Overview

Dataset statistics

Number of variables8
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory70.6 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description세목별 납세 인원 현황으로 자치단체명, 자치단체코드, 과세연도, 세목명, 납세자유형, 관내/관외, 납세자수로 구성되어 있음
Author경상남도 함양군
URLhttps://www.data.go.kr/data/15079296/fileData.do

Alerts

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

Reproduction

Analysis started2024-04-06 08:50:02.673898
Analysis finished2024-04-06 08:50:04.055629
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
경상남도
37 

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 37
100.0%

Length

2024-04-06T17:50:04.235925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:50:04.600553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 37
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
함양군
37 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
함양군 37
100.0%

Length

2024-04-06T17:50:04.940113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:50:05.518890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
함양군 37
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
48870
37 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48870
2nd row48870
3rd row48870
4th row48870
5th row48870

Common Values

ValueCountFrequency (%)
48870 37
100.0%

Length

2024-04-06T17:50:05.832896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:50:06.122165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48870 37
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
2022
37 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 37
100.0%

Length

2024-04-06T17:50:06.416829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:50:06.770704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 37
100.0%

세목명
Categorical

Distinct11
Distinct (%)29.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
등록세
4 
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
Other values (6)
17 

Length

Max length7
Median length5
Mean length4.1351351
Min length3

Unique

Unique1 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
등록세 4
10.8%
재산세 4
10.8%
주민세 4
10.8%
취득세 4
10.8%
자동차세 4
10.8%
등록면허세 4
10.8%
지방소득세 4
10.8%
지역자원시설세 4
10.8%
레저세 2
5.4%
담배소비세 2
5.4%

Length

2024-04-06T17:50:07.128374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록세 4
10.8%
재산세 4
10.8%
주민세 4
10.8%
취득세 4
10.8%
자동차세 4
10.8%
등록면허세 4
10.8%
지방소득세 4
10.8%
지역자원시설세 4
10.8%
레저세 2
5.4%
담배소비세 2
5.4%

납세자유형
Categorical

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
법인
19 
개인
18 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
법인 19
51.4%
개인 18
48.6%

Length

2024-04-06T17:50:07.556983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:50:07.907019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 19
51.4%
개인 18
48.6%

관내_관외
Boolean

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size169.0 B
False
20 
True
17 
ValueCountFrequency (%)
False 20
54.1%
True 17
45.9%
2024-04-06T17:50:08.194582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

Distinct34
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3012.7297
Minimum1
Maximum32070
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-04-06T17:50:08.553860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q137
median485
Q31552
95-th percentile18653.6
Maximum32070
Range32069
Interquartile range (IQR)1515

Descriptive statistics

Standard deviation6858.9586
Coefficient of variation (CV)2.2766591
Kurtosis9.5910908
Mean3012.7297
Median Absolute Deviation (MAD)468
Skewness3.0640784
Sum111471
Variance47045313
MonotonicityNot monotonic
2024-04-06T17:50:08.925126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
2 4
 
10.8%
803 1
 
2.7%
799 1
 
2.7%
417 1
 
2.7%
37 1
 
2.7%
4 1
 
2.7%
1552 1
 
2.7%
5351 1
 
2.7%
485 1
 
2.7%
848 1
 
2.7%
Other values (24) 24
64.9%
ValueCountFrequency (%)
1 1
 
2.7%
2 4
10.8%
4 1
 
2.7%
8 1
 
2.7%
15 1
 
2.7%
17 1
 
2.7%
37 1
 
2.7%
41 1
 
2.7%
47 1
 
2.7%
74 1
 
2.7%
ValueCountFrequency (%)
32070 1
2.7%
20272 1
2.7%
18249 1
2.7%
13003 1
2.7%
5460 1
2.7%
5351 1
2.7%
4059 1
2.7%
1636 1
2.7%
1578 1
2.7%
1552 1
2.7%

Interactions

2024-04-06T17:50:03.122119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:50:09.257042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형관내_관외납세자수
세목명1.0000.0000.0000.000
납세자유형0.0001.0000.0000.496
관내_관외0.0000.0001.0000.487
납세자수0.0000.4960.4871.000
2024-04-06T17:50:09.542944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형세목명관내_관외
납세자유형1.0000.0000.000
세목명0.0001.0000.000
관내_관외0.0000.0001.000
2024-04-06T17:50:09.816014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수세목명납세자유형관내_관외
납세자수1.0000.0000.3320.325
세목명0.0001.0000.0000.000
납세자유형0.3320.0001.0000.000
관내_관외0.3250.0000.0001.000

Missing values

2024-04-06T17:50:03.507934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:50:03.917168image/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_관외납세자수
0경상남도함양군488702022등록세개인N803
1경상남도함양군488702022등록세개인Y644
2경상남도함양군488702022등록세법인N8
3경상남도함양군488702022등록세법인Y47
4경상남도함양군488702022레저세개인N2
5경상남도함양군488702022레저세법인N2
6경상남도함양군488702022재산세개인N32070
7경상남도함양군488702022재산세개인Y20272
8경상남도함양군488702022재산세법인N442
9경상남도함양군488702022재산세법인Y1578
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
27경상남도함양군488702022등록면허세법인Y799
28경상남도함양군488702022지방소득세개인N848
29경상남도함양군488702022지방소득세개인Y5460
30경상남도함양군488702022지방소득세법인N177
31경상남도함양군488702022지방소득세법인Y692
32경상남도함양군488702022지방소비세법인Y1
33경상남도함양군488702022지역자원시설세개인N2
34경상남도함양군488702022지역자원시설세개인Y17
35경상남도함양군488702022지역자원시설세법인N2
36경상남도함양군488702022지역자원시설세법인Y15