Overview

Dataset statistics

Number of variables8
Number of observations223
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.9 KiB
Average record size in memory68.6 B

Variable types

Categorical5
Numeric3

Dataset

Description지방세 과세를 위해 세원이 되는 과세 대상 유형별 부과된 현황을 제공한다.2017년부터 2022년까지 세목별, 세원 유형별, 부과건수, 부과금액 등을 제공한다.
Author전라남도 장성군
URLhttps://www.data.go.kr/data/15080240/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 9 (4.0%) zerosZeros
부과금액 has 8 (3.6%) zerosZeros

Reproduction

Analysis started2024-03-14 13:42:18.349396
Analysis finished2024-03-14 13:42:21.047073
Duration2.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
전라남도
223 

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 223
100.0%

Length

2024-03-14T22:42:21.246053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:42:21.558377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 223
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
장성군
223 

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 223
100.0%

Length

2024-03-14T22:42:21.886013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:42:22.397702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장성군 223
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
46880
223 

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 223
100.0%

Length

2024-03-14T22:42:22.723829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:42:23.033774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46880 223
100.0%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.6233
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-03-14T22:42:23.320642image/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 deviation1.7531937
Coefficient of variation (CV)0.00086807953
Kurtosis-1.321308
Mean2019.6233
Median Absolute Deviation (MAD)2
Skewness-0.068308751
Sum450376
Variance3.073688
MonotonicityIncreasing
2024-03-14T22:42:23.676047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2022 46
20.6%
2018 36
16.1%
2021 36
16.1%
2017 35
15.7%
2019 35
15.7%
2020 35
15.7%
ValueCountFrequency (%)
2017 35
15.7%
2018 36
16.1%
2019 35
15.7%
2020 35
15.7%
2021 36
16.1%
2022 46
20.6%
ValueCountFrequency (%)
2022 46
20.6%
2021 36
16.1%
2020 35
15.7%
2019 35
15.7%
2018 36
16.1%
2017 35
15.7%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
취득세
51 
자동차세
42 
주민세
30 
재산세
26 
지방소득세
24 
Other values (8)
50 

Length

Max length7
Median length3
Mean length3.7982063
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 51
22.9%
자동차세 42
18.8%
주민세 30
13.5%
재산세 26
11.7%
지방소득세 24
10.8%
지역자원시설세 13
 
5.8%
등록면허세 12
 
5.4%
담배소비세 6
 
2.7%
교육세 6
 
2.7%
체납 6
 
2.7%
Other values (3) 7
 
3.1%

Length

2024-03-14T22:42:24.073804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 51
22.9%
자동차세 42
18.8%
주민세 30
13.5%
재산세 26
11.7%
지방소득세 24
10.8%
지역자원시설세 13
 
5.8%
등록면허세 12
 
5.4%
담배소비세 6
 
2.7%
교육세 6
 
2.7%
체납 6
 
2.7%
Other values (3) 7
 
3.1%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
기계장비
 
6
지역자원시설세(소방)
 
6
등록면허세(등록)
 
6
체납
 
6
교육세
 
6
Other values (45)
193 

Length

Max length11
Median length8
Mean length6.1345291
Min length2

Unique

Unique10 ?
Unique (%)4.5%

Sample

1st row주민세(재산분)
2nd row주민세(종업원분)
3rd row주민세(법인균등)
4th row주민세(개인사업)
5th row주민세(개인균등)

Common Values

ValueCountFrequency (%)
기계장비 6
 
2.7%
지역자원시설세(소방) 6
 
2.7%
등록면허세(등록) 6
 
2.7%
체납 6
 
2.7%
교육세 6
 
2.7%
지역자원시설세(특자) 6
 
2.7%
재산세(주택) 6
 
2.7%
담배소비세 6
 
2.7%
재산세(선박) 6
 
2.7%
재산세(건축물) 6
 
2.7%
Other values (40) 163
73.1%

Length

2024-03-14T22:42:24.460485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기계장비 6
 
2.7%
재산세(토지 6
 
2.7%
등록면허세(면허 6
 
2.7%
토지 6
 
2.7%
선박 6
 
2.7%
차량 6
 
2.7%
주민세(종업원분 6
 
2.7%
지역자원시설세(소방 6
 
2.7%
주택(단독 6
 
2.7%
주택(개별 6
 
2.7%
Other values (40) 163
73.1%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct194
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9795.8161
Minimum0
Maximum134229
Zeros9
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-03-14T22:42:24.841415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.1
Q1101.5
median1093
Q39427
95-th percentile51396.5
Maximum134229
Range134229
Interquartile range (IQR)9325.5

Descriptive statistics

Standard deviation23011.86
Coefficient of variation (CV)2.3491519
Kurtosis17.609454
Mean9795.8161
Median Absolute Deviation (MAD)1082
Skewness4.0374852
Sum2184467
Variance5.2954571 × 108
MonotonicityNot monotonic
2024-03-14T22:42:25.306771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
4.0%
12 5
 
2.2%
11 5
 
2.2%
1 3
 
1.3%
143 2
 
0.9%
13 2
 
0.9%
228 2
 
0.9%
1123 2
 
0.9%
1009 2
 
0.9%
7 2
 
0.9%
Other values (184) 189
84.8%
ValueCountFrequency (%)
0 9
4.0%
1 3
 
1.3%
2 2
 
0.9%
6 1
 
0.4%
7 2
 
0.9%
8 1
 
0.4%
9 1
 
0.4%
10 1
 
0.4%
11 5
2.2%
12 5
2.2%
ValueCountFrequency (%)
134229 1
0.4%
133582 1
0.4%
132349 1
0.4%
127925 1
0.4%
124611 1
0.4%
120581 1
0.4%
58080 1
0.4%
57123 1
0.4%
55878 1
0.4%
54979 1
0.4%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct215
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6874956 × 109
Minimum0
Maximum2.3850938 × 1010
Zeros8
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-03-14T22:42:25.739730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile73900
Q152604000
median5.816 × 108
Q32.6074075 × 109
95-th percentile5.9679487 × 109
Maximum2.3850938 × 1010
Range2.3850938 × 1010
Interquartile range (IQR)2.5548035 × 109

Descriptive statistics

Standard deviation2.6866868 × 109
Coefficient of variation (CV)1.5921148
Kurtosis21.982786
Mean1.6874956 × 109
Median Absolute Deviation (MAD)5.80198 × 108
Skewness3.6483088
Sum3.7631152 × 1011
Variance7.2182857 × 1018
MonotonicityNot monotonic
2024-03-14T22:42:26.197711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8
 
3.6%
52604000 2
 
0.9%
259816000 1
 
0.4%
4617463000 1
 
0.4%
4985341000 1
 
0.4%
1852221000 1
 
0.4%
3336623000 1
 
0.4%
5388962000 1
 
0.4%
1986125000 1
 
0.4%
1516401000 1
 
0.4%
Other values (205) 205
91.9%
ValueCountFrequency (%)
0 8
3.6%
1000 1
 
0.4%
14000 1
 
0.4%
43000 1
 
0.4%
73000 1
 
0.4%
82000 1
 
0.4%
118000 1
 
0.4%
204000 1
 
0.4%
223000 1
 
0.4%
256000 1
 
0.4%
ValueCountFrequency (%)
23850938000 1
0.4%
12275958000 1
0.4%
11095710000 1
0.4%
10314773000 1
0.4%
9878112000 1
0.4%
9282159000 1
0.4%
7056180000 1
0.4%
6910036000 1
0.4%
6810802000 1
0.4%
6775915000 1
0.4%

Interactions

2024-03-14T22:42:19.838892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:18.687083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:19.362242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:19.989486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:18.930399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:19.518895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:20.151722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:19.214115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:19.679706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T22:42:26.472621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.7930.649
세원 유형명0.0001.0001.0000.9270.824
부과건수0.0000.7930.9271.0000.444
부과금액0.0000.6490.8240.4441.000
2024-03-14T22:42:26.733749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세원 유형명세목명
세원 유형명1.0000.908
세목명0.9081.000
2024-03-14T22:42:26.980618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도부과건수부과금액세목명세원 유형명
과세년도1.000-0.093-0.0320.0000.000
부과건수-0.0931.0000.5450.5190.620
부과금액-0.0320.5451.0000.3660.450
세목명0.0000.5190.3661.0000.908
세원 유형명0.0000.6200.4500.9081.000

Missing values

2024-03-14T22:42:20.472465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:42:20.886997image/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
0전라남도장성군468802017주민세주민세(재산분)522259816000
1전라남도장성군468802017주민세주민세(종업원분)412557860000
2전라남도장성군468802017주민세주민세(법인균등)139379964000
3전라남도장성군468802017주민세주민세(개인사업)110055436000
4전라남도장성군468802017주민세주민세(개인균등)19849199939000
5전라남도장성군468802017재산세재산세(주택)13786445956000
6전라남도장성군468802017재산세재산세(토지)522192187355000
7전라남도장성군468802017재산세재산세(선박)18118000
8전라남도장성군468802017재산세재산세(건축물)4291868075000
9전라남도장성군468802017자동차세자동차세(주행)126018715000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
213전라남도장성군468802022지방소득세지방소득세(특별징수)123364674524000
214전라남도장성군468802022지방소득세지방소득세(법인소득)18335964274000
215전라남도장성군468802022지방소득세지방소득세(양도소득)10392008646000
216전라남도장성군468802022지방소득세지방소득세(종합소득)6748830213000
217전라남도장성군468802022등록면허세등록면허세(면허)12263187524000
218전라남도장성군468802022등록면허세등록면허세(등록)139501563349000
219전라남도장성군468802022지역자원시설세지역자원시설세(소방)101701060949000
220전라남도장성군468802022지역자원시설세지역자원시설세(시설)00
221전라남도장성군468802022지역자원시설세지역자원시설세(특자)9852584000
222전라남도장성군468802022체납체납367692737071000