Overview

Dataset statistics

Number of variables8
Number of observations140
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 KiB
Average record size in memory68.9 B

Variable types

Categorical6
Numeric2

Dataset

Description산청군 세원유형별 과세현황(시군구명, 과세년도, 세목명 , 세원 유형명 , 부과건수 , 부과금액 등) 데이터 자료입니다.
Author경상남도 산청군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15078803

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 38 (27.1%) zerosZeros
부과금액 has 38 (27.1%) zerosZeros

Reproduction

Analysis started2023-12-11 00:55:17.068396
Analysis finished2023-12-11 00:55:17.913959
Duration0.85 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
경상남도
140 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 140
100.0%

Length

2023-12-11T09:55:17.973554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:55:18.055207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 140
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
산청군
140 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
산청군 140
100.0%

Length

2023-12-11T09:55:18.146718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:55:18.260758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
산청군 140
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
48860
140 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48860
2nd row48860
3rd row48860
4th row48860
5th row48860

Common Values

ValueCountFrequency (%)
48860 140
100.0%

Length

2023-12-11T09:55:18.376118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:55:18.470620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48860 140
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2019
47 
2018
47 
2017
46 

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
33.6%
2018 47
33.6%
2017 46
32.9%

Length

2023-12-11T09:55:18.571699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:55:18.686376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 47
33.6%
2018 47
33.6%
2017 46
32.9%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
취득세
27 
주민세
27 
자동차세
21 
재산세
15 
레저세
12 
Other values (8)
38 

Length

Max length7
Median length3
Mean length3.6714286
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 27
19.3%
주민세 27
19.3%
자동차세 21
15.0%
재산세 15
10.7%
레저세 12
8.6%
지방소득세 12
8.6%
등록면허세 6
 
4.3%
지역자원시설세 6
 
4.3%
담배소비세 3
 
2.1%
지방소비세 3
 
2.1%
Other values (3) 8
 
5.7%

Length

2023-12-11T09:55:18.794941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 27
19.3%
주민세 27
19.3%
자동차세 21
15.0%
재산세 15
10.7%
레저세 12
8.6%
지방소득세 12
8.6%
등록면허세 6
 
4.3%
지역자원시설세 6
 
4.3%
담배소비세 3
 
2.1%
지방소비세 3
 
2.1%
Other values (3) 8
 
5.7%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)33.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
기타승용
 
3
경정
 
3
건축물
 
3
주택(개별)
 
3
주택(단독)
 
3
Other values (42)
125 

Length

Max length11
Median length8
Mean length6.05
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타승용 3
 
2.1%
경정 3
 
2.1%
건축물 3
 
2.1%
주택(개별) 3
 
2.1%
주택(단독) 3
 
2.1%
기타 3
 
2.1%
항공기 3
 
2.1%
기계장비 3
 
2.1%
차량 3
 
2.1%
선박 3
 
2.1%
Other values (37) 110
78.6%

Length

2023-12-11T09:55:18.918350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타승용 3
 
2.1%
승합 3
 
2.1%
주민세(재산분 3
 
2.1%
주민세(종업원분 3
 
2.1%
주민세(특별징수 3
 
2.1%
주민세(법인세분 3
 
2.1%
주민세(양도소득 3
 
2.1%
주민세(종합소득 3
 
2.1%
주민세(법인균등 3
 
2.1%
주민세(개인사업 3
 
2.1%
Other values (37) 110
78.6%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct100
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6511.6286
Minimum0
Maximum109718
Zeros38
Zeros (%)27.1%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:55:19.028386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median240.5
Q34447.5
95-th percentile25896.6
Maximum109718
Range109718
Interquartile range (IQR)4447.5

Descriptive statistics

Standard deviation17836.412
Coefficient of variation (CV)2.739163
Kurtosis22.388687
Mean6511.6286
Median Absolute Deviation (MAD)240.5
Skewness4.5317052
Sum911628
Variance3.1813759 × 108
MonotonicityNot monotonic
2023-12-11T09:55:19.156277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38
27.1%
12 2
 
1.4%
155 2
 
1.4%
2 2
 
1.4%
109264 1
 
0.7%
3803 1
 
0.7%
1 1
 
0.7%
2888 1
 
0.7%
133 1
 
0.7%
4 1
 
0.7%
Other values (90) 90
64.3%
ValueCountFrequency (%)
0 38
27.1%
1 1
 
0.7%
2 2
 
1.4%
4 1
 
0.7%
10 1
 
0.7%
12 2
 
1.4%
23 1
 
0.7%
24 1
 
0.7%
31 1
 
0.7%
49 1
 
0.7%
ValueCountFrequency (%)
109718 1
0.7%
109264 1
0.7%
107328 1
0.7%
54167 1
0.7%
52947 1
0.7%
51408 1
0.7%
30050 1
0.7%
25678 1
0.7%
24941 1
0.7%
20457 1
0.7%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct103
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.5335421 × 108
Minimum0
Maximum5.947184 × 109
Zeros38
Zeros (%)27.1%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:55:19.290941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.703795 × 108
Q39.8135025 × 108
95-th percentile3.2456278 × 109
Maximum5.947184 × 109
Range5.947184 × 109
Interquartile range (IQR)9.8135025 × 108

Descriptive statistics

Standard deviation1.219849 × 109
Coefficient of variation (CV)1.6192237
Kurtosis4.7511881
Mean7.5335421 × 108
Median Absolute Deviation (MAD)1.703795 × 108
Skewness2.1673915
Sum1.0546959 × 1011
Variance1.4880316 × 1018
MonotonicityNot monotonic
2023-12-11T09:55:19.423214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38
27.1%
7009000 1
 
0.7%
447881000 1
 
0.7%
2345825000 1
 
0.7%
182765000 1
 
0.7%
53034000 1
 
0.7%
320605000 1
 
0.7%
1020039000 1
 
0.7%
1492014000 1
 
0.7%
2368631000 1
 
0.7%
Other values (93) 93
66.4%
ValueCountFrequency (%)
0 38
27.1%
154000 1
 
0.7%
162000 1
 
0.7%
212000 1
 
0.7%
714000 1
 
0.7%
759000 1
 
0.7%
964000 1
 
0.7%
1904000 1
 
0.7%
3881000 1
 
0.7%
7009000 1
 
0.7%
ValueCountFrequency (%)
5947184000 1
0.7%
5351510000 1
0.7%
5110137000 1
0.7%
4730376000 1
0.7%
4694127000 1
0.7%
3298894000 1
0.7%
3252389000 1
0.7%
3245272000 1
0.7%
3058349000 1
0.7%
2745491000 1
0.7%

Interactions

2023-12-11T09:55:17.471585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:55:17.319026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:55:17.598509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:55:17.395545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:55:19.521458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8780.710
세원 유형명0.0001.0001.0000.9960.921
부과건수0.0000.8780.9961.0000.744
부과금액0.0000.7100.9210.7441.000
2023-12-11T09:55:19.614233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세원 유형명세목명
과세년도1.0000.0000.000
세원 유형명0.0001.0000.856
세목명0.0000.8561.000
2023-12-11T09:55:20.024320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액과세년도세목명세원 유형명
부과건수1.0000.7860.0000.7030.809
부과금액0.7861.0000.0000.3960.548
과세년도0.0000.0001.0000.0000.000
세목명0.7030.3960.0001.0000.856
세원 유형명0.8090.5480.0000.8561.000

Missing values

2023-12-11T09:55:17.729191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:55:17.865427image/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
0경상남도산청군488602019자동차세기타승용857009000
1경상남도산청군488602017담배소비세담배소비세1092458010000
2경상남도산청군488602017취득세건축물8881366305000
3경상남도산청군488602017취득세주택(개별)11641190366000
4경상남도산청군488602017취득세주택(단독)111129489000
5경상남도산청군488602017취득세기타2377518000
6경상남도산청군488602017취득세항공기00
7경상남도산청군488602017취득세기계장비163235502000
8경상남도산청군488602017취득세차량29442260812000
9경상남도산청군488602017취득세선박2154000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
130경상남도산청군488602019지방소득세지방소득세(법인소득)6171683791000
131경상남도산청군488602019지방소득세지방소득세(양도소득)647742892000
132경상남도산청군488602019지방소득세지방소득세(종합소득)2415476825000
133경상남도산청군488602019등록면허세등록면허세(면허)8341137818000
134경상남도산청군488602019등록면허세등록면허세(등록)11135968454000
135경상남도산청군488602019지역자원시설세지역자원시설세(소방)10423489952000
136경상남도산청군488602019지역자원시설세지역자원시설세(특자)171230303000
137경상남도산청군488602019지방소비세지방소비세00
138경상남도산청군488602019교육세교육세1097183298894000
139경상남도산청군488602019체납체납249411352744000