Overview

Dataset statistics

Number of variables9
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory83.1 B

Variable types

Categorical5
Numeric4

Dataset

Description부산광역시중구_지방세비과감면율현황_20211231
Author부산광역시 중구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15078410

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 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
세목명 is highly overall correlated with 비과세감면율High correlation
부과금액 has unique valuesUnique
비과세금액 has 2 (7.7%) zerosZeros
비과세감면율 has 2 (7.7%) zerosZeros

Reproduction

Analysis started2023-12-10 16:12:17.567519
Analysis finished2023-12-10 16:12:19.418045
Duration1.85 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
부산광역시
26 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 26
100.0%

Length

2023-12-11T01:12:19.507114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:12:19.631997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 26
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
중구
26 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 26
100.0%

Length

2023-12-11T01:12:19.750836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:12:19.852185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 26
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
26110
26 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26110
2nd row26110
3rd row26110
4th row26110
5th row26110

Common Values

ValueCountFrequency (%)
26110 26
100.0%

Length

2023-12-11T01:12:19.945260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:12:20.052202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26110 26
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size340.0 B
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
등록면허세
4 
Other values (2)
6 

Length

Max length7
Median length3
Mean length4.0769231
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 4
15.4%
주민세 4
15.4%
취득세 4
15.4%
자동차세 4
15.4%
등록면허세 4
15.4%
지역자원시설세 4
15.4%
교육세 2
7.7%

Length

2023-12-11T01:12:20.193011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:12:20.364053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 4
15.4%
주민세 4
15.4%
취득세 4
15.4%
자동차세 4
15.4%
등록면허세 4
15.4%
지역자원시설세 4
15.4%
교육세 2
7.7%

과세년도
Categorical

Distinct4
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size340.0 B
2020
7 
2021
7 
2018
6 
2019
6 

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 7
26.9%
2021 7
26.9%
2018 6
23.1%
2019 6
23.1%

Length

2023-12-11T01:12:20.507102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:12:20.617291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 7
26.9%
2021 7
26.9%
2018 6
23.1%
2019 6
23.1%

비과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3860355 × 109
Minimum0
Maximum8.193882 × 109
Zeros2
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T01:12:20.745668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7313250
Q157476500
median1.041795 × 108
Q37.216605 × 108
95-th percentile7.435627 × 109
Maximum8.193882 × 109
Range8.193882 × 109
Interquartile range (IQR)6.64184 × 108

Descriptive statistics

Standard deviation2.6147709 × 109
Coefficient of variation (CV)1.8865107
Kurtosis2.4193205
Mean1.3860355 × 109
Median Absolute Deviation (MAD)1.041795 × 108
Skewness2.00577
Sum3.6036924 × 1010
Variance6.8370267 × 1018
MonotonicityNot monotonic
2023-12-11T01:12:20.908695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 2
 
7.7%
6389400000 1
 
3.8%
656744000 1
 
3.8%
105814000 1
 
3.8%
41019000 1
 
3.8%
60497000 1
 
3.8%
512407000 1
 
3.8%
731514000 1
 
3.8%
8193882000 1
 
3.8%
102545000 1
 
3.8%
Other values (15) 15
57.7%
ValueCountFrequency (%)
0 2
7.7%
29253000 1
3.8%
29783000 1
3.8%
31870000 1
3.8%
41019000 1
3.8%
57387000 1
3.8%
57745000 1
3.8%
59264000 1
3.8%
60497000 1
3.8%
99989000 1
3.8%
ValueCountFrequency (%)
8193882000 1
3.8%
7535291000 1
3.8%
7136635000 1
3.8%
6389400000 1
3.8%
1454774000 1
3.8%
731514000 1
3.8%
722554000 1
3.8%
718980000 1
3.8%
711794000 1
3.8%
656744000 1
3.8%

감면금액
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.4466838 × 108
Minimum1000
Maximum4.604019 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T01:12:21.060830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile942750
Q128760000
median1.68143 × 108
Q31.384137 × 109
95-th percentile3.8377468 × 109
Maximum4.604019 × 109
Range4.604018 × 109
Interquartile range (IQR)1.355377 × 109

Descriptive statistics

Standard deviation1.3487728 × 109
Coefficient of variation (CV)1.5968075
Kurtosis2.1228468
Mean8.4466838 × 108
Median Absolute Deviation (MAD)1.475995 × 108
Skewness1.7599769
Sum2.1961378 × 1010
Variance1.8191881 × 1018
MonotonicityNot monotonic
2023-12-11T01:12:21.211034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1000 2
 
7.7%
1319028000 1
 
3.8%
180730000 1
 
3.8%
29303000 1
 
3.8%
3768000 1
 
3.8%
147485000 1
 
3.8%
2868049000 1
 
3.8%
168177000 1
 
3.8%
1405840000 1
 
3.8%
28119000 1
 
3.8%
Other values (15) 15
57.7%
ValueCountFrequency (%)
1000 2
7.7%
3768000 1
3.8%
11655000 1
3.8%
12968000 1
3.8%
28119000 1
3.8%
28579000 1
3.8%
29303000 1
3.8%
46147000 1
3.8%
91766000 1
3.8%
147485000 1
3.8%
ValueCountFrequency (%)
4604019000 1
3.8%
4087094000 1
3.8%
3089705000 1
3.8%
2868049000 1
3.8%
1485154000 1
3.8%
1477937000 1
3.8%
1405840000 1
3.8%
1319028000 1
3.8%
192183000 1
3.8%
186811000 1
3.8%

부과금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.1256568 × 109
Minimum2.696304 × 109
Maximum2.7973028 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T01:12:21.349220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.696304 × 109
5-th percentile2.7150318 × 109
Q13.176552 × 109
median4.302417 × 109
Q31.7423128 × 1010
95-th percentile2.3973829 × 1010
Maximum2.7973028 × 1010
Range2.5276724 × 1010
Interquartile range (IQR)1.4246576 × 1010

Descriptive statistics

Standard deviation8.4949668 × 109
Coefficient of variation (CV)0.93088826
Kurtosis-0.60845079
Mean9.1256568 × 109
Median Absolute Deviation (MAD)1.5575145 × 109
Skewness1.0399696
Sum2.3726708 × 1011
Variance7.2164461 × 1019
MonotonicityNot monotonic
2023-12-11T01:12:21.477403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
17752846000 1
 
3.8%
4297927000 1
 
3.8%
3576466000 1
 
3.8%
3153230000 1
 
3.8%
2711238000 1
 
3.8%
27973028000 1
 
3.8%
4691175000 1
 
3.8%
22216338000 1
 
3.8%
6658925000 1
 
3.8%
3585510000 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
2696304000 1
3.8%
2711238000 1
3.8%
2726413000 1
3.8%
2763392000 1
3.8%
3096094000 1
3.8%
3122969000 1
3.8%
3153230000 1
3.8%
3246518000 1
3.8%
3266920000 1
3.8%
3469210000 1
3.8%
ValueCountFrequency (%)
27973028000 1
3.8%
24559659000 1
3.8%
22216338000 1
3.8%
21179383000 1
3.8%
19834375000 1
3.8%
19691725000 1
3.8%
17752846000 1
3.8%
16433972000 1
3.8%
6658925000 1
3.8%
5931171000 1
3.8%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.187692
Minimum0
Maximum43.75
Zeros2
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T01:12:21.604523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3075
Q13.8325
median8.32
Q321.12
95-th percentile43.3675
Maximum43.75
Range43.75
Interquartile range (IQR)17.2875

Descriptive statistics

Standard deviation14.724622
Coefficient of variation (CV)0.96951015
Kurtosis-0.32935292
Mean15.187692
Median Absolute Deviation (MAD)7.705
Skewness0.93351452
Sum394.88
Variance216.81449
MonotonicityNot monotonic
2023-12-11T01:12:21.730888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.0 2
 
7.7%
43.42 1
 
3.8%
19.49 1
 
3.8%
3.78 1
 
3.8%
1.42 1
 
3.8%
7.67 1
 
3.8%
12.08 1
 
3.8%
19.18 1
 
3.8%
43.21 1
 
3.8%
3.64 1
 
3.8%
Other values (15) 15
57.7%
ValueCountFrequency (%)
0.0 2
7.7%
1.23 1
3.8%
1.31 1
3.8%
1.42 1
3.8%
3.64 1
3.8%
3.78 1
3.8%
3.99 1
3.8%
4.0 1
3.8%
4.47 1
3.8%
7.67 1
3.8%
ValueCountFrequency (%)
43.75 1
3.8%
43.42 1
3.8%
43.21 1
3.8%
42.59 1
3.8%
29.2 1
3.8%
22.91 1
3.8%
21.15 1
3.8%
21.03 1
3.8%
20.77 1
3.8%
19.49 1
3.8%

Interactions

2023-12-11T01:12:18.822350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:17.840710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:18.179872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:18.493619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:18.909562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:17.939839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:18.251896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:18.580340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:19.004690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:18.029605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:18.323629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:18.656603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:19.112898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:18.105141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:18.406802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:18.743028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:12:21.828796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.4490.8640.8670.949
과세년도0.0001.0000.0000.0000.0810.000
비과세금액0.4490.0001.0000.8220.8170.735
감면금액0.8640.0000.8221.0000.9820.852
부과금액0.8670.0810.8170.9821.0000.923
비과세감면율0.9490.0000.7350.8520.9231.000
2023-12-11T01:12:21.939850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2023-12-11T01:12:22.045786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세년도
비과세금액1.0000.7990.6390.9100.2750.000
감면금액0.7991.0000.6070.9120.4470.000
부과금액0.6390.6071.0000.5450.4820.000
비과세감면율0.9100.9120.5451.0000.6500.000
세목명0.2750.4470.4820.6501.0000.000
과세년도0.0000.0000.0000.0000.0001.000

Missing values

2023-12-11T01:12:19.216490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:12:19.354247image/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
0부산광역시중구26110재산세2018638940000013190280001775284600043.42
1부산광역시중구26110주민세2018722554000192183000432538300021.15
2부산광역시중구26110취득세201871179400040870940001643397200029.2
3부산광역시중구26110자동차세20185926400017172600027633920008.36
4부산광역시중구26110등록면허세2018318700009176600030960940003.99
5부산광역시중구26110지역자원시설세2018999890004614700032669200004.47
6부산광역시중구26110재산세2019713663500014779370001969172500043.75
7부산광역시중구26110주민세2019718980000186811000430690700021.03
8부산광역시중구26110취득세201949660000046040190002455965900020.77
9부산광역시중구26110자동차세20195774500016810900027264130008.28
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
16부산광역시중구26110자동차세20205738700015702400026963040007.95
17부산광역시중구26110등록면허세2020292530001165500031229690001.31
18부산광역시중구26110지역자원시설세20201025450002811900035855100003.64
19부산광역시중구26110교육세20210100066589250000.0
20부산광역시중구26110재산세2021819388200014058400002221633800043.21
21부산광역시중구26110주민세2021731514000168177000469117500019.18
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