Overview

Dataset statistics

Number of variables9
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory77.7 B

Variable types

Categorical5
Text4

Dataset

Description연도 별 지방세 과세 및 비과세 현황을 세목별로 제공하며, 국민 조세혜택 규모를 파악하는 데 사용하는 데이터 지표를 제공합니다.
Author경상북도 성주군
URLhttps://www.data.go.kr/data/15078608/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 00:02:43.179639
Analysis finished2023-12-12 00:02:43.734785
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
경상북도
36 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 36
100.0%

Length

2023-12-12T09:02:43.810974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:02:43.960768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 36
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
성주군
36 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성주군 36
100.0%

Length

2023-12-12T09:02:44.094315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:02:44.227566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성주군 36
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
47840
36 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47840
2nd row47840
3rd row47840
4th row47840
5th row47840

Common Values

ValueCountFrequency (%)
47840 36
100.0%

Length

2023-12-12T09:02:44.369732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:02:44.504119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47840 36
100.0%

과세년도
Categorical

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
2017
13 
2019
13 
2018
10 

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 (%)
2017 13
36.1%
2019 13
36.1%
2018 10
27.8%

Length

2023-12-12T09:02:44.616535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:02:44.731756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 13
36.1%
2019 13
36.1%
2018 10
27.8%

세목명
Categorical

Distinct13
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
취득세
3 
등록세
3 
주민세
3 
재산세
3 
자동차세
3 
Other values (8)
21 

Length

Max length7
Median length5
Mean length4.1388889
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취득세
2nd row등록세
3rd row주민세
4th row재산세
5th row자동차세

Common Values

ValueCountFrequency (%)
취득세 3
8.3%
등록세 3
8.3%
주민세 3
8.3%
재산세 3
8.3%
자동차세 3
8.3%
담배소비세 3
8.3%
등록면허세 3
8.3%
지역자원시설세 3
8.3%
지방소득세 3
8.3%
교육세 3
8.3%
Other values (3) 6
16.7%

Length

2023-12-12T09:02:44.855346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 3
8.3%
등록세 3
8.3%
주민세 3
8.3%
재산세 3
8.3%
자동차세 3
8.3%
담배소비세 3
8.3%
등록면허세 3
8.3%
지역자원시설세 3
8.3%
지방소득세 3
8.3%
교육세 3
8.3%
Other values (3) 6
16.7%

과세건수
Text

Distinct28
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T09:02:45.009759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.5277778
Min length3

Characters and Unicode

Total characters235
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)75.0%

Sample

1st row 12,424
2nd row -
3rd row 24,328
4th row 79,325
5th row 44,072
ValueCountFrequency (%)
9
25.0%
12,424 1
 
2.8%
16,791 1
 
2.8%
11,451 1
 
2.8%
30,240 1
 
2.8%
81 1
 
2.8%
45,345 1
 
2.8%
81,872 1
 
2.8%
25,278 1
 
2.8%
11,333 1
 
2.8%
Other values (18) 18
50.0%
2023-12-12T09:02:45.280840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
30.6%
1 27
 
11.5%
, 24
 
10.2%
4 16
 
6.8%
2 14
 
6.0%
3 14
 
6.0%
7 12
 
5.1%
8 11
 
4.7%
5 11
 
4.7%
0 10
 
4.3%
Other values (3) 24
 
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 130
55.3%
Space Separator 72
30.6%
Other Punctuation 24
 
10.2%
Dash Punctuation 9
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 27
20.8%
4 16
12.3%
2 14
10.8%
3 14
10.8%
7 12
9.2%
8 11
8.5%
5 11
8.5%
0 10
 
7.7%
9 9
 
6.9%
6 6
 
4.6%
Space Separator
ValueCountFrequency (%)
72
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 235
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
72
30.6%
1 27
 
11.5%
, 24
 
10.2%
4 16
 
6.8%
2 14
 
6.0%
3 14
 
6.0%
7 12
 
5.1%
8 11
 
4.7%
5 11
 
4.7%
0 10
 
4.3%
Other values (3) 24
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72
30.6%
1 27
 
11.5%
, 24
 
10.2%
4 16
 
6.8%
2 14
 
6.0%
3 14
 
6.0%
7 12
 
5.1%
8 11
 
4.7%
5 11
 
4.7%
0 10
 
4.3%
Other values (3) 24
 
10.2%

과세금액
Text

Distinct28
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T09:02:45.440628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length12.138889
Min length3

Characters and Unicode

Total characters437
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)75.0%

Sample

1st row 20,661,220,000
2nd row -
3rd row 1,353,050,000
4th row 5,251,538,000
5th row 13,009,487,000
ValueCountFrequency (%)
9
25.0%
20,661,220,000 1
 
2.8%
8,936,875,000 1
 
2.8%
1,502,831,000 1
 
2.8%
2,308,402,000 1
 
2.8%
3,917,122,000 1
 
2.8%
9,887,700,000 1
 
2.8%
6,491,927,000 1
 
2.8%
1,532,837,000 1
 
2.8%
16,582,483,000 1
 
2.8%
Other values (18) 18
50.0%
2023-12-12T09:02:46.006074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 100
22.9%
, 81
18.5%
72
16.5%
1 27
 
6.2%
8 25
 
5.7%
3 22
 
5.0%
2 21
 
4.8%
5 19
 
4.3%
4 17
 
3.9%
6 15
 
3.4%
Other values (3) 38
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 275
62.9%
Other Punctuation 81
 
18.5%
Space Separator 72
 
16.5%
Dash Punctuation 9
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 100
36.4%
1 27
 
9.8%
8 25
 
9.1%
3 22
 
8.0%
2 21
 
7.6%
5 19
 
6.9%
4 17
 
6.2%
6 15
 
5.5%
7 15
 
5.5%
9 14
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 81
100.0%
Space Separator
ValueCountFrequency (%)
72
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 437
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 100
22.9%
, 81
18.5%
72
16.5%
1 27
 
6.2%
8 25
 
5.7%
3 22
 
5.0%
2 21
 
4.8%
5 19
 
4.3%
4 17
 
3.9%
6 15
 
3.4%
Other values (3) 38
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 437
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 100
22.9%
, 81
18.5%
72
16.5%
1 27
 
6.2%
8 25
 
5.7%
3 22
 
5.0%
2 21
 
4.8%
5 19
 
4.3%
4 17
 
3.9%
6 15
 
3.4%
Other values (3) 38
 
8.7%

비과세건수
Text

Distinct26
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T09:02:46.164250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.6388889
Min length3

Characters and Unicode

Total characters203
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)66.7%

Sample

1st row 2,319
2nd row 10
3rd row 1,523
4th row 17,353
5th row 6,082
ValueCountFrequency (%)
10
27.8%
156 2
 
5.6%
2,319 1
 
2.8%
6,227 1
 
2.8%
1,139 1
 
2.8%
5,023 1
 
2.8%
6,280 1
 
2.8%
31,052 1
 
2.8%
1,859 1
 
2.8%
3 1
 
2.8%
Other values (16) 16
44.4%
2023-12-12T09:02:46.410576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
35.5%
1 24
 
11.8%
, 21
 
10.3%
2 15
 
7.4%
3 14
 
6.9%
- 10
 
4.9%
5 10
 
4.9%
0 9
 
4.4%
6 7
 
3.4%
9 7
 
3.4%
Other values (3) 14
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100
49.3%
Space Separator 72
35.5%
Other Punctuation 21
 
10.3%
Dash Punctuation 10
 
4.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
24.0%
2 15
15.0%
3 14
14.0%
5 10
10.0%
0 9
 
9.0%
6 7
 
7.0%
9 7
 
7.0%
7 6
 
6.0%
8 5
 
5.0%
4 3
 
3.0%
Space Separator
ValueCountFrequency (%)
72
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 203
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
72
35.5%
1 24
 
11.8%
, 21
 
10.3%
2 15
 
7.4%
3 14
 
6.9%
- 10
 
4.9%
5 10
 
4.9%
0 9
 
4.4%
6 7
 
3.4%
9 7
 
3.4%
Other values (3) 14
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 203
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72
35.5%
1 24
 
11.8%
, 21
 
10.3%
2 15
 
7.4%
3 14
 
6.9%
- 10
 
4.9%
5 10
 
4.9%
0 9
 
4.4%
6 7
 
3.4%
9 7
 
3.4%
Other values (3) 14
 
6.9%

비과세금액
Text

Distinct27
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T09:02:46.567890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length10
Min length3

Characters and Unicode

Total characters360
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)72.2%

Sample

1st row 5,572,080,000
2nd row 945,000
3rd row 27,508,000
4th row 3,594,153,000
5th row 329,674,000
ValueCountFrequency (%)
10
27.8%
5,572,080,000 1
 
2.8%
321,070,000 1
 
2.8%
99,569,000 1
 
2.8%
132,774,000 1
 
2.8%
317,812,000 1
 
2.8%
3,725,992,000 1
 
2.8%
30,458,000 1
 
2.8%
460,000 1
 
2.8%
4,103,414,000 1
 
2.8%
Other values (17) 17
47.2%
2023-12-12T09:02:46.855367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 91
25.3%
72
20.0%
, 57
15.8%
7 19
 
5.3%
4 19
 
5.3%
3 17
 
4.7%
1 16
 
4.4%
9 14
 
3.9%
5 14
 
3.9%
2 13
 
3.6%
Other values (3) 28
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 221
61.4%
Space Separator 72
 
20.0%
Other Punctuation 57
 
15.8%
Dash Punctuation 10
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 91
41.2%
7 19
 
8.6%
4 19
 
8.6%
3 17
 
7.7%
1 16
 
7.2%
9 14
 
6.3%
5 14
 
6.3%
2 13
 
5.9%
8 10
 
4.5%
6 8
 
3.6%
Space Separator
ValueCountFrequency (%)
72
100.0%
Other Punctuation
ValueCountFrequency (%)
, 57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 91
25.3%
72
20.0%
, 57
15.8%
7 19
 
5.3%
4 19
 
5.3%
3 17
 
4.7%
1 16
 
4.4%
9 14
 
3.9%
5 14
 
3.9%
2 13
 
3.6%
Other values (3) 28
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 91
25.3%
72
20.0%
, 57
15.8%
7 19
 
5.3%
4 19
 
5.3%
3 17
 
4.7%
1 16
 
4.4%
9 14
 
3.9%
5 14
 
3.9%
2 13
 
3.6%
Other values (3) 28
 
7.8%

Correlations

2023-12-12T09:02:46.947351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명과세건수과세금액비과세건수비과세금액
과세년도1.0000.0000.5910.5910.5050.662
세목명0.0001.0000.0000.0000.7050.000
과세건수0.5910.0001.0001.0000.9780.981
과세금액0.5910.0001.0001.0000.9780.981
비과세건수0.5050.7050.9780.9781.0001.000
비과세금액0.6620.0000.9810.9811.0001.000
2023-12-12T09:02:47.052798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도
세목명1.0000.000
과세년도0.0001.000
2023-12-12T09:02:47.133607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000

Missing values

2023-12-12T09:02:43.523597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:02:43.673444image/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

시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
0경상북도성주군478402017취득세12,42420,661,220,0002,3195,572,080,000
1경상북도성주군478402017등록세--10945,000
2경상북도성주군478402017주민세24,3281,353,050,0001,52327,508,000
3경상북도성주군478402017재산세79,3255,251,538,00017,3533,594,153,000
4경상북도성주군478402017자동차세44,07213,009,487,0006,082329,674,000
5경상북도성주군478402017레저세----
6경상북도성주군478402017담배소비세1114,428,078,000--
7경상북도성주군478402017지방소비세----
8경상북도성주군478402017등록면허세26,1852,186,724,0004,6721,199,306,000
9경상북도성주군478402017도시계획세----
시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
26경상북도성주군478402019재산세81,8726,491,927,00031,0523,725,992,000
27경상북도성주군478402019자동차세45,3459,887,700,0006,280317,812,000
28경상북도성주군478402019레저세----
29경상북도성주군478402019담배소비세813,917,122,000--
30경상북도성주군478402019지방소비세----
31경상북도성주군478402019등록면허세30,2402,308,402,0005,023132,774,000
32경상북도성주군478402019도시계획세----
33경상북도성주군478402019지역자원시설세11,4511,502,831,0001,13999,569,000
34경상북도성주군478402019지방소득세16,7918,936,875,000--
35경상북도성주군478402019교육세139,6875,516,865,00011,5314,815,000