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

Description경상남도 사천시 세원 유형별 과세현황(2018 ~ 2020년)에 대한 데이터로 지방세 과세를 위해 세원이 되는 과세 대상 유형별 부과된 현황을 제공합니다.
Author경상남도 사천시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15079573

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 24 (17.8%) zerosZeros
부과금액 has 25 (18.5%) zerosZeros

Reproduction

Analysis started2023-12-11 00:08:44.357553
Analysis finished2023-12-11 00:08:45.328290
Duration0.97 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
135 

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 135
100.0%

Length

2023-12-11T09:08:45.395478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:08:45.495020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 135
100.0%

시군구명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사천시 135
100.0%

Length

2023-12-11T09:08:45.596224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:08:45.687415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사천시 135
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
48240
135 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48240
2nd row48240
3rd row48240
4th row48240
5th row48240

Common Values

ValueCountFrequency (%)
48240 135
100.0%

Length

2023-12-11T09:08:45.781483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:08:45.879092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48240 135
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2018
47 
2020
47 
2019
41 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 47
34.8%
2020 47
34.8%
2019 41
30.4%

Length

2023-12-11T09:08:45.993173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:08:46.129118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 47
34.8%
2020 47
34.8%
2019 41
30.4%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
취득세
27 
주민세
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 row담배소비세
2nd row도시계획세
3rd row취득세
4th row취득세
5th row취득세

Common Values

ValueCountFrequency (%)
취득세 27
20.0%
주민세 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%
담배소비세 3
 
2.2%
교육세 3
 
2.2%
Other values (3) 7
 
5.2%

Length

2023-12-11T09:08:46.301463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 27
20.0%
주민세 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%
담배소비세 3
 
2.2%
교육세 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
담배소비세
 
3
주택(개별)
 
3
승합
 
3
항공기
 
3
기계장비
 
3
Other values (42)
120 

Length

Max length11
Median length8
Mean length6.1703704
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
담배소비세 3
 
2.2%
주택(개별) 3
 
2.2%
승합 3
 
2.2%
항공기 3
 
2.2%
기계장비 3
 
2.2%
차량 3
 
2.2%
선박 3
 
2.2%
토지 3
 
2.2%
특수 3
 
2.2%
주택(단독) 3
 
2.2%
Other values (37) 105
77.8%

Length

2023-12-11T09:08:46.422374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
담배소비세 3
 
2.2%
주민세(법인균등 3
 
2.2%
주택(개별 3
 
2.2%
승용 3
 
2.2%
주민세(재산분 3
 
2.2%
주민세(종업원분 3
 
2.2%
주민세(특별징수 3
 
2.2%
주민세(법인세분 3
 
2.2%
주민세(양도소득 3
 
2.2%
지역자원시설세(특자 3
 
2.2%
Other values (37) 105
77.8%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct106
Distinct (%)78.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16653.667
Minimum0
Maximum267751
Zeros24
Zeros (%)17.8%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-11T09:08:46.560260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q134
median1201
Q311772.5
95-th percentile71671.7
Maximum267751
Range267751
Interquartile range (IQR)11738.5

Descriptive statistics

Standard deviation42660.32
Coefficient of variation (CV)2.5616172
Kurtosis23.347531
Mean16653.667
Median Absolute Deviation (MAD)1201
Skewness4.5440761
Sum2248245
Variance1.8199029 × 109
MonotonicityNot monotonic
2023-12-11T09:08:46.705980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 24
 
17.8%
12 3
 
2.2%
1088 2
 
1.5%
34 2
 
1.5%
6 2
 
1.5%
2 2
 
1.5%
276 1
 
0.7%
1201 1
 
0.7%
261489 1
 
0.7%
82348 1
 
0.7%
Other values (96) 96
71.1%
ValueCountFrequency (%)
0 24
17.8%
1 1
 
0.7%
2 2
 
1.5%
6 2
 
1.5%
10 1
 
0.7%
12 3
 
2.2%
34 2
 
1.5%
44 1
 
0.7%
69 1
 
0.7%
87 1
 
0.7%
ValueCountFrequency (%)
267751 1
0.7%
261489 1
0.7%
260266 1
0.7%
87633 1
0.7%
84327 1
0.7%
82348 1
0.7%
72469 1
0.7%
71330 1
0.7%
70676 1
0.7%
64656 1
0.7%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct111
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2798401 × 109
Minimum0
Maximum1.953098 × 1010
Zeros25
Zeros (%)18.5%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-11T09:08:46.847044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111102000
median4.63739 × 108
Q34.8254195 × 109
95-th percentile1.2279111 × 1010
Maximum1.953098 × 1010
Range1.953098 × 1010
Interquartile range (IQR)4.8143175 × 109

Descriptive statistics

Standard deviation4.4189938 × 109
Coefficient of variation (CV)1.3473199
Kurtosis1.3049655
Mean3.2798401 × 109
Median Absolute Deviation (MAD)4.63739 × 108
Skewness1.4027243
Sum4.4277841 × 1011
Variance1.9527506 × 1019
MonotonicityNot monotonic
2023-12-11T09:08:47.002595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25
 
18.5%
9546688000 1
 
0.7%
243821000 1
 
0.7%
8312937000 1
 
0.7%
239139000 1
 
0.7%
1041119000 1
 
0.7%
17981530000 1
 
0.7%
2883529000 1
 
0.7%
4479415000 1
 
0.7%
10146660000 1
 
0.7%
Other values (101) 101
74.8%
ValueCountFrequency (%)
0 25
18.5%
3107000 1
 
0.7%
3792000 1
 
0.7%
4337000 1
 
0.7%
4870000 1
 
0.7%
5734000 1
 
0.7%
7255000 1
 
0.7%
9405000 1
 
0.7%
10298000 1
 
0.7%
10772000 1
 
0.7%
ValueCountFrequency (%)
19530980000 1
0.7%
17981530000 1
0.7%
13539985000 1
0.7%
13188211000 1
0.7%
13151863000 1
0.7%
12737531000 1
0.7%
12307546000 1
0.7%
12266925000 1
0.7%
12044868000 1
0.7%
12029568000 1
0.7%

Interactions

2023-12-11T09:08:44.895177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:08:44.682841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:08:44.997577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:08:44.774343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:08:47.096322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8900.727
세원 유형명0.0001.0001.0001.0000.949
부과건수0.0000.8901.0001.0000.722
부과금액0.0000.7270.9490.7221.000
2023-12-11T09:08:47.201823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세원 유형명과세년도세목명
세원 유형명1.0000.0000.849
과세년도0.0001.0000.000
세목명0.8490.0001.000
2023-12-11T09:08:47.297671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액과세년도세목명세원 유형명
부과건수1.0000.7110.0000.7240.823
부과금액0.7111.0000.0000.4290.617
과세년도0.0000.0001.0000.0000.000
세목명0.7240.4290.0001.0000.849
세원 유형명0.8230.6170.0000.8491.000

Missing values

2023-12-11T09:08:45.142289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:08:45.280023image/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
0경상남도사천시482402018담배소비세담배소비세879546688000
1경상남도사천시482402018도시계획세도시계획세00
2경상남도사천시482402018취득세건축물9294806240000
3경상남도사천시482402018취득세주택(개별)15684722293000
4경상남도사천시482402018취득세주택(단독)17908197445000
5경상남도사천시482402018취득세기타34305837000
6경상남도사천시482402018취득세항공기195181000
7경상남도사천시482402018취득세기계장비310355696000
8경상남도사천시482402018취득세차량83657110026000
9경상남도사천시482402018취득세선박135255864000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
125경상남도사천시482402020지방소득세지방소득세(법인소득)165511244590000
126경상남도사천시482402020지방소득세지방소득세(양도소득)13981980820000
127경상남도사천시482402020지방소득세지방소득세(종합소득)106122620168000
128경상남도사천시482402020지방소비세지방소비세60
129경상남도사천시482402020등록면허세등록면허세(면허)19460331809000
130경상남도사천시482402020등록면허세등록면허세(등록)312353267876000
131경상남도사천시482402020지역자원시설세지역자원시설세(소방)430393120362000
132경상남도사천시482402020지역자원시설세지역자원시설세(특자)90252626000
133경상남도사천시482402020교육세교육세26775113539985000
134경상남도사천시482402020체납체납843276406435000