Overview

Dataset statistics

Number of variables9
Number of observations203
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.0 KiB
Average record size in memory75.7 B

Variable types

Categorical6
Numeric2
Boolean1

Dataset

Description산청군 지방세 납세자현황(시도명, 시군구명, 과세년도, 세목명, 납세자유형, 관내/관외, 납세자수 등) 자료 입니다.
Author경상남도 산청군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15078811

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2023-12-11 00:25:38.495002
Analysis finished2023-12-11 00:25:39.254684
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
경상남도
203 

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 203
100.0%

Length

2023-12-11T09:25:39.310656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:25:39.400954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 203
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
산청군
203 

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 203
100.0%

Length

2023-12-11T09:25:39.482067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:25:39.575868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
산청군 203
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
48860
203 

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 203
100.0%

Length

2023-12-11T09:25:39.660417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:25:39.740554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48860 203
100.0%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.5616
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T09:25:39.816789image/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 deviation1.7118982
Coefficient of variation (CV)0.00084765834
Kurtosis-1.2655422
Mean2019.5616
Median Absolute Deviation (MAD)1
Skewness-0.04313061
Sum409971
Variance2.9305955
MonotonicityIncreasing
2023-12-11T09:25:39.913423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2022 36
17.7%
2020 35
17.2%
2021 34
16.7%
2018 33
16.3%
2019 33
16.3%
2017 32
15.8%
ValueCountFrequency (%)
2017 32
15.8%
2018 33
16.3%
2019 33
16.3%
2020 35
17.2%
2021 34
16.7%
2022 36
17.7%
ValueCountFrequency (%)
2022 36
17.7%
2021 34
16.7%
2020 35
17.2%
2019 33
16.3%
2018 33
16.3%
2017 32
15.8%

세목명
Categorical

Distinct11
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
재산세
24 
주민세
24 
취득세
24 
자동차세
24 
등록면허세
24 
Other values (6)
83 

Length

Max length7
Median length5
Mean length4.1133005
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row등록세
2nd row등록세
3rd row등록세
4th row재산세
5th row재산세

Common Values

ValueCountFrequency (%)
재산세 24
11.8%
주민세 24
11.8%
취득세 24
11.8%
자동차세 24
11.8%
등록면허세 24
11.8%
지방소득세 24
11.8%
등록세 23
11.3%
지역자원시설세 19
9.4%
담배소비세 12
5.9%
지방소비세 3
 
1.5%

Length

2023-12-11T09:25:40.030921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재산세 24
11.8%
주민세 24
11.8%
취득세 24
11.8%
자동차세 24
11.8%
등록면허세 24
11.8%
지방소득세 24
11.8%
등록세 23
11.3%
지역자원시설세 19
9.4%
담배소비세 12
5.9%
지방소비세 3
 
1.5%

납세자유형
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
개인
103 
법인
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row개인
3rd row법인
4th row개인
5th row개인

Common Values

ValueCountFrequency (%)
개인 103
50.7%
법인 100
49.3%

Length

2023-12-11T09:25:40.188250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:25:40.305493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 103
50.7%
법인 100
49.3%

관내_관외
Boolean

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size335.0 B
False
104 
True
99 
ValueCountFrequency (%)
False 104
51.2%
True 99
48.8%
2023-12-11T09:25:40.403749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

Distinct167
Distinct (%)82.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3229.1478
Minimum1
Maximum35565
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T09:25:40.530755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q159.5
median595
Q32298.5
95-th percentile17971.7
Maximum35565
Range35564
Interquartile range (IQR)2239

Descriptive statistics

Standard deviation6989.8016
Coefficient of variation (CV)2.1645964
Kurtosis9.7453941
Mean3229.1478
Median Absolute Deviation (MAD)584
Skewness3.0992345
Sum655517
Variance48857326
MonotonicityNot monotonic
2023-12-11T09:25:40.662295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5
 
2.5%
2 5
 
2.5%
10 4
 
2.0%
13 4
 
2.0%
3 4
 
2.0%
9 4
 
2.0%
157 3
 
1.5%
5 3
 
1.5%
19 3
 
1.5%
7 3
 
1.5%
Other values (157) 165
81.3%
ValueCountFrequency (%)
1 5
2.5%
2 5
2.5%
3 4
2.0%
4 2
 
1.0%
5 3
1.5%
6 1
 
0.5%
7 3
1.5%
8 1
 
0.5%
9 4
2.0%
10 4
2.0%
ValueCountFrequency (%)
35565 1
0.5%
35158 1
0.5%
34558 1
0.5%
33803 1
0.5%
32864 1
0.5%
31930 1
0.5%
18480 1
0.5%
18260 1
0.5%
18170 1
0.5%
18027 1
0.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-08-04
203 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-04
2nd row2023-08-04
3rd row2023-08-04
4th row2023-08-04
5th row2023-08-04

Common Values

ValueCountFrequency (%)
2023-08-04 203
100.0%

Length

2023-12-11T09:25:40.778646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:25:40.884650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-04 203
100.0%

Interactions

2023-12-11T09:25:38.850321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:25:38.706632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:25:38.935776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:25:38.775427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:25:40.944103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명납세자유형관내_관외납세자수
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0000.0000.2160.569
납세자유형0.0000.0001.0000.0000.596
관내_관외0.0000.2160.0001.0000.584
납세자수0.0000.5690.5960.5841.000
2023-12-11T09:25:41.054277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형관내_관외
세목명1.0000.0000.201
납세자유형0.0001.0000.000
관내_관외0.2010.0001.000
2023-12-11T09:25:41.139508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도납세자수세목명납세자유형관내_관외
과세년도1.000-0.0190.0000.0000.000
납세자수-0.0191.0000.3090.4440.434
세목명0.0000.3091.0000.0000.201
납세자유형0.0000.4440.0001.0000.000
관내_관외0.0000.4340.2010.0001.000

Missing values

2023-12-11T09:25:39.067181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:25:39.198871image/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

시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수데이터기준일자
0경상남도산청군488602017등록세개인N1752023-08-04
1경상남도산청군488602017등록세개인Y1342023-08-04
2경상남도산청군488602017등록세법인Y132023-08-04
3경상남도산청군488602017재산세개인N319302023-08-04
4경상남도산청군488602017재산세개인Y177532023-08-04
5경상남도산청군488602017재산세법인N5722023-08-04
6경상남도산청군488602017재산세법인Y16932023-08-04
7경상남도산청군488602017주민세개인N21112023-08-04
8경상남도산청군488602017주민세개인Y166842023-08-04
9경상남도산청군488602017주민세법인N962023-08-04
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수데이터기준일자
193경상남도산청군488602022등록면허세법인N5592023-08-04
194경상남도산청군488602022등록면허세법인Y7662023-08-04
195경상남도산청군488602022지방소득세개인N8092023-08-04
196경상남도산청군488602022지방소득세개인Y54722023-08-04
197경상남도산청군488602022지방소득세법인N1572023-08-04
198경상남도산청군488602022지방소득세법인Y7422023-08-04
199경상남도산청군488602022지방소비세법인Y12023-08-04
200경상남도산청군488602022지역자원시설세개인N32023-08-04
201경상남도산청군488602022지역자원시설세개인Y92023-08-04
202경상남도산청군488602022지역자원시설세법인Y192023-08-04