Overview

Dataset statistics

Number of variables10
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory88.0 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description부산광역시_지방세납부현황_20211231
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15079364

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
납부년도 has constant value ""Constant
납부매체전자고지여부 is highly overall correlated with 납부매체High correlation
납부매체 is highly overall correlated with 납부매체전자고지여부High correlation
납부건수 is highly overall correlated with 납부금액 and 1 other fieldsHigh correlation
납부금액 is highly overall correlated with 납부건수 and 2 other fieldsHigh correlation
납부매체비율 is highly overall correlated with 납부건수 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 납부금액High correlation
납부금액 has unique valuesUnique
납부매체비율 has 5 (11.4%) zerosZeros

Reproduction

Analysis started2024-03-13 13:18:17.331136
Analysis finished2024-03-13 13:18:18.615235
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
부산광역시
44 

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 44
100.0%

Length

2024-03-13T22:18:18.680494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:18:18.799212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 44
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
부산광역시
44 

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 44
100.0%

Length

2024-03-13T22:18:18.923173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:18:19.034024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 44
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
26000
44 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26000
2nd row26000
3rd row26000
4th row26000
5th row26000

Common Values

ValueCountFrequency (%)
26000 44
100.0%

Length

2024-03-13T22:18:19.134672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:18:19.236660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26000 44
100.0%

납부년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
2021
44 

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 44
100.0%

Length

2024-03-13T22:18:19.340831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:18:19.483187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 44
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size484.0 B
자동차세
9 
지방소득세
9 
취득세
9 
주민세
8 
담배소비세
5 
Other values (2)
4 

Length

Max length5
Median length4
Mean length3.8863636
Min length3

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row담배소비세
2nd row자동차세
3rd row주민세
4th row지방소득세
5th row취득세

Common Values

ValueCountFrequency (%)
자동차세 9
20.5%
지방소득세 9
20.5%
취득세 9
20.5%
주민세 8
18.2%
담배소비세 5
11.4%
등록세 3
 
6.8%
지방소비세 1
 
2.3%

Length

2024-03-13T22:18:19.621169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:18:19.748526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 9
20.5%
지방소득세 9
20.5%
취득세 9
20.5%
주민세 8
18.2%
담배소비세 5
11.4%
등록세 3
 
6.8%
지방소비세 1
 
2.3%

납부매체
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
기타
6 
은행창구
6 
자동화기기
6 
가상계좌
5 
위택스
5 
Other values (4)
16 

Length

Max length5
Median length4
Mean length3.8863636
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 6
13.6%
은행창구 6
13.6%
자동화기기 6
13.6%
가상계좌 5
11.4%
위택스 5
11.4%
이택스 5
11.4%
인터넷지로 4
9.1%
페이사납부 4
9.1%
지자체방문 3
6.8%

Length

2024-03-13T22:18:19.886825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:18:20.022084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 6
13.6%
은행창구 6
13.6%
자동화기기 6
13.6%
가상계좌 5
11.4%
위택스 5
11.4%
이택스 5
11.4%
인터넷지로 4
9.1%
페이사납부 4
9.1%
지자체방문 3
6.8%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size176.0 B
True
23 
False
21 
ValueCountFrequency (%)
True 23
52.3%
False 21
47.7%
2024-03-13T22:18:20.159961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28030.841
Minimum2
Maximum271978
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-03-13T22:18:20.608196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.15
Q111.5
median103.5
Q3688
95-th percentile181872.55
Maximum271978
Range271976
Interquartile range (IQR)676.5

Descriptive statistics

Standard deviation67533.606
Coefficient of variation (CV)2.4092608
Kurtosis5.5844633
Mean28030.841
Median Absolute Deviation (MAD)100
Skewness2.5259795
Sum1233357
Variance4.5607879 × 109
MonotonicityNot monotonic
2024-03-13T22:18:20.742139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
2 3
 
6.8%
6 2
 
4.5%
4 2
 
4.5%
12 2
 
4.5%
3 1
 
2.3%
60 1
 
2.3%
167641 1
 
2.3%
26 1
 
2.3%
14 1
 
2.3%
150 1
 
2.3%
Other values (29) 29
65.9%
ValueCountFrequency (%)
2 3
6.8%
3 1
 
2.3%
4 2
4.5%
6 2
4.5%
8 1
 
2.3%
9 1
 
2.3%
10 1
 
2.3%
12 2
4.5%
14 1
 
2.3%
18 1
 
2.3%
ValueCountFrequency (%)
271978 1
2.3%
243306 1
2.3%
184384 1
2.3%
167641 1
2.3%
137038 1
2.3%
87111 1
2.3%
81672 1
2.3%
48438 1
2.3%
4359 1
2.3%
3159 1
2.3%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9381879 × 1010
Minimum12870
Maximum1.0573111 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-03-13T22:18:20.879599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12870
5-th percentile24209
Q17043755
median92478670
Q31.4964532 × 1010
95-th percentile2.5337929 × 1011
Maximum1.0573111 × 1012
Range1.057311 × 1012
Interquartile range (IQR)1.4957488 × 1010

Descriptive statistics

Standard deviation1.6868731 × 1011
Coefficient of variation (CV)3.415976
Kurtosis31.107541
Mean4.9381879 × 1010
Median Absolute Deviation (MAD)92442400
Skewness5.3285879
Sum2.1728027 × 1012
Variance2.8455409 × 1022
MonotonicityNot monotonic
2024-03-13T22:18:21.039397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1849400 1
 
2.3%
24890731250 1
 
2.3%
1398334340 1
 
2.3%
91455278120 1
 
2.3%
80298320 1
 
2.3%
19040 1
 
2.3%
38744360 1
 
2.3%
37708454530 1
 
2.3%
14490 1
 
2.3%
53500 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
12870 1
2.3%
14490 1
2.3%
19040 1
2.3%
53500 1
2.3%
159480 1
2.3%
238390 1
2.3%
275060 1
2.3%
1161260 1
2.3%
1849400 1
2.3%
2003550 1
2.3%
ValueCountFrequency (%)
1057311055390 1
2.3%
309352326880 1
2.3%
275269149910 1
2.3%
129336780710 1
2.3%
91455278120 1
2.3%
81540031700 1
2.3%
68041098950 1
2.3%
43614485280 1
2.3%
37708454530 1
2.3%
32135676140 1
2.3%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.454545
Minimum0
Maximum99.88
Zeros5
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-03-13T22:18:21.204549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.02
median0.225
Q323.9925
95-th percentile99.534
Maximum99.88
Range99.88
Interquartile range (IQR)23.9725

Descriptive statistics

Standard deviation36.133776
Coefficient of variation (CV)1.7665402
Kurtosis0.83922832
Mean20.454545
Median Absolute Deviation (MAD)0.22
Skewness1.5798001
Sum900
Variance1305.6498
MonotonicityNot monotonic
2024-03-13T22:18:21.357946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.01 5
 
11.4%
0.0 5
 
11.4%
0.02 4
 
9.1%
0.06 4
 
9.1%
99.38 1
 
2.3%
99.5 1
 
2.3%
0.38 1
 
2.3%
98.58 1
 
2.3%
0.07 1
 
2.3%
1.36 1
 
2.3%
Other values (20) 20
45.5%
ValueCountFrequency (%)
0.0 5
11.4%
0.01 5
11.4%
0.02 4
9.1%
0.06 4
9.1%
0.07 1
 
2.3%
0.09 1
 
2.3%
0.12 1
 
2.3%
0.16 1
 
2.3%
0.29 1
 
2.3%
0.33 1
 
2.3%
ValueCountFrequency (%)
99.88 1
2.3%
99.63 1
2.3%
99.54 1
2.3%
99.5 1
2.3%
99.38 1
2.3%
98.58 1
2.3%
84.6 1
2.3%
63.89 1
2.3%
35.99 1
2.3%
32.49 1
2.3%

Interactions

2024-03-13T22:18:18.109219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:18:17.628109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:18:17.885491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:18:18.205429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:18:17.712663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:18:17.964952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:18:18.306788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:18:17.798563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:18:18.033559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:18:21.442571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
세목명1.0000.0000.0000.0000.6860.580
납부매체0.0001.0001.0000.0000.0000.000
납부매체전자고지여부0.0001.0001.0000.2160.0000.000
납부건수0.0000.0000.2161.0000.2590.970
납부금액0.6860.0000.0000.2591.0000.000
납부매체비율0.5800.0000.0000.9700.0001.000
2024-03-13T22:18:21.551231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체전자고지여부납부매체세목명
납부매체전자고지여부1.0000.9130.000
납부매체0.9131.0000.000
세목명0.0000.0001.000
2024-03-13T22:18:21.674078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율세목명납부매체납부매체전자고지여부
납부건수1.0000.7920.7870.0000.0000.210
납부금액0.7921.0000.8110.5300.0000.000
납부매체비율0.7870.8111.0000.2270.0000.000
세목명0.0000.5300.2271.0000.0000.000
납부매체0.0000.0000.0000.0001.0000.913
납부매체전자고지여부0.2100.0000.0000.0000.9131.000

Missing values

2024-03-13T22:18:18.417772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:18:18.560846image/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
0부산광역시부산광역시260002021담배소비세가상계좌Y818494000.01
1부산광역시부산광역시260002021자동차세가상계좌Y368998985100.42
2부산광역시부산광역시260002021주민세가상계좌Y92750600.01
3부산광역시부산광역시260002021지방소득세가상계좌Y18618652200.02
4부산광역시부산광역시260002021취득세가상계좌Y871114361448528099.54
5부산광역시부산광역시260002021담배소비세기타N22116557984703.7
6부산광역시부산광역시260002021자동차세기타N16230935232688027.27
7부산광역시부산광역시260002021주민세기타N7114003940011.95
8부산광역시부산광역시260002021지방소득세기타N19373716865032.49
9부산광역시부산광역시260002021지방소비세기타N1010573110553901.68
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
34부산광역시부산광역시260002021주민세자동화기기N14105281600.01
35부산광역시부산광역시260002021지방소득세자동화기기N26717693400.02
36부산광역시부산광역시260002021취득세자동화기기N16764112933678071099.88
37부산광역시부산광역시260002021자동차세지자체방문N6084291901.36
38부산광역시부산광역시260002021지방소득세지자체방문N3114368700.07
39부산광역시부산광역시260002021취득세지자체방문N4359318391089098.58
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