Overview

Dataset statistics

Number of variables8
Number of observations135
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory69.0 B

Variable types

Categorical6
Numeric2

Dataset

Description지방세 과세를 위해 세원이 되는 과세 대상 유형별 부과된 현황을 제공
Author경상북도 의성군
URLhttps://www.data.go.kr/data/15079686/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
부과건수 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
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
부과건수 has 30 (22.2%) zerosZeros
부과금액 has 30 (22.2%) zerosZeros

Reproduction

Analysis started2023-12-12 19:03:39.476309
Analysis finished2023-12-12 19:03:40.421169
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
경상북도
135 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 135
100.0%

Length

2023-12-13T04:03:40.524915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:03:40.662368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 135
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
의성군
135 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
의성군 135
100.0%

Length

2023-12-13T04:03:40.789462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:03:40.930552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의성군 135
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
47730
135 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47730
2nd row47730
3rd row47730
4th row47730
5th row47730

Common Values

ValueCountFrequency (%)
47730 135
100.0%

Length

2023-12-13T04:03:41.074535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:03:41.200624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47730 135
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2019
47 
2018
47 
2017
41 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2019 47
34.8%
2018 47
34.8%
2017 41
30.4%

Length

2023-12-13T04:03:41.327748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:03:41.465991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 47
34.8%
2018 47
34.8%
2017 41
30.4%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
주민세
27 
취득세
27 
자동차세
21 
재산세
15 
지방소득세
12 
Other values (8)
33 

Length

Max length7
Median length3
Mean length3.6814815
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주민세 27
20.0%
취득세 27
20.0%
자동차세 21
15.6%
재산세 15
11.1%
지방소득세 12
8.9%
레저세 8
 
5.9%
등록면허세 6
 
4.4%
지역자원시설세 6
 
4.4%
교육세 3
 
2.2%
담배소비세 3
 
2.2%
Other values (3) 7
 
5.2%

Length

2023-12-13T04:03:41.629642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주민세 27
20.0%
취득세 27
20.0%
자동차세 21
15.6%
재산세 15
11.1%
지방소득세 12
8.9%
레저세 8
 
5.9%
등록면허세 6
 
4.4%
지역자원시설세 6
 
4.4%
교육세 3
 
2.2%
담배소비세 3
 
2.2%
Other values (3) 7
 
5.2%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
주민세(특별징수)
 
3
선박
 
3
지방소득세(특별징수)
 
3
건축물
 
3
주택(개별)
 
3
Other values (42)
120 

Length

Max length11
Median length8
Mean length6.1703704
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주민세(특별징수) 3
 
2.2%
선박 3
 
2.2%
지방소득세(특별징수) 3
 
2.2%
건축물 3
 
2.2%
주택(개별) 3
 
2.2%
주택(단독) 3
 
2.2%
기타 3
 
2.2%
항공기 3
 
2.2%
기계장비 3
 
2.2%
화물 3
 
2.2%
Other values (37) 105
77.8%

Length

2023-12-13T04:03:41.781321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주민세(특별징수 3
 
2.2%
주민세(개인균등 3
 
2.2%
선박 3
 
2.2%
교육세 3
 
2.2%
주민세(종업원분 3
 
2.2%
주민세(법인세분 3
 
2.2%
주민세(양도소득 3
 
2.2%
주민세(종합소득 3
 
2.2%
주민세(법인균등 3
 
2.2%
체납 3
 
2.2%
Other values (37) 105
77.8%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct101
Distinct (%)74.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9382.2741
Minimum0
Maximum151845
Zeros30
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T04:03:41.946077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.5
median383
Q35713.5
95-th percentile48112.4
Maximum151845
Range151845
Interquartile range (IQR)5708

Descriptive statistics

Standard deviation25432.68
Coefficient of variation (CV)2.710716
Kurtosis20.030351
Mean9382.2741
Median Absolute Deviation (MAD)383
Skewness4.2974652
Sum1266607
Variance6.4682123 × 108
MonotonicityNot monotonic
2023-12-13T04:03:42.112986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30
 
22.2%
2 3
 
2.2%
12 3
 
2.2%
651 2
 
1.5%
53 1
 
0.7%
3 1
 
0.7%
4480 1
 
0.7%
241 1
 
0.7%
19 1
 
0.7%
212 1
 
0.7%
Other values (91) 91
67.4%
ValueCountFrequency (%)
0 30
22.2%
2 3
 
2.2%
3 1
 
0.7%
8 1
 
0.7%
10 1
 
0.7%
11 1
 
0.7%
12 3
 
2.2%
13 1
 
0.7%
18 1
 
0.7%
19 1
 
0.7%
ValueCountFrequency (%)
151845 1
0.7%
150826 1
0.7%
147410 1
0.7%
76064 1
0.7%
74923 1
0.7%
73405 1
0.7%
50526 1
0.7%
47078 1
0.7%
46802 1
0.7%
29102 1
0.7%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct106
Distinct (%)78.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.7498058 × 108
Minimum0
Maximum9.131799 × 109
Zeros30
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T04:03:42.294178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1329000
median1.73991 × 108
Q38.883785 × 108
95-th percentile4.124019 × 109
Maximum9.131799 × 109
Range9.131799 × 109
Interquartile range (IQR)8.880495 × 108

Descriptive statistics

Standard deviation1.6527367 × 109
Coefficient of variation (CV)1.6951483
Kurtosis5.7533568
Mean9.7498058 × 108
Median Absolute Deviation (MAD)1.73991 × 108
Skewness2.3103669
Sum1.3162238 × 1011
Variance2.7315386 × 1018
MonotonicityNot monotonic
2023-12-13T04:03:42.818319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30
 
22.2%
635413000 1
 
0.7%
414000 1
 
0.7%
3335442000 1
 
0.7%
221042000 1
 
0.7%
47703000 1
 
0.7%
560262000 1
 
0.7%
865588000 1
 
0.7%
834590000 1
 
0.7%
4118682000 1
 
0.7%
Other values (96) 96
71.1%
ValueCountFrequency (%)
0 30
22.2%
93000 1
 
0.7%
115000 1
 
0.7%
171000 1
 
0.7%
298000 1
 
0.7%
360000 1
 
0.7%
414000 1
 
0.7%
1270000 1
 
0.7%
1317000 1
 
0.7%
1325000 1
 
0.7%
ValueCountFrequency (%)
9131799000 1
0.7%
6504385000 1
0.7%
6162153000 1
0.7%
6121339000 1
0.7%
5933096000 1
0.7%
5089092000 1
0.7%
4136472000 1
0.7%
4118682000 1
0.7%
4038852000 1
0.7%
3891829000 1
0.7%

Interactions

2023-12-13T04:03:39.973897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:39.779643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:40.091332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:39.882085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:03:42.963035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8490.682
세원 유형명0.0001.0001.0000.9700.903
부과건수0.0000.8490.9701.0000.703
부과금액0.0000.6820.9030.7031.000
2023-12-13T04:03:43.097381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세원 유형명과세년도세목명
세원 유형명1.0000.0000.849
과세년도0.0001.0000.000
세목명0.8490.0001.000
2023-12-13T04:03:43.230502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액과세년도세목명세원 유형명
부과건수1.0000.7790.0000.6160.689
부과금액0.7791.0000.0000.3700.508
과세년도0.0000.0001.0000.0000.000
세목명0.6160.3700.0001.0000.849
세원 유형명0.6890.5080.0000.8491.000

Missing values

2023-12-13T04:03:40.230924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:03:40.367544image/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
0경상북도의성군477302019주민세주민세(특별징수)00
1경상북도의성군477302017교육세교육세1474104038852000
2경상북도의성군477302017취득세건축물6512112456000
3경상북도의성군477302017취득세주택(개별)1413941193000
4경상북도의성군477302017취득세주택(단독)269523490000
5경상북도의성군477302017취득세기타1331822000
6경상북도의성군477302017취득세항공기00
7경상북도의성군477302017취득세기계장비283269428000
8경상북도의성군477302017취득세차량46263124872000
9경상북도의성군477302017취득세선박2115000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
125경상북도의성군477302019지방소득세지방소득세(법인소득)8431914664000
126경상북도의성군477302019지방소득세지방소득세(양도소득)651488203000
127경상북도의성군477302019지방소득세지방소득세(종합소득)2898583195000
128경상북도의성군477302019등록면허세등록면허세(면허)10354183412000
129경상북도의성군477302019등록면허세등록면허세(등록)12701928943000
130경상북도의성군477302019지역자원시설세지역자원시설세(소방)9611401701000
131경상북도의성군477302019지역자원시설세지역자원시설세(특자)6313393000
132경상북도의성군477302019지방소비세지방소비세00
133경상북도의성군477302019담배소비세담배소비세813447749000
134경상북도의성군477302019체납체납505262040043000