Overview

Dataset statistics

Number of variables8
Number of observations181
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory68.7 B

Variable types

Categorical6
Numeric2

Dataset

Description부산광역시해운대구_세원유형별과세현황_20201231
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 부과건수High 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 48 (26.5%) zerosZeros
부과금액 has 49 (27.1%) zerosZeros

Reproduction

Analysis started2023-12-10 16:09:44.144947
Analysis finished2023-12-10 16:09:45.162069
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
부산광역시
181 

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 181
100.0%

Length

2023-12-11T01:09:45.246133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:09:45.341697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 181
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
해운대구
181 

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 181
100.0%

Length

2023-12-11T01:09:45.438051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:09:45.572213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해운대구 181
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
26350
181 

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 181
100.0%

Length

2023-12-11T01:09:45.713546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:09:45.834478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26350 181
100.0%

과세년도
Categorical

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2017
47 
2019
47 
2020
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
26.0%
2019 47
26.0%
2020 47
26.0%
2018 40
22.1%

Length

2023-12-11T01:09:45.954643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:09:46.094955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 47
26.0%
2019 47
26.0%
2020 47
26.0%
2018 40
22.1%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
취득세
36 
주민세
36 
자동차세
28 
재산세
20 
지방소득세
16 
Other values (8)
45 

Length

Max length7
Median length3
Mean length3.6740331
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 36
19.9%
주민세 36
19.9%
자동차세 28
15.5%
재산세 20
11.0%
지방소득세 16
8.8%
레저세 12
 
6.6%
등록면허세 8
 
4.4%
지역자원시설세 8
 
4.4%
교육세 4
 
2.2%
체납 4
 
2.2%
Other values (3) 9
 
5.0%

Length

2023-12-11T01:09:46.241346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 36
19.9%
주민세 36
19.9%
자동차세 28
15.5%
재산세 20
11.0%
지방소득세 16
8.8%
레저세 12
 
6.6%
등록면허세 8
 
4.4%
지역자원시설세 8
 
4.4%
교육세 4
 
2.2%
체납 4
 
2.2%
Other values (3) 9
 
5.0%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
주민세(법인균등)
 
4
체납
 
4
등록면허세(등록)
 
4
건축물
 
4
주택(개별)
 
4
Other values (42)
161 

Length

Max length11
Median length8
Mean length6.1436464
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주민세(법인균등) 4
 
2.2%
체납 4
 
2.2%
등록면허세(등록) 4
 
2.2%
건축물 4
 
2.2%
주택(개별) 4
 
2.2%
주택(단독) 4
 
2.2%
기타 4
 
2.2%
항공기 4
 
2.2%
기계장비 4
 
2.2%
주민세(특별징수) 4
 
2.2%
Other values (37) 141
77.9%

Length

2023-12-11T01:09:46.381823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주민세(법인균등 4
 
2.2%
주민세(종합소득 4
 
2.2%
체납 4
 
2.2%
주민세(개인사업 4
 
2.2%
주민세(개인균등 4
 
2.2%
지방소득세(특별징수 4
 
2.2%
지방소득세(법인소득 4
 
2.2%
승용 4
 
2.2%
지방소득세(종합소득 4
 
2.2%
등록면허세(면허 4
 
2.2%
Other values (37) 141
77.9%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct132
Distinct (%)72.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55326.591
Minimum0
Maximum919855
Zeros48
Zeros (%)26.5%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T01:09:46.553299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2566
Q337885
95-th percentile322414
Maximum919855
Range919855
Interquartile range (IQR)37885

Descriptive statistics

Standard deviation147437.26
Coefficient of variation (CV)2.6648534
Kurtosis19.789146
Mean55326.591
Median Absolute Deviation (MAD)2566
Skewness4.2155761
Sum10014113
Variance2.1737744 × 1010
MonotonicityNot monotonic
2023-12-11T01:09:46.724092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 48
 
26.5%
4 2
 
1.1%
2 2
 
1.1%
782 1
 
0.6%
5582 1
 
0.6%
51694 1
 
0.6%
38434 1
 
0.6%
82430 1
 
0.6%
322414 1
 
0.6%
1239 1
 
0.6%
Other values (122) 122
67.4%
ValueCountFrequency (%)
0 48
26.5%
2 2
 
1.1%
4 2
 
1.1%
7 1
 
0.6%
81 1
 
0.6%
131 1
 
0.6%
136 1
 
0.6%
140 1
 
0.6%
159 1
 
0.6%
171 1
 
0.6%
ValueCountFrequency (%)
919855 1
0.6%
866095 1
0.6%
858693 1
0.6%
857272 1
0.6%
370010 1
0.6%
361922 1
0.6%
361649 1
0.6%
341535 1
0.6%
332446 1
0.6%
322414 1
0.6%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct133
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2551548 × 1010
Minimum0
Maximum2.51639 × 1011
Zeros49
Zeros (%)27.1%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T01:09:46.878367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5.77269 × 108
Q32.1408494 × 1010
95-th percentile4.3999526 × 1010
Maximum2.51639 × 1011
Range2.51639 × 1011
Interquartile range (IQR)2.1408494 × 1010

Descriptive statistics

Standard deviation2.4677287 × 1010
Coefficient of variation (CV)1.9660752
Kurtosis48.496395
Mean1.2551548 × 1010
Median Absolute Deviation (MAD)5.77269 × 108
Skewness5.5204197
Sum2.2718302 × 1012
Variance6.0896849 × 1020
MonotonicityNot monotonic
2023-12-11T01:09:47.031101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49
 
27.1%
1489598000 1
 
0.6%
32898713000 1
 
0.6%
28804000 1
 
0.6%
226994000 1
 
0.6%
410932000 1
 
0.6%
40869000 1
 
0.6%
16646000 1
 
0.6%
86436000 1
 
0.6%
15735085000 1
 
0.6%
Other values (123) 123
68.0%
ValueCountFrequency (%)
0 49
27.1%
410000 1
 
0.6%
710000 1
 
0.6%
3062000 1
 
0.6%
4655000 1
 
0.6%
5279000 1
 
0.6%
11957000 1
 
0.6%
13672000 1
 
0.6%
14903000 1
 
0.6%
16646000 1
 
0.6%
ValueCountFrequency (%)
251639000000 1
0.6%
76921357000 1
0.6%
68805234000 1
0.6%
66602836000 1
0.6%
57486169000 1
0.6%
53468529000 1
0.6%
48505006000 1
0.6%
47592390000 1
0.6%
46872400000 1
0.6%
43999526000 1
0.6%

Interactions

2023-12-11T01:09:44.678931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:09:44.439545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:09:44.799446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:09:44.548955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:09:47.129687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.058
세목명0.0001.0001.0000.8340.427
세원 유형명0.0001.0001.0000.9770.709
부과건수0.0000.8340.9771.0000.277
부과금액0.0580.4270.7090.2771.000
2023-12-11T01:09:47.228496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세원 유형명세목명
과세년도1.0000.0000.000
세원 유형명0.0001.0000.893
세목명0.0000.8931.000
2023-12-11T01:09:47.308102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액과세년도세목명세원 유형명
부과건수1.0000.8710.0000.5970.756
부과금액0.8711.0000.0460.2410.364
과세년도0.0000.0461.0000.0000.000
세목명0.5970.2410.0001.0000.893
세원 유형명0.7560.3640.0000.8931.000

Missing values

2023-12-11T01:09:44.946832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:09:45.098618image/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
171부산광역시해운대구263502020레저세경륜00
172부산광역시해운대구263502020레저세경마00
173부산광역시해운대구263502020자동차세자동차세(주행)00
174부산광역시해운대구263502020자동차세3륜이하165719061000
175부산광역시해운대구263502020자동차세특수127943532000
176부산광역시해운대구263502020자동차세화물16282402231000
177부산광역시해운대구263502020자동차세승합4300221054000
178부산광역시해운대구263502020자동차세기타승용80653529000
179부산광역시해운대구263502020자동차세승용22689733212280000
180부산광역시해운대구263502020체납체납34153521408494000