Overview

Dataset statistics

Number of variables10
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory92.3 B

Variable types

Numeric3
Categorical7

Dataset

Description2017년부터 2021년까지 연도별 지방세 과세 및 비과세 현황을 세목별로 제공하는 사항으로서 국민 조세 혜택 규모를 파악하는 데 사용할 수 있습니다.
URLhttps://www.data.go.kr/data/15079232/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
비과세건수 has constant value ""Constant
비과세금액 has constant value ""Constant
연번 is highly overall correlated with 과세년도High correlation
과세건수 is highly overall correlated with 세목명High correlation
과세금액 is highly overall correlated with 세목명High correlation
과세년도 is highly overall correlated with 연번High correlation
세목명 is highly overall correlated with 과세건수 and 1 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:52:54.616440
Analysis finished2023-12-12 09:52:55.998208
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T18:52:56.083773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q17
median13
Q319
95-th percentile23.8
Maximum25
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3598007
Coefficient of variation (CV)0.56613852
Kurtosis-1.2
Mean13
Median Absolute Deviation (MAD)6
Skewness0
Sum325
Variance54.166667
MonotonicityStrictly increasing
2023-12-12T18:52:56.209573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 1
 
4.0%
2 1
 
4.0%
25 1
 
4.0%
24 1
 
4.0%
23 1
 
4.0%
22 1
 
4.0%
21 1
 
4.0%
20 1
 
4.0%
19 1
 
4.0%
18 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1 1
4.0%
2 1
4.0%
3 1
4.0%
4 1
4.0%
5 1
4.0%
6 1
4.0%
7 1
4.0%
8 1
4.0%
9 1
4.0%
10 1
4.0%
ValueCountFrequency (%)
25 1
4.0%
24 1
4.0%
23 1
4.0%
22 1
4.0%
21 1
4.0%
20 1
4.0%
19 1
4.0%
18 1
4.0%
17 1
4.0%
16 1
4.0%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
대전광역시
25 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전광역시 25
100.0%

Length

2023-12-12T18:52:56.352778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:52:56.435306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 25
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
대전광역시
25 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전광역시 25
100.0%

Length

2023-12-12T18:52:56.552390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:52:56.667045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 25
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
30000
25 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30000
2nd row30000
3rd row30000
4th row30000
5th row30000

Common Values

ValueCountFrequency (%)
30000 25
100.0%

Length

2023-12-12T18:52:56.787164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:52:56.894791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30000 25
100.0%

과세년도
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2017
5 
2018
5 
2019
5 
2020
5 
2021
5 

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 5
20.0%
2018 5
20.0%
2019 5
20.0%
2020 5
20.0%
2021 5
20.0%

Length

2023-12-12T18:52:57.005196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:52:57.111655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 5
20.0%
2018 5
20.0%
2019 5
20.0%
2020 5
20.0%
2021 5
20.0%

세목명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
취득세
5 
자동차세
5 
담배소비세
5 
지방소비세
5 
교육세
5 

Length

Max length5
Median length4
Mean length4
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 5
20.0%
자동차세 5
20.0%
담배소비세 5
20.0%
지방소비세 5
20.0%
교육세 5
20.0%

Length

2023-12-12T18:52:57.251070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:52:57.399075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취득세 5
20.0%
자동차세 5
20.0%
담배소비세 5
20.0%
지방소비세 5
20.0%
교육세 5
20.0%

과세건수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21371.88
Minimum6
Maximum111703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T18:52:57.510766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile8
Q112
median113
Q31220
95-th percentile105966.4
Maximum111703
Range111697
Interquartile range (IQR)1208

Descriptive statistics

Standard deviation42904.301
Coefficient of variation (CV)2.0075118
Kurtosis0.62395836
Mean21371.88
Median Absolute Deviation (MAD)107
Skewness1.602815
Sum534297
Variance1.8407791 × 109
MonotonicityNot monotonic
2023-12-12T18:52:57.651075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
12 5
20.0%
8 2
 
8.0%
106407 1
 
4.0%
111703 1
 
4.0%
1593 1
 
4.0%
10 1
 
4.0%
487 1
 
4.0%
104204 1
 
4.0%
1208 1
 
4.0%
9 1
 
4.0%
Other values (10) 10
40.0%
ValueCountFrequency (%)
6 1
 
4.0%
8 2
 
8.0%
9 1
 
4.0%
10 1
 
4.0%
12 5
20.0%
86 1
 
4.0%
92 1
 
4.0%
113 1
 
4.0%
273 1
 
4.0%
487 1
 
4.0%
ValueCountFrequency (%)
111703 1
4.0%
106407 1
4.0%
104204 1
4.0%
103274 1
4.0%
101318 1
4.0%
1593 1
4.0%
1220 1
4.0%
1208 1
4.0%
1149 1
4.0%
1069 1
4.0%

과세금액
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3459033 × 1011
Minimum3.9770884 × 1010
Maximum4.74 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T18:52:57.797919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.9770884 × 1010
5-th percentile4.0974158 × 1010
Q19.2374544 × 1010
median1.08 × 1011
Q31.31 × 1011
95-th percentile3.406 × 1011
Maximum4.74 × 1011
Range4.3422912 × 1011
Interquartile range (IQR)3.8625456 × 1010

Descriptive statistics

Standard deviation1.0344339 × 1011
Coefficient of variation (CV)0.76857968
Kurtosis4.4149536
Mean1.3459033 × 1011
Median Absolute Deviation (MAD)1.7775377 × 1010
Skewness2.042878
Sum3.3647581 × 1012
Variance1.0700535 × 1022
MonotonicityNot monotonic
2023-12-12T18:52:57.909596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
109000000000 3
 
12.0%
232000000000 2
 
8.0%
111000000000 2
 
8.0%
107000000000 1
 
4.0%
96726766000 1
 
4.0%
42111877000 1
 
4.0%
474000000000 1
 
4.0%
95447408000 1
 
4.0%
108000000000 1
 
4.0%
131000000000 1
 
4.0%
Other values (11) 11
44.0%
ValueCountFrequency (%)
39770884000 1
4.0%
40729898000 1
4.0%
41951197000 1
4.0%
42111877000 1
4.0%
42637822000 1
4.0%
90224623000 1
4.0%
92374544000 1
4.0%
95447408000 1
4.0%
96726766000 1
4.0%
96783117000 1
4.0%
ValueCountFrequency (%)
474000000000 1
 
4.0%
363000000000 1
 
4.0%
251000000000 1
 
4.0%
232000000000 2
8.0%
133000000000 1
 
4.0%
131000000000 1
 
4.0%
111000000000 2
8.0%
109000000000 3
12.0%
108000000000 1
 
4.0%
107000000000 1
 
4.0%

비과세건수
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
0
25 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25
100.0%

Length

2023-12-12T18:52:58.066453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:52:58.155921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 25
100.0%

비과세금액
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
0
25 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25
100.0%

Length

2023-12-12T18:52:58.247759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:52:58.346214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 25
100.0%

Interactions

2023-12-12T18:52:55.481925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:52:54.885611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:52:55.186214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:52:55.570199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:52:54.978974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:52:55.277514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:52:55.678544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:52:55.097118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:52:55.383807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:52:58.408964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번과세년도세목명과세건수과세금액
연번1.0001.0000.0000.0000.330
과세년도1.0001.0000.0000.0000.000
세목명0.0000.0001.0001.0000.796
과세건수0.0000.0001.0001.0000.698
과세금액0.3300.0000.7960.6981.000
2023-12-12T18:52:58.534476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도
세목명1.0000.000
과세년도0.0001.000
2023-12-12T18:52:58.632334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번과세건수과세금액과세년도세목명
연번1.0000.0060.0320.8660.000
과세건수0.0061.000-0.4730.0000.933
과세금액0.032-0.4731.0000.0000.665
과세년도0.8660.0000.0001.0000.000
세목명0.0000.9330.6650.0001.000

Missing values

2023-12-12T18:52:55.787229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:52:55.941245image/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

연번시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
01대전광역시대전광역시300002017취득세10640710700000000000
12대전광역시대전광역시300002017자동차세1210900000000000
23대전광역시대전광역시300002017담배소비세1139678311700000
34대전광역시대전광역시300002017지방소비세823200000000000
45대전광역시대전광역시300002017교육세12204195119700000
56대전광역시대전광역시300002018취득세10327410900000000000
67대전광역시대전광역시300002018자동차세1211100000000000
78대전광역시대전광역시300002018담배소비세929237454400000
89대전광역시대전광역시300002018지방소비세823200000000000
910대전광역시대전광역시300002018교육세11494072989800000
연번시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
1516대전광역시대전광역시300002020취득세11170313300000000000
1617대전광역시대전광역시300002020자동차세1211100000000000
1718대전광역시대전광역시300002020담배소비세2739672676600000
1819대전광역시대전광역시300002020지방소비세925100000000000
1920대전광역시대전광역시300002020교육세12084263782200000
2021대전광역시대전광역시300002021취득세10420413100000000000
2122대전광역시대전광역시300002021자동차세1210800000000000
2223대전광역시대전광역시300002021담배소비세4879544740800000
2324대전광역시대전광역시300002021지방소비세1047400000000000
2425대전광역시대전광역시300002021교육세15934211187700000