Overview

Dataset statistics

Number of variables9
Number of observations66
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory80.0 B

Variable types

Categorical4
Numeric5

Dataset

Description연도별 지방세 과세 및 비과세 현황을 세목별로 제공한다.연도별 주민세, 재산세, 자동차세, 담배소비세, 지방소득세, 취득세,등록면허세,지역자원시설세,지방교육세 등과세건수, 과세금액, 비과세건수, 비과세금액의 자료를 제공한다.
Author전라남도 장성군
URLhttps://www.data.go.kr/data/15080212/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세건수 is highly overall correlated with 과세금액 and 2 other fieldsHigh correlation
과세금액 is highly overall correlated with 과세건수High correlation
비과세건수 is highly overall correlated with 과세건수 and 2 other fieldsHigh correlation
비과세금액 is highly overall correlated with 비과세건수High correlation
세목명 is highly overall correlated with 과세건수 and 1 other fieldsHigh correlation
과세건수 has 9 (13.6%) zerosZeros
과세금액 has 10 (15.2%) zerosZeros
비과세건수 has 18 (27.3%) zerosZeros
비과세금액 has 18 (27.3%) zerosZeros

Reproduction

Analysis started2024-04-17 09:52:45.980906
Analysis finished2024-04-17 09:52:48.212154
Duration2.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
전라남도
66 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 66
100.0%

Length

2024-04-17T18:52:48.266511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:52:48.342802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 66
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
장성군
66 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장성군 66
100.0%

Length

2024-04-17T18:52:48.423256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:52:48.497939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장성군 66
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
46880
66 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46880
2nd row46880
3rd row46880
4th row46880
5th row46880

Common Values

ValueCountFrequency (%)
46880 66
100.0%

Length

2024-04-17T18:52:48.575649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:52:48.653877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46880 66
100.0%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.6818
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-04-17T18:52:48.721344image/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 deviation1.7467252
Coefficient of variation (CV)0.00086485168
Kurtosis-1.3052867
Mean2019.6818
Median Absolute Deviation (MAD)1.5
Skewness-0.15352392
Sum133299
Variance3.051049
MonotonicityIncreasing
2024-04-17T18:52:48.807849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2021 13
19.7%
2022 13
19.7%
2017 10
15.2%
2018 10
15.2%
2019 10
15.2%
2020 10
15.2%
ValueCountFrequency (%)
2017 10
15.2%
2018 10
15.2%
2019 10
15.2%
2020 10
15.2%
2021 13
19.7%
2022 13
19.7%
ValueCountFrequency (%)
2022 13
19.7%
2021 13
19.7%
2020 10
15.2%
2019 10
15.2%
2018 10
15.2%
2017 10
15.2%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Memory size660.0 B
주민세
6 
재산세
6 
자동차세
6 
담배소비세
6 
지방소득세
6 
Other values (8)
36 

Length

Max length7
Median length5
Mean length4.1212121
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주민세
2nd row재산세
3rd row자동차세
4th row담배소비세
5th row지방소득세

Common Values

ValueCountFrequency (%)
주민세 6
9.1%
재산세 6
9.1%
자동차세 6
9.1%
담배소비세 6
9.1%
지방소득세 6
9.1%
취득세 6
9.1%
등록세 6
9.1%
등록면허세 6
9.1%
지역자원시설세 6
9.1%
교육세 6
9.1%
Other values (3) 6
9.1%

Length

2024-04-17T18:52:48.915202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주민세 6
9.1%
재산세 6
9.1%
자동차세 6
9.1%
담배소비세 6
9.1%
지방소득세 6
9.1%
취득세 6
9.1%
등록세 6
9.1%
등록면허세 6
9.1%
지역자원시설세 6
9.1%
교육세 6
9.1%
Other values (3) 6
9.1%

과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct58
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29792.788
Minimum0
Maximum134229
Zeros9
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-04-17T18:52:49.028064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1323.25
median15700.5
Q337288.25
95-th percentile127096.5
Maximum134229
Range134229
Interquartile range (IQR)36965

Descriptive statistics

Standard deviation38089.405
Coefficient of variation (CV)1.2784774
Kurtosis1.9022362
Mean29792.788
Median Absolute Deviation (MAD)15603
Skewness1.6784717
Sum1966324
Variance1.4508028 × 109
MonotonicityNot monotonic
2024-04-17T18:52:49.157207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
13.6%
23276 1
 
1.5%
10243 1
 
1.5%
6 1
 
1.5%
12020 1
 
1.5%
26839 1
 
1.5%
9826 1
 
1.5%
132349 1
 
1.5%
13228 1
 
1.5%
24042 1
 
1.5%
Other values (48) 48
72.7%
ValueCountFrequency (%)
0 9
13.6%
6 1
 
1.5%
7 1
 
1.5%
9 1
 
1.5%
45 1
 
1.5%
81 1
 
1.5%
88 1
 
1.5%
107 1
 
1.5%
273 1
 
1.5%
474 1
 
1.5%
ValueCountFrequency (%)
134229 1
1.5%
133582 1
1.5%
132349 1
1.5%
127925 1
1.5%
124611 1
1.5%
120581 1
1.5%
78862 1
1.5%
77189 1
1.5%
76567 1
1.5%
74508 1
1.5%

과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct57
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4052003 × 109
Minimum0
Maximum3.3853028 × 1010
Zeros10
Zeros (%)15.2%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-04-17T18:52:49.271320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.1234035 × 109
median3.3395055 × 109
Q38.857316 × 109
95-th percentile1.517082 × 1010
Maximum3.3853028 × 1010
Range3.3853028 × 1010
Interquartile range (IQR)7.7339125 × 109

Descriptive statistics

Standard deviation6.2947431 × 109
Coefficient of variation (CV)1.1645717
Kurtosis5.6933126
Mean5.4052003 × 109
Median Absolute Deviation (MAD)2.5485065 × 109
Skewness2.0374687
Sum3.5674322 × 1011
Variance3.9623791 × 1019
MonotonicityNot monotonic
2024-04-17T18:52:49.750092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
15.2%
1153015000 1
 
1.5%
12128293000 1
 
1.5%
19787376000 1
 
1.5%
1684114000 1
 
1.5%
991397000 1
 
1.5%
4985341000 1
 
1.5%
21710652000 1
 
1.5%
1462948000 1
 
1.5%
5629551000 1
 
1.5%
Other values (47) 47
71.2%
ValueCountFrequency (%)
0 10
15.2%
24406000 1
 
1.5%
737457000 1
 
1.5%
844541000 1
 
1.5%
964209000 1
 
1.5%
991397000 1
 
1.5%
1049938000 1
 
1.5%
1113533000 1
 
1.5%
1153015000 1
 
1.5%
1193636000 1
 
1.5%
ValueCountFrequency (%)
33853028000 1
1.5%
21710652000 1
1.5%
19787376000 1
1.5%
15307692000 1
1.5%
14760205000 1
1.5%
14663888000 1
1.5%
13628756000 1
1.5%
13477657000 1
1.5%
12128293000 1
1.5%
11095710000 1
1.5%

비과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3556.0758
Minimum0
Maximum24191
Zeros18
Zeros (%)27.3%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-04-17T18:52:49.869346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1859
Q33520
95-th percentile21735
Maximum24191
Range24191
Interquartile range (IQR)3520

Descriptive statistics

Standard deviation6283.4261
Coefficient of variation (CV)1.7669551
Kurtosis5.3209596
Mean3556.0758
Median Absolute Deviation (MAD)1859
Skewness2.5028497
Sum234701
Variance39481444
MonotonicityNot monotonic
2024-04-17T18:52:49.981976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 18
27.3%
2 2
 
3.0%
3565 1
 
1.5%
6573 1
 
1.5%
6501 1
 
1.5%
2131 1
 
1.5%
3385 1
 
1.5%
1956 1
 
1.5%
51 1
 
1.5%
2497 1
 
1.5%
Other values (38) 38
57.6%
ValueCountFrequency (%)
0 18
27.3%
2 2
 
3.0%
3 1
 
1.5%
8 1
 
1.5%
9 1
 
1.5%
19 1
 
1.5%
29 1
 
1.5%
46 1
 
1.5%
49 1
 
1.5%
51 1
 
1.5%
ValueCountFrequency (%)
24191 1
1.5%
23954 1
1.5%
23493 1
1.5%
21950 1
1.5%
21090 1
1.5%
18904 1
1.5%
6705 1
1.5%
6573 1
1.5%
6501 1
1.5%
5433 1
1.5%

비과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.9931464 × 108
Minimum0
Maximum6.139651 × 109
Zeros18
Zeros (%)27.3%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-04-17T18:52:50.092685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median26839500
Q32.59838 × 108
95-th percentile4.7352402 × 109
Maximum6.139651 × 109
Range6.139651 × 109
Interquartile range (IQR)2.59838 × 108

Descriptive statistics

Standard deviation1.7886837 × 109
Coefficient of variation (CV)1.988941
Kurtosis1.4803848
Mean8.9931464 × 108
Median Absolute Deviation (MAD)26839500
Skewness1.7932383
Sum5.9354766 × 1010
Variance3.1993895 × 1018
MonotonicityNot monotonic
2024-04-17T18:52:50.207063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 18
27.3%
4000 3
 
4.5%
3000 2
 
3.0%
155282000 1
 
1.5%
3043827000 1
 
1.5%
2182000 1
 
1.5%
151163000 1
 
1.5%
239827000 1
 
1.5%
4660620000 1
 
1.5%
320000 1
 
1.5%
Other values (36) 36
54.5%
ValueCountFrequency (%)
0 18
27.3%
3000 2
 
3.0%
4000 3
 
4.5%
5000 1
 
1.5%
320000 1
 
1.5%
437000 1
 
1.5%
2182000 1
 
1.5%
6242000 1
 
1.5%
8355000 1
 
1.5%
12696000 1
 
1.5%
ValueCountFrequency (%)
6139651000 1
1.5%
5278696000 1
1.5%
5006218000 1
1.5%
4735856000 1
1.5%
4733393000 1
1.5%
4660620000 1
1.5%
4643003000 1
1.5%
4523054000 1
1.5%
4505485000 1
1.5%
4005581000 1
1.5%

Interactions

2024-04-17T18:52:47.673974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:46.188445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:46.564239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:46.923611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:47.300416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:47.746972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:46.253659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:46.631320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:46.994425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:47.368552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:47.825300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:46.330409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:46.704953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:47.070305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:47.447682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:47.899778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:46.418280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:46.780846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:47.148202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:47.524714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:47.968807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:46.490556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:46.851780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:47.216631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:52:47.592243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T18:52:50.285148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명과세건수과세금액비과세건수비과세금액
과세년도1.0000.0000.0000.0000.0000.149
세목명0.0001.0000.9410.7640.8730.655
과세건수0.0000.9411.0000.5890.9380.693
과세금액0.0000.7640.5891.0000.5060.860
비과세건수0.0000.8730.9380.5061.0000.715
비과세금액0.1490.6550.6930.8600.7151.000
2024-04-17T18:52:50.373923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도과세건수과세금액비과세건수비과세금액세목명
과세년도1.000-0.0670.029-0.092-0.1350.000
과세건수-0.0671.0000.5010.6740.4240.775
과세금액0.0290.5011.0000.2290.2900.457
비과세건수-0.0920.6740.2291.0000.8640.634
비과세금액-0.1350.4240.2900.8641.0000.370
세목명0.0000.7750.4570.6340.3701.000

Missing values

2024-04-17T18:52:48.064764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T18:52:48.171610image/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

시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
0전라남도장성군468802017주민세232761153015000356527317000
1전라남도장성군468802017재산세703143501504000189044643003000
2전라남도장성군468802017자동차세3629699943310004872303013000
3전라남도장성군468802017담배소비세107279731200000
4전라남도장성군468802017지방소득세12673869578700000
5전라남도장성군468802017취득세108251362875600021686139651000
6전라남도장성군468802017등록세0096242000
7전라남도장성군468802017등록면허세2179713686760002313148487000
8전라남도장성군468802017지역자원시설세82197374570001292218073000
9전라남도장성군468802017교육세1205813950157000293000
시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
56전라남도장성군468802022재산세788626400097000241915006218000
57전라남도장성군468802022자동차세4026691152560006705249791000
58전라남도장성군468802022레저세452440600000
59전라남도장성군468802022담배소비세636348218000000
60전라남도장성군468802022지방소비세91109571000000
61전라남도장성군468802022등록면허세2621317508730003876102821000
62전라남도장성군468802022도시계획세0000
63전라남도장성군468802022지역자원시설세1026811135330002038252764000
64전라남도장성군468802022지방소득세219561347765700000
65전라남도장성군468802022교육세1335826775915000534000