Overview

Dataset statistics

Number of variables10
Number of observations277
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.1 KiB
Average record size in memory85.5 B

Variable types

Numeric4
Categorical6

Dataset

Description지방세 세원이 되는 과세물건 유형별 부과된 현황을 제공
Author인천광역시 옹진군
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15079401&srcSe=7661IVAWM27C61E190

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일자 has constant value ""Constant
세목명 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
세원 유형명 is highly overall correlated with 부과건수 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 과세년도High correlation
과세년도 is highly overall correlated with 연번High correlation
부과건수 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
부과건수 has 65 (23.5%) zerosZeros
부과금액 has 65 (23.5%) zerosZeros

Reproduction

Analysis started2024-01-28 13:34:24.851273
Analysis finished2024-01-28 13:34:26.965331
Duration2.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct277
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139
Minimum1
Maximum277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-01-28T22:34:27.022575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.8
Q170
median139
Q3208
95-th percentile263.2
Maximum277
Range276
Interquartile range (IQR)138

Descriptive statistics

Standard deviation80.10722
Coefficient of variation (CV)0.57631093
Kurtosis-1.2
Mean139
Median Absolute Deviation (MAD)69
Skewness0
Sum38503
Variance6417.1667
MonotonicityStrictly increasing
2024-01-28T22:34:27.155131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
184 1
 
0.4%
190 1
 
0.4%
189 1
 
0.4%
188 1
 
0.4%
187 1
 
0.4%
186 1
 
0.4%
185 1
 
0.4%
183 1
 
0.4%
175 1
 
0.4%
Other values (267) 267
96.4%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
277 1
0.4%
276 1
0.4%
275 1
0.4%
274 1
0.4%
273 1
0.4%
272 1
0.4%
271 1
0.4%
270 1
0.4%
269 1
0.4%
268 1
0.4%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
인천광역시
277 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 277
100.0%

Length

2024-01-28T22:34:27.295183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T22:34:27.371034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 277
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
옹진군
277 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
옹진군 277
100.0%

Length

2024-01-28T22:34:27.466418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T22:34:27.555970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
옹진군 277
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
28720
277 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28720
2nd row28720
3rd row28720
4th row28720
5th row28720

Common Values

ValueCountFrequency (%)
28720 277
100.0%

Length

2024-01-28T22:34:27.656021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T22:34:27.759514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28720 277
100.0%

과세년도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.491
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-01-28T22:34:27.848209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2019
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7016908
Coefficient of variation (CV)0.00084263353
Kurtosis-1.2550231
Mean2019.491
Median Absolute Deviation (MAD)1
Skewness0.0044547879
Sum559399
Variance2.8957516
MonotonicityIncreasing
2024-01-28T22:34:27.937757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2019 47
17.0%
2020 47
17.0%
2017 46
16.6%
2018 46
16.6%
2021 46
16.6%
2022 45
16.2%
ValueCountFrequency (%)
2017 46
16.6%
2018 46
16.6%
2019 47
17.0%
2020 47
17.0%
2021 46
16.6%
2022 45
16.2%
ValueCountFrequency (%)
2022 45
16.2%
2021 46
16.6%
2020 47
17.0%
2019 47
17.0%
2018 46
16.6%
2017 46
16.6%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
취득세
54 
주민세
50 
자동차세
42 
재산세
30 
레저세
24 
Other values (8)
77 

Length

Max length7
Median length3
Mean length3.700361
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 54
19.5%
주민세 50
18.1%
자동차세 42
15.2%
재산세 30
10.8%
레저세 24
8.7%
지방소득세 24
8.7%
지역자원시설세 14
 
5.1%
등록면허세 12
 
4.3%
담배소비세 6
 
2.2%
교육세 6
 
2.2%
Other values (3) 15
 
5.4%

Length

2024-01-28T22:34:28.047036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 54
19.5%
주민세 50
18.1%
자동차세 42
15.2%
재산세 30
10.8%
레저세 24
8.7%
지방소득세 24
8.7%
지역자원시설세 14
 
5.1%
등록면허세 12
 
4.3%
담배소비세 6
 
2.2%
교육세 6
 
2.2%
Other values (3) 15
 
5.4%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
담배소비세
 
6
소싸움
 
6
주택(개별)
 
6
등록면허세(면허)
 
6
기타
 
6
Other values (45)
247 

Length

Max length11
Median length8
Mean length6.0469314
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
담배소비세 6
 
2.2%
소싸움 6
 
2.2%
주택(개별) 6
 
2.2%
등록면허세(면허) 6
 
2.2%
기타 6
 
2.2%
항공기 6
 
2.2%
기계장비 6
 
2.2%
자동차세(주행) 6
 
2.2%
차량 6
 
2.2%
선박 6
 
2.2%
Other values (40) 217
78.3%

Length

2024-01-28T22:34:28.157579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
담배소비세 6
 
2.2%
지방소득세(법인소득 6
 
2.2%
승합 6
 
2.2%
소싸움 6
 
2.2%
승용 6
 
2.2%
지방소비세 6
 
2.2%
지방소득세(특별징수 6
 
2.2%
화물 6
 
2.2%
지방소득세(양도소득 6
 
2.2%
지방소득세(종합소득 6
 
2.2%
Other values (40) 217
78.3%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct188
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4402.1119
Minimum0
Maximum64482
Zeros65
Zeros (%)23.5%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-01-28T22:34:28.276029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median257
Q33054
95-th percentile27558.6
Maximum64482
Range64482
Interquartile range (IQR)3049

Descriptive statistics

Standard deviation11177.322
Coefficient of variation (CV)2.5390817
Kurtosis15.926132
Mean4402.1119
Median Absolute Deviation (MAD)257
Skewness3.8655377
Sum1219385
Variance1.2493252 × 108
MonotonicityNot monotonic
2024-01-28T22:34:28.407892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 65
 
23.5%
12 12
 
4.3%
71 3
 
1.1%
52 2
 
0.7%
64 2
 
0.7%
7 2
 
0.7%
271 2
 
0.7%
84 2
 
0.7%
53 2
 
0.7%
668 2
 
0.7%
Other values (178) 183
66.1%
ValueCountFrequency (%)
0 65
23.5%
2 2
 
0.7%
3 2
 
0.7%
5 1
 
0.4%
6 1
 
0.4%
7 2
 
0.7%
8 1
 
0.4%
9 1
 
0.4%
10 1
 
0.4%
11 1
 
0.4%
ValueCountFrequency (%)
64482 1
0.4%
64124 1
0.4%
63869 1
0.4%
62646 1
0.4%
62209 1
0.4%
61908 1
0.4%
40960 1
0.4%
40784 1
0.4%
33868 1
0.4%
33125 1
0.4%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct213
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.098479 × 109
Minimum-4000
Maximum1.1866136 × 1010
Zeros65
Zeros (%)23.5%
Negative1
Negative (%)0.4%
Memory size2.6 KiB
2024-01-28T22:34:28.541957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-4000
5-th percentile0
Q1797000
median1.60996 × 108
Q31.324505 × 109
95-th percentile5.8106882 × 109
Maximum1.1866136 × 1010
Range1.186614 × 1010
Interquartile range (IQR)1.323708 × 109

Descriptive statistics

Standard deviation2.0580648 × 109
Coefficient of variation (CV)1.8735586
Kurtosis8.8666672
Mean1.098479 × 109
Median Absolute Deviation (MAD)1.60996 × 108
Skewness2.8406636
Sum3.0427869 × 1011
Variance4.2356308 × 1018
MonotonicityNot monotonic
2024-01-28T22:34:28.683635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 65
 
23.5%
2490662000 1
 
0.4%
3410000 1
 
0.4%
217646000 1
 
0.4%
632923000 1
 
0.4%
23618000 1
 
0.4%
26273000 1
 
0.4%
44081000 1
 
0.4%
3870712000 1
 
0.4%
2525380000 1
 
0.4%
Other values (203) 203
73.3%
ValueCountFrequency (%)
-4000 1
 
0.4%
0 65
23.5%
663000 1
 
0.4%
714000 1
 
0.4%
758000 1
 
0.4%
797000 1
 
0.4%
812000 1
 
0.4%
918000 1
 
0.4%
954000 1
 
0.4%
1224000 1
 
0.4%
ValueCountFrequency (%)
11866136000 1
0.4%
11430473000 1
0.4%
11087820000 1
0.4%
9894788000 1
0.4%
8638539000 1
0.4%
8503322000 1
0.4%
7919755000 1
0.4%
6851149000 1
0.4%
6719698000 1
0.4%
6328333000 1
0.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2022-08-31
277 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-31
2nd row2022-08-31
3rd row2022-08-31
4th row2022-08-31
5th row2022-08-31

Common Values

ValueCountFrequency (%)
2022-08-31 277
100.0%

Length

2024-01-28T22:34:28.802895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T22:34:28.884832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-31 277
100.0%

Interactions

2024-01-28T22:34:26.431132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:25.160882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:25.774517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:26.101466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:26.510717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:25.224812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:25.857514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:26.175324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:26.586884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:25.297985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:25.925756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:26.258696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:26.676142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:25.369261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:26.015441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:34:26.346980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T22:34:28.937374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번과세년도세목명세원 유형명부과건수부과금액
연번1.0000.9460.3600.0000.0000.000
과세년도0.9461.0000.0000.0000.0000.000
세목명0.3600.0001.0001.0000.8660.765
세원 유형명0.0000.0001.0001.0000.9660.947
부과건수0.0000.0000.8660.9661.0000.726
부과금액0.0000.0000.7650.9470.7261.000
2024-01-28T22:34:29.029034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명세원 유형명
세목명1.0000.927
세원 유형명0.9271.000
2024-01-28T22:34:29.111112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번과세년도부과건수부과금액세목명세원 유형명
연번1.0000.9860.0350.0240.1560.000
과세년도0.9861.0000.0200.0350.0000.000
부과건수0.0350.0201.0000.7420.6340.741
부과금액0.0240.0350.7421.0000.4480.615
세목명0.1560.0000.6340.4481.0000.927
세원 유형명0.0000.0000.7410.6150.9271.000

Missing values

2024-01-28T22:34:26.790032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T22:34:26.913971image/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

연번시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액데이터기준일자
01인천광역시옹진군287202017담배소비세담배소비세10724906620002022-08-31
12인천광역시옹진군287202017교육세교육세6264635966180002022-08-31
23인천광역시옹진군287202017취득세건축물25715651220002022-08-31
34인천광역시옹진군287202017취득세주택(개별)77413829720002022-08-31
45인천광역시옹진군287202017취득세주택(단독)832141900002022-08-31
56인천광역시옹진군287202017취득세기타8164280002022-08-31
67인천광역시옹진군287202017취득세항공기002022-08-31
78인천광역시옹진군287202017취득세기계장비401486590002022-08-31
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