Overview

Dataset statistics

Number of variables8
Number of observations107
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory67.2 B

Variable types

Categorical6
Boolean1
Text1

Dataset

Description2017년부터 2019년 지방세 세목별 납세자 유형과 지방세 세목별 납세자 거주지역, 지방세 세목별 납세자수를 포함한 데이터입니다.
Author경상남도 양산시
URLhttps://www.data.go.kr/data/15079424/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 11:54:24.076874
Analysis finished2023-12-12 11:54:24.737399
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size988.0 B
경상남도
107 

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 107
100.0%

Length

2023-12-12T20:54:24.814092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:54:24.946622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 107
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size988.0 B
양산시
107 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양산시 107
100.0%

Length

2023-12-12T20:54:25.066594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:54:25.173780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양산시 107
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size988.0 B
48330
107 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48330
2nd row48330
3rd row48330
4th row48330
5th row48330

Common Values

ValueCountFrequency (%)
48330 107
100.0%

Length

2023-12-12T20:54:25.296716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:54:25.408596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48330 107
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size988.0 B
2018
36 
2019
36 
2017
35 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2018 36
33.6%
2019 36
33.6%
2017 35
32.7%

Length

2023-12-12T20:54:25.534673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:54:25.650263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 36
33.6%
2019 36
33.6%
2017 35
32.7%

세목명
Categorical

Distinct10
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size988.0 B
등록세
12 
재산세
12 
주민세
12 
취득세
12 
자동차세
12 
Other values (5)
47 

Length

Max length7
Median length5
Mean length4.1775701
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
등록세 12
11.2%
재산세 12
11.2%
주민세 12
11.2%
취득세 12
11.2%
자동차세 12
11.2%
등록면허세 12
11.2%
지방소득세 12
11.2%
지역자원시설세 12
11.2%
담배소비세 9
8.4%
레저세 2
 
1.9%

Length

2023-12-12T20:54:25.795761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:54:25.962370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록세 12
11.2%
재산세 12
11.2%
주민세 12
11.2%
취득세 12
11.2%
자동차세 12
11.2%
등록면허세 12
11.2%
지방소득세 12
11.2%
지역자원시설세 12
11.2%
담배소비세 9
8.4%
레저세 2
 
1.9%

납세자유형
Categorical

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size988.0 B
개인
56 
법인
51 

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 (%)
개인 56
52.3%
법인 51
47.7%

Length

2023-12-12T20:54:26.155786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:54:26.287539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 56
52.3%
법인 51
47.7%

관내_관외
Boolean

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size239.0 B
False
56 
True
51 
ValueCountFrequency (%)
False 56
52.3%
True 51
47.7%
2023-12-12T20:54:26.380408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Text

Distinct97
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-12T20:54:26.692968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.1682243
Min length1

Characters and Unicode

Total characters446
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)83.2%

Sample

1st row119
2nd row113
3rd row7
4th row5
5th row52,947
ValueCountFrequency (%)
12 3
 
2.8%
2 3
 
2.8%
7 2
 
1.9%
5 2
 
1.9%
13 2
 
1.9%
17 2
 
1.9%
9 2
 
1.9%
1 2
 
1.9%
55,741 1
 
0.9%
82 1
 
0.9%
Other values (87) 87
81.3%
2023-12-12T20:54:27.263476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 79
17.7%
, 66
14.8%
2 53
11.9%
3 41
9.2%
9 35
7.8%
5 33
7.4%
4 32
7.2%
0 31
 
7.0%
8 30
 
6.7%
7 26
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 380
85.2%
Other Punctuation 66
 
14.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 79
20.8%
2 53
13.9%
3 41
10.8%
9 35
9.2%
5 33
8.7%
4 32
8.4%
0 31
 
8.2%
8 30
 
7.9%
7 26
 
6.8%
6 20
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 446
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 79
17.7%
, 66
14.8%
2 53
11.9%
3 41
9.2%
9 35
7.8%
5 33
7.4%
4 32
7.2%
0 31
 
7.0%
8 30
 
6.7%
7 26
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 79
17.7%
, 66
14.8%
2 53
11.9%
3 41
9.2%
9 35
7.8%
5 33
7.4%
4 32
7.2%
0 31
 
7.0%
8 30
 
6.7%
7 26
 
5.8%

Correlations

2023-12-12T20:54:27.428113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명납세자유형관내_관외납세자수
과세년도1.0000.0000.0000.0000.034
세목명0.0001.0000.0000.0000.897
납세자유형0.0000.0001.0000.0000.000
관내_관외0.0000.0000.0001.0000.873
납세자수0.0340.8970.0000.8731.000
2023-12-12T20:54:27.581202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명관내_관외과세년도납세자유형
세목명1.0000.0000.0000.000
관내_관외0.0001.0000.0000.000
과세년도0.0000.0001.0000.000
납세자유형0.0000.0000.0001.000
2023-12-12T20:54:27.720466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명납세자유형관내_관외
과세년도1.0000.0000.0000.000
세목명0.0001.0000.0000.000
납세자유형0.0000.0001.0000.000
관내_관외0.0000.0000.0001.000

Missing values

2023-12-12T20:54:24.444644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:54:24.663285image/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
0경상남도양산시483302017등록세개인N119
1경상남도양산시483302017등록세개인Y113
2경상남도양산시483302017등록세법인N7
3경상남도양산시483302017등록세법인Y5
4경상남도양산시483302017재산세개인N52,947
5경상남도양산시483302017재산세개인Y88,041
6경상남도양산시483302017재산세법인N1,059
7경상남도양산시483302017재산세법인Y2,172
8경상남도양산시483302017주민세개인N19,936
9경상남도양산시483302017주민세개인Y116,897
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
97경상남도양산시483302019등록면허세법인N2,288
98경상남도양산시483302019등록면허세법인Y3,449
99경상남도양산시483302019지방소득세개인N7,644
100경상남도양산시483302019지방소득세개인Y46,728
101경상남도양산시483302019지방소득세법인N1,552
102경상남도양산시483302019지방소득세법인Y3,461
103경상남도양산시483302019지역자원시설세개인N16
104경상남도양산시483302019지역자원시설세개인Y36
105경상남도양산시483302019지역자원시설세법인N17
106경상남도양산시483302019지역자원시설세법인Y110