Overview

Dataset statistics

Number of variables11
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory93.2 B

Variable types

Categorical6
Text5

Dataset

Description지방세 부과액에 대한 세목별 징수현황을 제공하며 지자체의 재정자주도와 재정자립도를 산출하는 기초 및 납세 협력도 및 조세순응도를 확인하는 자료로 활용
Author경상북도 성주군
URLhttps://www.data.go.kr/data/15078604/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
세목명 is highly overall correlated with 징수율High correlation
징수율 is highly overall correlated with 세목명High correlation

Reproduction

Analysis started2023-12-12 05:24:59.383582
Analysis finished2023-12-12 05:25:00.074842
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
경상북도
41 

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 41
100.0%

Length

2023-12-12T14:25:00.175471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:25:00.292651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 41
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
성주군
41 

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 41
100.0%

Length

2023-12-12T14:25:00.398838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:25:00.494607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성주군 41
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
47840
41 

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 41
100.0%

Length

2023-12-12T14:25:00.596311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:25:00.709277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47840 41
100.0%

과세년도
Categorical

Distinct3
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
2017
14 
2018
14 
2019
13 

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 14
34.1%
2018 14
34.1%
2019 13
31.7%

Length

2023-12-12T14:25:00.827865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:25:00.924287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 14
34.1%
2018 14
34.1%
2019 13
31.7%

세목명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size460.0 B
레저세
3 
재산세
3 
주민세
3 
취득세
3 
자동차세
3 
Other values (9)
26 

Length

Max length7
Median length5
Mean length4.3902439
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row도축세
2nd row레저세
3rd row재산세
4th row주민세
5th row취득세

Common Values

ValueCountFrequency (%)
레저세 3
 
7.3%
재산세 3
 
7.3%
주민세 3
 
7.3%
취득세 3
 
7.3%
자동차세 3
 
7.3%
과년도수입 3
 
7.3%
담배소비세 3
 
7.3%
도시계획세 3
 
7.3%
등록면허세 3
 
7.3%
지방교육세 3
 
7.3%
Other values (4) 11
26.8%

Length

2023-12-12T14:25:01.046550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
레저세 3
 
7.3%
재산세 3
 
7.3%
주민세 3
 
7.3%
취득세 3
 
7.3%
자동차세 3
 
7.3%
과년도수입 3
 
7.3%
담배소비세 3
 
7.3%
도시계획세 3
 
7.3%
등록면허세 3
 
7.3%
지방교육세 3
 
7.3%
Other values (4) 11
26.8%

부과금액
Text

Distinct31
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T14:25:01.219596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length11.902439
Min length3

Characters and Unicode

Total characters488
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

Unique30 ?
Unique (%)73.2%

Sample

1st row -
2nd row -
3rd row 5,251,538,000
4th row 1,353,050,000
5th row 20,661,220,000
ValueCountFrequency (%)
11
26.8%
3,891,118,000 1
 
2.4%
8,936,875,000 1
 
2.4%
5,516,865,000 1
 
2.4%
2,308,402,000 1
 
2.4%
3,917,122,000 1
 
2.4%
2,218,009,000 1
 
2.4%
9,887,700,000 1
 
2.4%
16,582,483,000 1
 
2.4%
1,532,837,000 1
 
2.4%
Other values (21) 21
51.2%
2023-12-12T14:25:01.546630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 111
22.7%
, 90
18.4%
82
16.8%
1 29
 
5.9%
8 27
 
5.5%
2 26
 
5.3%
3 23
 
4.7%
5 20
 
4.1%
4 19
 
3.9%
7 18
 
3.7%
Other values (3) 43
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 305
62.5%
Other Punctuation 90
 
18.4%
Space Separator 82
 
16.8%
Dash Punctuation 11
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 111
36.4%
1 29
 
9.5%
8 27
 
8.9%
2 26
 
8.5%
3 23
 
7.5%
5 20
 
6.6%
4 19
 
6.2%
7 18
 
5.9%
9 17
 
5.6%
6 15
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 90
100.0%
Space Separator
ValueCountFrequency (%)
82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 488
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 111
22.7%
, 90
18.4%
82
16.8%
1 29
 
5.9%
8 27
 
5.5%
2 26
 
5.3%
3 23
 
4.7%
5 20
 
4.1%
4 19
 
3.9%
7 18
 
3.7%
Other values (3) 43
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 488
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 111
22.7%
, 90
18.4%
82
16.8%
1 29
 
5.9%
8 27
 
5.5%
2 26
 
5.3%
3 23
 
4.7%
5 20
 
4.1%
4 19
 
3.9%
7 18
 
3.7%
Other values (3) 43
 
8.8%

수납급액
Text

Distinct31
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T14:25:01.709479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length11.731707
Min length3

Characters and Unicode

Total characters481
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

Unique30 ?
Unique (%)73.2%

Sample

1st row -
2nd row -
3rd row 5,115,698,000
4th row 1,323,272,000
5th row 20,302,259,000
ValueCountFrequency (%)
11
26.8%
3,891,118,000 1
 
2.4%
8,712,711,000 1
 
2.4%
5,354,322,000 1
 
2.4%
2,306,358,000 1
 
2.4%
3,917,122,000 1
 
2.4%
744,340,000 1
 
2.4%
9,478,550,000 1
 
2.4%
16,310,010,000 1
 
2.4%
1,497,413,000 1
 
2.4%
Other values (21) 21
51.2%
2023-12-12T14:25:02.008757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 109
22.7%
, 87
18.1%
82
17.0%
1 31
 
6.4%
7 26
 
5.4%
3 25
 
5.2%
5 23
 
4.8%
2 22
 
4.6%
4 22
 
4.6%
8 19
 
4.0%
Other values (3) 35
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 301
62.6%
Other Punctuation 87
 
18.1%
Space Separator 82
 
17.0%
Dash Punctuation 11
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 109
36.2%
1 31
 
10.3%
7 26
 
8.6%
3 25
 
8.3%
5 23
 
7.6%
2 22
 
7.3%
4 22
 
7.3%
8 19
 
6.3%
9 16
 
5.3%
6 8
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 87
100.0%
Space Separator
ValueCountFrequency (%)
82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 481
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 109
22.7%
, 87
18.1%
82
17.0%
1 31
 
6.4%
7 26
 
5.4%
3 25
 
5.2%
5 23
 
4.8%
2 22
 
4.6%
4 22
 
4.6%
8 19
 
4.0%
Other values (3) 35
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 481
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 109
22.7%
, 87
18.1%
82
17.0%
1 31
 
6.4%
7 26
 
5.4%
3 25
 
5.2%
5 23
 
4.8%
2 22
 
4.6%
4 22
 
4.6%
8 19
 
4.0%
Other values (3) 35
 
7.3%

환급금액
Text

Distinct28
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T14:25:02.169875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length8.6585366
Min length3

Characters and Unicode

Total characters355
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 (%)65.9%

Sample

1st row -
2nd row -
3rd row 1,265,000
4th row 2,564,000
5th row 73,824,000
ValueCountFrequency (%)
14
34.1%
1,265,000 1
 
2.4%
100,612,000 1
 
2.4%
29,994,000 1
 
2.4%
8,335,000 1
 
2.4%
216,348,000 1
 
2.4%
48,943,000 1
 
2.4%
180,035,000 1
 
2.4%
3,399,000 1
 
2.4%
1,978,000 1
 
2.4%
Other values (18) 18
43.9%
2023-12-12T14:25:02.429180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 87
24.5%
82
23.1%
, 51
14.4%
1 18
 
5.1%
9 17
 
4.8%
4 15
 
4.2%
- 14
 
3.9%
3 14
 
3.9%
2 13
 
3.7%
6 13
 
3.7%
Other values (3) 31
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 208
58.6%
Space Separator 82
 
23.1%
Other Punctuation 51
 
14.4%
Dash Punctuation 14
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 87
41.8%
1 18
 
8.7%
9 17
 
8.2%
4 15
 
7.2%
3 14
 
6.7%
2 13
 
6.2%
6 13
 
6.2%
5 12
 
5.8%
8 11
 
5.3%
7 8
 
3.8%
Space Separator
ValueCountFrequency (%)
82
100.0%
Other Punctuation
ValueCountFrequency (%)
, 51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 355
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 87
24.5%
82
23.1%
, 51
14.4%
1 18
 
5.1%
9 17
 
4.8%
4 15
 
4.2%
- 14
 
3.9%
3 14
 
3.9%
2 13
 
3.7%
6 13
 
3.7%
Other values (3) 31
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 355
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 87
24.5%
82
23.1%
, 51
14.4%
1 18
 
5.1%
9 17
 
4.8%
4 15
 
4.2%
- 14
 
3.9%
3 14
 
3.9%
2 13
 
3.7%
6 13
 
3.7%
Other values (3) 31
 
8.7%

결손금액
Text

Distinct26
Distinct (%)63.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T14:25:02.572512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.6829268
Min length3

Characters and Unicode

Total characters315
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

Unique25 ?
Unique (%)61.0%

Sample

1st row -
2nd row -
3rd row 5,578,000
4th row 618,000
5th row 28,586,000
ValueCountFrequency (%)
16
39.0%
5,578,000 1
 
2.4%
59,704,000 1
 
2.4%
2,044,000 1
 
2.4%
19,000 1
 
2.4%
519,917,000 1
 
2.4%
1,306,000 1
 
2.4%
628,000 1
 
2.4%
8,288,000 1
 
2.4%
847,000 1
 
2.4%
Other values (16) 16
39.0%
2023-12-12T14:25:02.939909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 83
26.3%
82
26.0%
, 42
13.3%
- 16
 
5.1%
1 13
 
4.1%
4 13
 
4.1%
9 12
 
3.8%
8 11
 
3.5%
7 10
 
3.2%
5 9
 
2.9%
Other values (3) 24
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 175
55.6%
Space Separator 82
26.0%
Other Punctuation 42
 
13.3%
Dash Punctuation 16
 
5.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 83
47.4%
1 13
 
7.4%
4 13
 
7.4%
9 12
 
6.9%
8 11
 
6.3%
7 10
 
5.7%
5 9
 
5.1%
6 9
 
5.1%
3 8
 
4.6%
2 7
 
4.0%
Space Separator
ValueCountFrequency (%)
82
100.0%
Other Punctuation
ValueCountFrequency (%)
, 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 315
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 83
26.3%
82
26.0%
, 42
13.3%
- 16
 
5.1%
1 13
 
4.1%
4 13
 
4.1%
9 12
 
3.8%
8 11
 
3.5%
7 10
 
3.2%
5 9
 
2.9%
Other values (3) 24
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 315
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 83
26.3%
82
26.0%
, 42
13.3%
- 16
 
5.1%
1 13
 
4.1%
4 13
 
4.1%
9 12
 
3.8%
8 11
 
3.5%
7 10
 
3.2%
5 9
 
2.9%
Other values (3) 24
 
7.6%

미수납 금액
Text

Distinct28
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T14:25:03.215644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.2926829
Min length3

Characters and Unicode

Total characters381
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 (%)65.9%

Sample

1st row -
2nd row -
3rd row 130,262,000
4th row 29,160,000
5th row 330,375,000
ValueCountFrequency (%)
14
34.1%
130,262,000 1
 
2.4%
164,460,000 1
 
2.4%
160,499,000 1
 
2.4%
2,025,000 1
 
2.4%
953,752,000 1
 
2.4%
407,844,000 1
 
2.4%
272,473,000 1
 
2.4%
34,796,000 1
 
2.4%
172,751,000 1
 
2.4%
Other values (18) 18
43.9%
2023-12-12T14:25:03.603710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 91
23.9%
82
21.5%
, 54
14.2%
1 19
 
5.0%
7 19
 
5.0%
4 19
 
5.0%
3 17
 
4.5%
2 16
 
4.2%
6 16
 
4.2%
8 16
 
4.2%
Other values (3) 32
 
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 231
60.6%
Space Separator 82
 
21.5%
Other Punctuation 54
 
14.2%
Dash Punctuation 14
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 91
39.4%
1 19
 
8.2%
7 19
 
8.2%
4 19
 
8.2%
3 17
 
7.4%
2 16
 
6.9%
6 16
 
6.9%
8 16
 
6.9%
5 11
 
4.8%
9 7
 
3.0%
Space Separator
ValueCountFrequency (%)
82
100.0%
Other Punctuation
ValueCountFrequency (%)
, 54
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 381
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 91
23.9%
82
21.5%
, 54
14.2%
1 19
 
5.0%
7 19
 
5.0%
4 19
 
5.0%
3 17
 
4.5%
2 16
 
4.2%
6 16
 
4.2%
8 16
 
4.2%
Other values (3) 32
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 381
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 91
23.9%
82
21.5%
, 54
14.2%
1 19
 
5.0%
7 19
 
5.0%
4 19
 
5.0%
3 17
 
4.5%
2 16
 
4.2%
6 16
 
4.2%
8 16
 
4.2%
Other values (3) 32
 
8.4%

징수율
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
-
11 
97
10 
100
6 
98
5 
96
2 
Other values (5)
7 

Length

Max length5
Median length4
Mean length3.8780488
Min length3

Unique

Unique3 ?
Unique (%)7.3%

Sample

1st row -
2nd row -
3rd row 97
4th row 98
5th row 98

Common Values

ValueCountFrequency (%)
- 11
26.8%
97 10
24.4%
100 6
14.6%
98 5
12.2%
96 2
 
4.9%
95 2
 
4.9%
34 2
 
4.9%
40 1
 
2.4%
94 1
 
2.4%
99 1
 
2.4%

Length

2023-12-12T14:25:03.788700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:25:03.938272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11
26.8%
97 10
24.4%
100 6
14.6%
98 5
12.2%
96 2
 
4.9%
95 2
 
4.9%
34 2
 
4.9%
40 1
 
2.4%
94 1
 
2.4%
99 1
 
2.4%

Correlations

2023-12-12T14:25:04.087701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
과세년도1.0000.0000.1930.1930.1510.1160.1510.000
세목명0.0001.0000.7900.7900.7730.6600.7730.872
부과금액0.1930.7901.0001.0001.0001.0001.0001.000
수납급액0.1930.7901.0001.0001.0001.0001.0001.000
환급금액0.1510.7731.0001.0001.0001.0001.0000.984
결손금액0.1160.6601.0001.0001.0001.0001.0000.931
미수납 금액0.1510.7731.0001.0001.0001.0001.0000.984
징수율0.0000.8721.0001.0000.9840.9310.9841.000
2023-12-12T14:25:04.217837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도징수율
세목명1.0000.0000.554
과세년도0.0001.0000.000
징수율0.5540.0001.000
2023-12-12T14:25:04.338153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명징수율
과세년도1.0000.0000.000
세목명0.0001.0000.554
징수율0.0000.5541.000

Missing values

2023-12-12T14:24:59.785128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:24:59.989528image/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

시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
0경상북도성주군478402017도축세------
1경상북도성주군478402017레저세------
2경상북도성주군478402017재산세5,251,538,0005,115,698,0001,265,0005,578,000130,262,00097
3경상북도성주군478402017주민세1,353,050,0001,323,272,0002,564,000618,00029,160,00098
4경상북도성주군478402017취득세20,661,220,00020,302,259,00073,824,00028,586,000330,375,00098
5경상북도성주군478402017자동차세13,009,487,00012,540,173,00046,345,0001,189,000468,125,00096
6경상북도성주군478402017과년도수입1,982,477,000801,555,000199,849,000399,456,000781,466,00040
7경상북도성주군478402017담배소비세4,428,078,0004,428,078,000---100
8경상북도성주군478402017도시계획세------
9경상북도성주군478402017등록면허세2,186,724,0002,184,712,0005,246,000144,0001,868,000100
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
31경상북도성주군478402019취득세16,582,483,00016,310,010,000180,035,000-272,473,00098
32경상북도성주군478402019자동차세9,887,700,0009,478,550,00048,943,0001,306,000407,844,00096
33경상북도성주군478402019과년도수입2,218,009,000744,340,000216,348,000519,917,000953,752,00034
34경상북도성주군478402019담배소비세3,917,122,0003,917,122,000---100
35경상북도성주군478402019도시계획세------
36경상북도성주군478402019등록면허세2,308,402,0002,306,358,0008,335,00019,0002,025,000100
37경상북도성주군478402019지방교육세5,516,865,0005,354,322,00029,994,0002,044,000160,499,00097
38경상북도성주군478402019지방소득세8,936,875,0008,712,711,000100,612,00059,704,000164,460,00097
39경상북도성주군478402019지방소비세------
40경상북도성주군478402019지역자원시설세1,502,831,0001,456,409,000191,0002,591,00043,831,00097