Overview

Dataset statistics

Number of variables8
Number of observations134
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 KiB
Average record size in memory69.0 B

Variable types

Categorical6
Numeric2

Dataset

Description부산광역시해운대구_세원유형별과세현황_20191231
Author부산광역시 해운대구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15078919

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
부과건수 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 부과건수 High correlation
세목명 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
세원 유형명 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
부과건수 has 35 (26.1%) zerosZeros
부과금액 has 35 (26.1%) zerosZeros

Reproduction

Analysis started2023-12-10 16:09:49.481310
Analysis finished2023-12-10 16:09:50.466336
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
부산광역시
134 

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 134
100.0%

Length

2023-12-11T01:09:50.527444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:09:50.613405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 134
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
해운대구
134 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
해운대구 134
100.0%

Length

2023-12-11T01:09:50.702399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:09:50.780112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해운대구 134
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
26350
134 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26350
2nd row26350
3rd row26350
4th row26350
5th row26350

Common Values

ValueCountFrequency (%)
26350 134
100.0%

Length

2023-12-11T01:09:50.853874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:09:50.930196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26350 134
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2017
47 
2019
47 
2018
40 

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 (%)
2017 47
35.1%
2019 47
35.1%
2018 40
29.9%

Length

2023-12-11T01:09:51.010357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:09:51.088480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 47
35.1%
2019 47
35.1%
2018 40
29.9%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
취득세
27 
주민세
27 
자동차세
21 
재산세
15 
지방소득세
12 
Other values (8)
32 

Length

Max length7
Median length3
Mean length3.6716418
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row담배소비세
2nd row교육세
3rd row도시계획세
4th row취득세
5th row취득세

Common Values

ValueCountFrequency (%)
취득세 27
20.1%
주민세 27
20.1%
자동차세 21
15.7%
재산세 15
11.2%
지방소득세 12
9.0%
레저세 8
 
6.0%
등록면허세 6
 
4.5%
지역자원시설세 6
 
4.5%
교육세 3
 
2.2%
체납 3
 
2.2%
Other values (3) 6
 
4.5%

Length

2023-12-11T01:09:51.188896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 27
20.1%
주민세 27
20.1%
자동차세 21
15.7%
재산세 15
11.2%
지방소득세 12
9.0%
레저세 8
 
6.0%
등록면허세 6
 
4.5%
지역자원시설세 6
 
4.5%
교육세 3
 
2.2%
체납 3
 
2.2%
Other values (3) 6
 
4.5%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
주민세(법인균등)
 
3
체납
 
3
등록면허세(등록)
 
3
건축물
 
3
주택(개별)
 
3
Other values (42)
119 

Length

Max length11
Median length8
Mean length6.1791045
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row담배소비세
2nd row교육세
3rd row도시계획세
4th row건축물
5th row주택(개별)

Common Values

ValueCountFrequency (%)
주민세(법인균등) 3
 
2.2%
체납 3
 
2.2%
등록면허세(등록) 3
 
2.2%
건축물 3
 
2.2%
주택(개별) 3
 
2.2%
주택(단독) 3
 
2.2%
기타 3
 
2.2%
항공기 3
 
2.2%
기계장비 3
 
2.2%
주민세(특별징수) 3
 
2.2%
Other values (37) 104
77.6%

Length

2023-12-11T01:09:51.283894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주민세(법인균등 3
 
2.2%
주민세(종합소득 3
 
2.2%
체납 3
 
2.2%
주민세(개인사업 3
 
2.2%
주민세(개인균등 3
 
2.2%
지방소득세(특별징수 3
 
2.2%
지방소득세(법인소득 3
 
2.2%
승용 3
 
2.2%
지방소득세(종합소득 3
 
2.2%
등록면허세(면허 3
 
2.2%
Other values (37) 104
77.6%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct100
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55275.985
Minimum0
Maximum866095
Zeros35
Zeros (%)26.1%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-11T01:09:51.398426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2552.5
Q337882.5
95-th percentile312872.65
Maximum866095
Range866095
Interquartile range (IQR)37882.5

Descriptive statistics

Standard deviation146511.71
Coefficient of variation (CV)2.650549
Kurtosis19.23719
Mean55275.985
Median Absolute Deviation (MAD)2552.5
Skewness4.1557821
Sum7406982
Variance2.146568 × 1010
MonotonicityNot monotonic
2023-12-11T01:09:51.517437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 35
 
26.1%
189 1
 
0.7%
159 1
 
0.7%
2198 1
 
0.7%
7 1
 
0.7%
171 1
 
0.7%
7738 1
 
0.7%
764 1
 
0.7%
3437 1
 
0.7%
866095 1
 
0.7%
Other values (90) 90
67.2%
ValueCountFrequency (%)
0 35
26.1%
2 1
 
0.7%
4 1
 
0.7%
7 1
 
0.7%
81 1
 
0.7%
140 1
 
0.7%
159 1
 
0.7%
171 1
 
0.7%
178 1
 
0.7%
181 1
 
0.7%
ValueCountFrequency (%)
866095 1
0.7%
858693 1
0.7%
857272 1
0.7%
370010 1
0.7%
361922 1
0.7%
361649 1
0.7%
322414 1
0.7%
307735 1
0.7%
299588 1
0.7%
227725 1
0.7%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct100
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0643402 × 1010
Minimum0
Maximum5.3468529 × 1010
Zeros35
Zeros (%)26.1%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-11T01:09:51.635362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.146145 × 108
Q32.0250172 × 1010
95-th percentile4.2434875 × 1010
Maximum5.3468529 × 1010
Range5.3468529 × 1010
Interquartile range (IQR)2.0250172 × 1010

Descriptive statistics

Standard deviation1.5390407 × 1010
Coefficient of variation (CV)1.4460044
Kurtosis-0.093609968
Mean1.0643402 × 1010
Median Absolute Deviation (MAD)6.146145 × 108
Skewness1.1637842
Sum1.4262159 × 1012
Variance2.3686463 × 1020
MonotonicityNot monotonic
2023-12-11T01:09:51.762242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 35
 
26.1%
11957000 1
 
0.7%
207057000 1
 
0.7%
332182000 1
 
0.7%
3062000 1
 
0.7%
759763000 1
 
0.7%
53468529000 1
 
0.7%
8341097000 1
 
0.7%
32733382000 1
 
0.7%
37017918000 1
 
0.7%
Other values (90) 90
67.2%
ValueCountFrequency (%)
0 35
26.1%
410000 1
 
0.7%
3062000 1
 
0.7%
4655000 1
 
0.7%
5279000 1
 
0.7%
11957000 1
 
0.7%
13672000 1
 
0.7%
14903000 1
 
0.7%
16646000 1
 
0.7%
28804000 1
 
0.7%
ValueCountFrequency (%)
53468529000 1
0.7%
48505006000 1
0.7%
47592390000 1
0.7%
46872400000 1
0.7%
43999526000 1
0.7%
42606987000 1
0.7%
42482409000 1
0.7%
42409280000 1
0.7%
40739741000 1
0.7%
38603248000 1
0.7%

Interactions

2023-12-11T01:09:49.890881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:09:49.735116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:09:49.961333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:09:49.815580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:09:51.855779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.188
세목명0.0001.0001.0000.8890.621
세원 유형명0.0001.0001.0001.0000.872
부과건수0.0000.8891.0001.0000.692
부과금액0.1880.6210.8720.6921.000
2023-12-11T01:09:51.953585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세원 유형명세목명
과세년도1.0000.0000.000
세원 유형명0.0001.0000.848
세목명0.0000.8481.000
2023-12-11T01:09:52.044281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액과세년도세목명세원 유형명
부과건수1.0000.8670.0000.6870.824
부과금액0.8671.0000.1080.3090.441
과세년도0.0000.1081.0000.0000.000
세목명0.6870.3090.0001.0000.848
세원 유형명0.8240.4410.0000.8481.000

Missing values

2023-12-11T01:09:50.319749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:09:50.424150image/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

시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
0부산광역시해운대구263502017담배소비세담배소비세00
1부산광역시해운대구263502017교육세교육세85727236596627000
2부산광역시해운대구263502017도시계획세도시계획세00
3부산광역시해운대구263502017취득세건축물472947592390000
4부산광역시해운대구263502017취득세주택(개별)129610988976000
5부산광역시해운대구263502017취득세주택(단독)770942409280000
6부산광역시해운대구263502017취득세기타240577269000
7부산광역시해운대구263502017취득세항공기00
8부산광역시해운대구263502017취득세기계장비2410000
9부산광역시해운대구263502017취득세차량2152350617000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
124부산광역시해운대구263502019레저세경륜00
125부산광역시해운대구263502019레저세경마00
126부산광역시해운대구263502019자동차세자동차세(주행)00
127부산광역시해운대구263502019자동차세3륜이하136716646000
128부산광역시해운대구263502019자동차세특수123940869000
129부산광역시해운대구263502019자동차세화물16457410932000
130부산광역시해운대구263502019자동차세승합4419226994000
131부산광역시해운대구263502019자동차세기타승용45728804000
132부산광역시해운대구263502019자동차세승용22399732898713000
133부산광역시해운대구263502019체납체납36164920417542000