Overview

Dataset statistics

Number of variables8
Number of observations265
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.7 KiB
Average record size in memory68.5 B

Variable types

Categorical5
Numeric3

Dataset

Description울산광역시 남구 세원유형별 과세 현황에 대한 데이터로 시도명, 시군구명, 자치단체코드, 과세년도, 세목명, 세원 유형명 등의 항목을 제공합니다.
Author울산광역시 남구
URLhttps://www.data.go.kr/data/15078504/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
세원 유형명 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
부과건수 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 부과건수High correlation
부과건수 has 64 (24.2%) zerosZeros
부과금액 has 65 (24.5%) zerosZeros

Reproduction

Analysis started2024-04-29 22:43:28.860850
Analysis finished2024-04-29 22:43:31.209982
Duration2.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
울산광역시
265 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
울산광역시 265
100.0%

Length

2024-04-30T07:43:31.266706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:43:31.345280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울산광역시 265
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
남구
265 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남구 265
100.0%

Length

2024-04-30T07:43:31.427569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:43:31.533543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남구 265
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
31140
265 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row31140
2nd row31140
3rd row31140
4th row31140
5th row31140

Common Values

ValueCountFrequency (%)
31140 265
100.0%

Length

2024-04-30T07:43:31.620765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:43:31.706926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
31140 265
100.0%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.5585
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-30T07:43:31.793085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7048765
Coefficient of variation (CV)0.00084418276
Kurtosis-1.2776824
Mean2019.5585
Median Absolute Deviation (MAD)2
Skewness-0.03375438
Sum535183
Variance2.9066038
MonotonicityDecreasing
2024-04-30T07:43:31.893259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2018 47
17.7%
2022 46
17.4%
2021 46
17.4%
2020 45
17.0%
2019 41
15.5%
2017 40
15.1%
ValueCountFrequency (%)
2017 40
15.1%
2018 47
17.7%
2019 41
15.5%
2020 45
17.0%
2021 46
17.4%
2022 46
17.4%
ValueCountFrequency (%)
2022 46
17.4%
2021 46
17.4%
2020 45
17.0%
2019 41
15.5%
2018 47
17.7%
2017 40
15.1%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
취득세
54 
주민세
50 
자동차세
42 
재산세
30 
지방소득세
24 
Other values (8)
65 

Length

Max length7
Median length3
Mean length3.7018868
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지방소득세
2nd row지방소득세
3rd row지방소득세
4th row지방소득세
5th row지방소비세

Common Values

ValueCountFrequency (%)
취득세 54
20.4%
주민세 50
18.9%
자동차세 42
15.8%
재산세 30
11.3%
지방소득세 24
9.1%
레저세 16
 
6.0%
지역자원시설세 14
 
5.3%
등록면허세 12
 
4.5%
교육세 6
 
2.3%
체납 6
 
2.3%
Other values (3) 11
 
4.2%

Length

2024-04-30T07:43:32.016665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 54
20.4%
주민세 50
18.9%
자동차세 42
15.8%
재산세 30
11.3%
지방소득세 24
9.1%
레저세 16
 
6.0%
지역자원시설세 14
 
5.3%
등록면허세 12
 
4.5%
교육세 6
 
2.3%
체납 6
 
2.3%
Other values (3) 11
 
4.2%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
지방소득세(특별징수)
 
6
승합
 
6
교육세
 
6
지방소득세(종합소득)
 
6
지방소득세(양도소득)
 
6
Other values (45)
235 

Length

Max length11
Median length8
Mean length6.1773585
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지방소득세(특별징수)
2nd row지방소득세(법인소득)
3rd row지방소득세(양도소득)
4th row지방소득세(종합소득)
5th row지방소비세

Common Values

ValueCountFrequency (%)
지방소득세(특별징수) 6
 
2.3%
승합 6
 
2.3%
교육세 6
 
2.3%
지방소득세(종합소득) 6
 
2.3%
지방소득세(양도소득) 6
 
2.3%
재산세(항공기) 6
 
2.3%
주민세(특별징수) 6
 
2.3%
주택(개별) 6
 
2.3%
주택(단독) 6
 
2.3%
기타 6
 
2.3%
Other values (40) 205
77.4%

Length

2024-04-30T07:43:32.134504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지방소득세(특별징수 6
 
2.3%
자동차세(주행 6
 
2.3%
3륜이하 6
 
2.3%
체납 6
 
2.3%
화물 6
 
2.3%
지방소득세(법인소득 6
 
2.3%
승합 6
 
2.3%
승용 6
 
2.3%
주민세(종업원분 6
 
2.3%
특수 6
 
2.3%
Other values (40) 205
77.4%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct200
Distinct (%)75.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41672.796
Minimum0
Maximum660085
Zeros64
Zeros (%)24.2%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-30T07:43:32.256595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median2543
Q326324
95-th percentile211482.6
Maximum660085
Range660085
Interquartile range (IQR)26315

Descriptive statistics

Standard deviation105800.77
Coefficient of variation (CV)2.5388449
Kurtosis20.432084
Mean41672.796
Median Absolute Deviation (MAD)2543
Skewness4.2641982
Sum11043291
Variance1.1193802 × 1010
MonotonicityNot monotonic
2024-04-30T07:43:32.405419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 64
 
24.2%
370 2
 
0.8%
418 2
 
0.8%
38606 1
 
0.4%
13983 1
 
0.4%
121241 1
 
0.4%
45129 1
 
0.4%
64810 1
 
0.4%
177390 1
 
0.4%
216803 1
 
0.4%
Other values (190) 190
71.7%
ValueCountFrequency (%)
0 64
24.2%
6 1
 
0.4%
7 1
 
0.4%
9 1
 
0.4%
11 1
 
0.4%
22 1
 
0.4%
24 1
 
0.4%
26 1
 
0.4%
27 1
 
0.4%
34 1
 
0.4%
ValueCountFrequency (%)
660085 1
0.4%
649441 1
0.4%
630150 1
0.4%
625562 1
0.4%
624313 1
0.4%
619449 1
0.4%
231343 1
0.4%
231170 1
0.4%
221208 1
0.4%
216803 1
0.4%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct201
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1982153 × 1010
Minimum0
Maximum1.42 × 1011
Zeros65
Zeros (%)24.5%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-30T07:43:32.598040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19604000
median1.223715 × 109
Q31.6684898 × 1010
95-th percentile4.672659 × 1010
Maximum1.42 × 1011
Range1.42 × 1011
Interquartile range (IQR)1.6675294 × 1010

Descriptive statistics

Standard deviation2.0879456 × 1010
Coefficient of variation (CV)1.7425463
Kurtosis13.385213
Mean1.1982153 × 1010
Median Absolute Deviation (MAD)1.223715 × 109
Skewness3.1547758
Sum3.1752706 × 1012
Variance4.3595169 × 1020
MonotonicityNot monotonic
2024-04-30T07:43:32.731196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 65
 
24.5%
60030382000 1
 
0.4%
30220850000 1
 
0.4%
1221583000 1
 
0.4%
1917448000 1
 
0.4%
9502127000 1
 
0.4%
14186932000 1
 
0.4%
3266192000 1
 
0.4%
23868625000 1
 
0.4%
46332908000 1
 
0.4%
Other values (191) 191
72.1%
ValueCountFrequency (%)
0 65
24.5%
7182000 1
 
0.4%
9604000 1
 
0.4%
10585000 1
 
0.4%
11662000 1
 
0.4%
14202000 1
 
0.4%
16136000 1
 
0.4%
17120000 1
 
0.4%
19107000 1
 
0.4%
21249000 1
 
0.4%
ValueCountFrequency (%)
142000000000 1
0.4%
127000000000 1
0.4%
126000000000 1
0.4%
110000000000 1
0.4%
87969285000 1
0.4%
74778909000 1
0.4%
60030382000 1
0.4%
54573780000 1
0.4%
51476350000 1
0.4%
50786882000 1
0.4%

Interactions

2024-04-30T07:43:30.786688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:43:30.131644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:43:30.534136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:43:30.867657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:43:30.251902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:43:30.625964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:43:30.946029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:43:30.444149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:43:30.703752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:43:32.822113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8390.516
세원 유형명0.0001.0001.0000.9970.840
부과건수0.0000.8390.9971.0000.624
부과금액0.0000.5160.8400.6241.000
2024-04-30T07:43:32.908377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세원 유형명세목명
세원 유형명1.0000.924
세목명0.9241.000
2024-04-30T07:43:32.983656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도부과건수부과금액세목명세원 유형명
과세년도1.000-0.050-0.0040.0000.000
부과건수-0.0501.0000.8040.6470.845
부과금액-0.0040.8041.0000.2410.409
세목명0.0000.6470.2411.0000.924
세원 유형명0.0000.8450.4090.9241.000

Missing values

2024-04-30T07:43:31.054432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:43:31.161253image/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
0울산광역시남구311402022지방소득세지방소득세(특별징수)7973060030382000
1울산광역시남구311402022지방소득세지방소득세(법인소득)5240142000000000
2울산광역시남구311402022지방소득세지방소득세(양도소득)556646832859000
3울산광역시남구311402022지방소득세지방소득세(종합소득)6846516684898000
4울산광역시남구311402022지방소비세지방소비세910573698000
5울산광역시남구311402022교육세교육세62431334138116000
6울산광역시남구311402022도시계획세도시계획세00
7울산광역시남구311402022취득세건축물233821552881000
8울산광역시남구311402022취득세주택(개별)106224888292000
9울산광역시남구311402022취득세주택(단독)480136978976000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
255울산광역시남구311402017주민세주민세(양도소득)00
256울산광역시남구311402017주민세주민세(종합소득)00
257울산광역시남구311402017주민세주민세(법인균등)6659476851000
258울산광역시남구311402017주민세주민세(개인사업)13010655497000
259울산광역시남구311402017주민세주민세(개인균등)1291771302968000
260울산광역시남구311402017등록면허세등록면허세(면허)429631801996000
261울산광역시남구311402017등록면허세등록면허세(등록)654548567275000
262울산광역시남구311402017지역자원시설세지역자원시설세(소방)19547212902667000
263울산광역시남구311402017지역자원시설세지역자원시설세(특자)4912534545000
264울산광역시남구311402017체납체납23117020299514000