
부과금액 has 1 (2.9%) zerosZeros
비과세감면율(퍼센트) has 4 (11.4%) zerosZeros

Reproduction

Analysis started2023-12-10 23:04:43.537608
Analysis finished2023-12-10 23:04:45.675542
Duration2.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
경상남도
35 

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 35
100.0%

Length

2023-12-11T08:04:45.752038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:45.872494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 35
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
김해시
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
김해시 35
100.0%

Length

2023-12-11T08:04:46.007095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:46.099622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김해시 35
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
48250
35 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48250
2nd row48250
3rd row48250
4th row48250
5th row48250

Common Values

ValueCountFrequency (%)
48250 35
100.0%

Length

2023-12-11T08:04:46.214812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:46.320940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48250 35
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
재산세
5 
주민세
5 
자동차세
5 
등록면허세
5 
지역자원시설세
5 
Other values (4)
10 

Length

Max length7
Median length5
Mean length4.0857143
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 5
14.3%
주민세 5
14.3%
자동차세 5
14.3%
등록면허세 5
14.3%
지역자원시설세 5
14.3%
취등록세 3
8.6%
교육세 3
8.6%
등록세 2
 
5.7%
취득세 2
 
5.7%

Length

2023-12-11T08:04:46.449619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:46.602650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 5
14.3%
주민세 5
14.3%
자동차세 5
14.3%
등록면허세 5
14.3%
지역자원시설세 5
14.3%
취등록세 3
8.6%
교육세 3
8.6%
등록세 2
 
5.7%
취득세 2
 
5.7%

과세년도
Categorical

Distinct5
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2020
8 
2021
8 
2019
7 
2017
6 
2018
6 

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 8
22.9%
2021 8
22.9%
2019 7
20.0%
2017 6
17.1%
2018 6
17.1%

Length

2023-12-11T08:04:46.770960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:46.879338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 8
22.9%
2021 8
22.9%
2019 7
20.0%
2017 6
17.1%
2018 6
17.1%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct31
Distinct (%)91.2%
Missing1
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean5.6925352 × 109
Minimum0
Maximum3.8889449 × 1010
Zeros4
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-11T08:04:47.004004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q133882500
median4.29252 × 108
Q37.4330898 × 109
95-th percentile2.8359473 × 1010
Maximum3.8889449 × 1010
Range3.8889449 × 1010
Interquartile range (IQR)7.3992072 × 109

Descriptive statistics

Standard deviation1.0478189 × 1010
Coefficient of variation (CV)1.8406893
Kurtosis2.9039584
Mean5.6925352 × 109
Median Absolute Deviation (MAD)4.163995 × 108
Skewness1.9708708
Sum1.935462 × 1011
Variance1.0979244 × 1020
MonotonicityNot monotonic
2023-12-11T08:04:47.129668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 4
 
11.4%
22893860000 1
 
2.9%
69752000 1
 
2.9%
704479000 1
 
2.9%
209098000 1
 
2.9%
260545000 1
 
2.9%
7909215000 1
 
2.9%
11300000 1
 
2.9%
38889449000 1
 
2.9%
682988000 1
 
2.9%
Other values (21) 21
60.0%
ValueCountFrequency (%)
0 4
11.4%
7414000 1
 
2.9%
11200000 1
 
2.9%
11300000 1
 
2.9%
14405000 1
 
2.9%
21926000 1
 
2.9%
69752000 1
 
2.9%
106970000 1
 
2.9%
120910000 1
 
2.9%
123550000 1
 
2.9%
ValueCountFrequency (%)
38889449000 1
2.9%
30666315000 1
2.9%
27117327000 1
2.9%
24649514000 1
2.9%
22893860000 1
2.9%
12919750000 1
2.9%
8386322000 1
2.9%
8120920000 1
2.9%
7909215000 1
2.9%
6004714000 1
2.9%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5108265 × 109
Minimum5000
Maximum3.8510868 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-11T08:04:47.292152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5000
5-th percentile8400
Q12.607365 × 108
median8.05918 × 108
Q37.4123045 × 109
95-th percentile3.4526438 × 1010
Maximum3.8510868 × 1010
Range3.8510863 × 1010
Interquartile range (IQR)7.151568 × 109

Descriptive statistics

Standard deviation1.1982633 × 1010
Coefficient of variation (CV)1.8404165
Kurtosis2.3724039
Mean6.5108265 × 109
Median Absolute Deviation (MAD)7.73429 × 108
Skewness1.9768445
Sum2.2787893 × 1011
Variance1.4358349 × 1020
MonotonicityNot monotonic
2023-12-11T08:04:47.457372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
8004329000 1
 
2.9%
69108000 1
 
2.9%
86265000 1
 
2.9%
7493575000 1
 
2.9%
964094000 1
 
2.9%
38510868000 1
 
2.9%
2043442000 1
 
2.9%
477979000 1
 
2.9%
281448000 1
 
2.9%
9000 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
5000 1
2.9%
7000 1
2.9%
9000 1
2.9%
2879000 1
2.9%
54365000 1
2.9%
67944000 1
2.9%
69108000 1
2.9%
86265000 1
2.9%
246992000 1
2.9%
274481000 1
2.9%
ValueCountFrequency (%)
38510868000 1
2.9%
36263362000 1
2.9%
33782042000 1
2.9%
32765086000 1
2.9%
32126075000 1
2.9%
8299448000 1
2.9%
8004329000 1
2.9%
7515433000 1
2.9%
7493575000 1
2.9%
7331034000 1
2.9%

부과금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6749351 × 1010
Minimum0
Maximum2.71 × 1011
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-11T08:04:47.618082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.8680559 × 109
Q11.7015099 × 1010
median6.9147385 × 1010
Q31.055 × 1011
95-th percentile2.534 × 1011
Maximum2.71 × 1011
Range2.71 × 1011
Interquartile range (IQR)8.8484901 × 1010

Descriptive statistics

Standard deviation7.8272314 × 1010
Coefficient of variation (CV)1.0198433
Kurtosis0.76206493
Mean7.6749351 × 1010
Median Absolute Deviation (MAD)5.2028489 × 1010
Skewness1.2527201
Sum2.6862273 × 1012
Variance6.1265552 × 1021
MonotonicityNot monotonic
2023-12-11T08:04:47.752815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
101000000000 1
 
2.9%
16194768000 1
 
2.9%
163496000 1
 
2.9%
122000000000 1
 
2.9%
17118896000 1
 
2.9%
201000000000 1
 
2.9%
78097902000 1
 
2.9%
17742018000 1
 
2.9%
16812415000 1
 
2.9%
75048659000 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
0 1
2.9%
163496000 1
2.9%
14027153000 1
2.9%
15262235000 1
2.9%
15961688000 1
2.9%
16179940000 1
2.9%
16194768000 1
2.9%
16812415000 1
2.9%
16949969000 1
2.9%
17080229000 1
2.9%
ValueCountFrequency (%)
271000000000 1
2.9%
266000000000 1
2.9%
248000000000 1
2.9%
202000000000 1
2.9%
201000000000 1
2.9%
127000000000 1
2.9%
122000000000 1
2.9%
118000000000 1
2.9%
110000000000 1
2.9%
101000000000 1
2.9%

비과세감면율(퍼센트)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.836571
Minimum0
Maximum52.76
Zeros4
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-11T08:04:47.879254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.61
median5.58
Q316.73
95-th percentile32.996
Maximum52.76
Range52.76
Interquartile range (IQR)14.12

Descriptive statistics

Standard deviation13.106456
Coefficient of variation (CV)1.2094652
Kurtosis1.8344963
Mean10.836571
Median Absolute Deviation (MAD)4.41
Skewness1.5437662
Sum379.28
Variance171.77918
MonotonicityNot monotonic
2023-12-11T08:04:48.020563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 4
 
11.4%
30.54 1
 
2.9%
2.82 1
 
2.9%
52.76 1
 
2.9%
31.19 1
 
2.9%
5.7 1
 
2.9%
25.65 1
 
2.9%
2.94 1
 
2.9%
5.74 1
 
2.9%
2.97 1
 
2.9%
Other values (22) 22
62.9%
ValueCountFrequency (%)
0.0 4
11.4%
0.93 1
 
2.9%
1.13 1
 
2.9%
1.17 1
 
2.9%
2.39 1
 
2.9%
2.59 1
 
2.9%
2.63 1
 
2.9%
2.72 1
 
2.9%
2.82 1
 
2.9%
2.94 1
 
2.9%
ValueCountFrequency (%)
52.76 1
2.9%
37.21 1
2.9%
31.19 1
2.9%
30.54 1
2.9%
29.34 1
2.9%
29.08 1
2.9%
25.65 1
2.9%
19.22 1
2.9%
18.02 1
2.9%
15.44 1
2.9%

Interactions

2023-12-11T08:04:45.009886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:43.806572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:44.190629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:44.602448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:45.102629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:43.910018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:44.288413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:44.706542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:45.223701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:44.020686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:44.397832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:44.799008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:45.328776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:44.109537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:44.507117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:44.915352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:04:48.155218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율(퍼센트)
세목명1.0000.0000.6450.7780.8730.853
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.6450.0001.0000.9400.8770.970
감면금액0.7780.0000.9401.0000.7650.896
부과금액0.8730.0000.8770.7651.0000.818
비과세감면율(퍼센트)0.8530.0000.9700.8960.8181.000
2023-12-11T08:04:48.269031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2023-12-11T08:04:48.377474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율(퍼센트)세목명과세년도
비과세금액1.0000.7200.5770.6770.3680.000
감면금액0.7201.0000.7610.6590.5550.000
부과금액0.5770.7611.0000.3390.6220.000
비과세감면율(퍼센트)0.6770.6590.3391.0000.6240.000
세목명0.3680.5550.6220.6241.0000.000
과세년도0.0000.0000.0000.0000.0001.000

Missing values

2023-12-11T08:04:45.478939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:04:45.617866image/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

시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율(퍼센트)
0경상남도김해시48250재산세201722893860000800432900010100000000030.54
1경상남도김해시48250주민세201712091000069108000161947680001.17
2경상남도김해시48250취등록세201783863220003626336200024800000000018.02
3경상남도김해시48250자동차세20176303500001579347000839657920002.63
4경상남도김해시48250등록면허세201714405000805918000185237550004.43
5경상남도김해시48250지역자원시설세2017597395000373834000140271530006.92
6경상남도김해시48250재산세201824649514000751543300011000000000029.34
7경상남도김해시48250주민세201812355000067944000169499690001.13
8경상남도김해시48250취등록세201860047140003276508600020200000000019.22
9경상남도김해시48250자동차세20186392360001549393000804811930002.72
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율(퍼센트)
25경상남도김해시48250등록면허세202021926000477979000177420180002.82
26경상남도김해시48250지역자원시설세2020682988000281448000168124150005.74
27경상남도김해시48250교육세202109000750486590000.0
28경상남도김해시48250등록세2021<NA>287900000.0
29경상남도김해시48250재산세202138889449000829944800012700000000037.21
30경상남도김해시48250주민세202111300000972880000174281170005.65
31경상남도김해시48250취득세202179092150003212607500026600000000015.04
32경상남도김해시48250자동차세20212605450002029740000884796460002.59
33경상남도김해시48250등록면허세2021209098000448723000182720120003.6
34경상남도김해시48250지역자원시설세2021704479000274481000170802290005.73