Overview

Dataset statistics

Number of variables12
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory100.4 B

Variable types

Categorical6
Text5
DateTime1

Dataset

Description이 데이터는 2017~2020년 남원시 지방세 징수현황에 대하여 세목명, 부과금액, 수납금액, 환급금액, 결손금액, 미수납금액, 징수율에 대한 데이터입니다.
URLhttps://www.data.go.kr/data/15079834/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 17:58:07.774533
Analysis finished2023-12-12 17:58:08.877448
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
전라북도
54 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 54
100.0%

Length

2023-12-13T02:58:08.988453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:58:09.094017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 54
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
남원시
54 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남원시 54
100.0%

Length

2023-12-13T02:58:09.184441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:58:09.320592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남원시 54
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
45190
54 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row45190
2nd row45190
3rd row45190
4th row45190
5th row45190

Common Values

ValueCountFrequency (%)
45190 54
100.0%

Length

2023-12-13T02:58:09.458680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:58:09.581969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
45190 54
100.0%

과세년도
Categorical

Distinct4
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size564.0 B
2017
14 
2018
14 
2019
13 
2020
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
25.9%
2018 14
25.9%
2019 13
24.1%
2020 13
24.1%

Length

2023-12-13T02:58:09.699579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:58:09.825176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 14
25.9%
2018 14
25.9%
2019 13
24.1%
2020 13
24.1%

세목명
Categorical

Distinct14
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
레저세
4 
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
Other values (9)
34 

Length

Max length7
Median length5
Mean length4.4074074
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
레저세 4
 
7.4%
재산세 4
 
7.4%
주민세 4
 
7.4%
취득세 4
 
7.4%
자동차세 4
 
7.4%
과년도수입 4
 
7.4%
담배소비세 4
 
7.4%
도시계획세 4
 
7.4%
등록면허세 4
 
7.4%
지방교육세 4
 
7.4%
Other values (4) 14
25.9%

Length

2023-12-13T02:58:09.981271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
레저세 4
 
7.4%
재산세 4
 
7.4%
주민세 4
 
7.4%
취득세 4
 
7.4%
자동차세 4
 
7.4%
과년도수입 4
 
7.4%
담배소비세 4
 
7.4%
도시계획세 4
 
7.4%
등록면허세 4
 
7.4%
지방교육세 4
 
7.4%
Other values (4) 14
25.9%

부과금액
Text

Distinct42
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-13T02:58:10.224507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8
Min length1

Characters and Unicode

Total characters432
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

Unique41 ?
Unique (%)75.9%

Sample

1st row
2nd row
3rd row6763945000
4th row1179715000
5th row16397136000
ValueCountFrequency (%)
8938254000 1
 
2.4%
1300671000 1
 
2.4%
18945822000 1
 
2.4%
12048451000 1
 
2.4%
2432264000 1
 
2.4%
5252773000 1
 
2.4%
1984050000 1
 
2.4%
6535039000 1
 
2.4%
10345683000 1
 
2.4%
1132029000 1
 
2.4%
Other values (31) 31
75.6%
2023-12-13T02:58:10.673742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 149
34.5%
1 44
 
10.2%
7 34
 
7.9%
2 32
 
7.4%
4 30
 
6.9%
3 29
 
6.7%
5 29
 
6.7%
6 25
 
5.8%
8 24
 
5.6%
9 23
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 419
97.0%
Space Separator 13
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 149
35.6%
1 44
 
10.5%
7 34
 
8.1%
2 32
 
7.6%
4 30
 
7.2%
3 29
 
6.9%
5 29
 
6.9%
6 25
 
6.0%
8 24
 
5.7%
9 23
 
5.5%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 432
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 149
34.5%
1 44
 
10.2%
7 34
 
7.9%
2 32
 
7.4%
4 30
 
6.9%
3 29
 
6.7%
5 29
 
6.7%
6 25
 
5.8%
8 24
 
5.6%
9 23
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 149
34.5%
1 44
 
10.2%
7 34
 
7.9%
2 32
 
7.4%
4 30
 
6.9%
3 29
 
6.7%
5 29
 
6.7%
6 25
 
5.8%
8 24
 
5.6%
9 23
 
5.3%

수납급액
Text

Distinct42
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-13T02:58:10.930434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10.5
Mean length7.9444444
Min length1

Characters and Unicode

Total characters429
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

Unique41 ?
Unique (%)75.9%

Sample

1st row
2nd row
3rd row6534530000
4th row1130695000
5th row16370105000
ValueCountFrequency (%)
8707042000 1
 
2.4%
1247193000 1
 
2.4%
18907805000 1
 
2.4%
11399741000 1
 
2.4%
955299000 1
 
2.4%
5252773000 1
 
2.4%
1976136000 1
 
2.4%
6290590000 1
 
2.4%
10039006000 1
 
2.4%
1051301000 1
 
2.4%
Other values (31) 31
75.6%
2023-12-13T02:58:11.318335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 152
35.4%
1 40
 
9.3%
3 32
 
7.5%
9 31
 
7.2%
7 30
 
7.0%
5 30
 
7.0%
2 28
 
6.5%
8 26
 
6.1%
6 24
 
5.6%
4 23
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 416
97.0%
Space Separator 13
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 152
36.5%
1 40
 
9.6%
3 32
 
7.7%
9 31
 
7.5%
7 30
 
7.2%
5 30
 
7.2%
2 28
 
6.7%
8 26
 
6.2%
6 24
 
5.8%
4 23
 
5.5%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 429
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 152
35.4%
1 40
 
9.3%
3 32
 
7.5%
9 31
 
7.2%
7 30
 
7.0%
5 30
 
7.0%
2 28
 
6.5%
8 26
 
6.1%
6 24
 
5.6%
4 23
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 429
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 152
35.4%
1 40
 
9.3%
3 32
 
7.5%
9 31
 
7.2%
7 30
 
7.0%
5 30
 
7.0%
2 28
 
6.5%
8 26
 
6.1%
6 24
 
5.6%
4 23
 
5.4%

환급금액
Text

Distinct38
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-13T02:58:11.567403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.5555556
Min length1

Characters and Unicode

Total characters300
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

Unique37 ?
Unique (%)68.5%

Sample

1st row
2nd row
3rd row1210000
4th row948000
5th row47892000
ValueCountFrequency (%)
123505000 1
 
2.7%
211000 1
 
2.7%
115751000 1
 
2.7%
88324000 1
 
2.7%
279246000 1
 
2.7%
7519000 1
 
2.7%
31933000 1
 
2.7%
157605000 1
 
2.7%
421000 1
 
2.7%
565000 1
 
2.7%
Other values (27) 27
73.0%
2023-12-13T02:58:11.982012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 120
40.0%
5 26
 
8.7%
1 25
 
8.3%
2 22
 
7.3%
8 21
 
7.0%
3 18
 
6.0%
17
 
5.7%
7 15
 
5.0%
4 13
 
4.3%
9 12
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 283
94.3%
Space Separator 17
 
5.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 120
42.4%
5 26
 
9.2%
1 25
 
8.8%
2 22
 
7.8%
8 21
 
7.4%
3 18
 
6.4%
7 15
 
5.3%
4 13
 
4.6%
9 12
 
4.2%
6 11
 
3.9%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 120
40.0%
5 26
 
8.7%
1 25
 
8.3%
2 22
 
7.3%
8 21
 
7.0%
3 18
 
6.0%
17
 
5.7%
7 15
 
5.0%
4 13
 
4.3%
9 12
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 120
40.0%
5 26
 
8.7%
1 25
 
8.3%
2 22
 
7.3%
8 21
 
7.0%
3 18
 
6.0%
17
 
5.7%
7 15
 
5.0%
4 13
 
4.3%
9 12
 
4.0%

결손금액
Text

Distinct34
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-13T02:58:12.205881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.7777778
Min length1

Characters and Unicode

Total characters258
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

Unique33 ?
Unique (%)61.1%

Sample

1st row
2nd row
3rd row37153000
4th row381000
5th row
ValueCountFrequency (%)
37299000 1
 
3.0%
165000 1
 
3.0%
444000 1
 
3.0%
596621000 1
 
3.0%
169000 1
 
3.0%
21851000 1
 
3.0%
12544000 1
 
3.0%
51819000 1
 
3.0%
52000 1
 
3.0%
37153000 1
 
3.0%
Other values (23) 23
69.7%
2023-12-13T02:58:12.591755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 100
38.8%
1 26
 
10.1%
2 22
 
8.5%
21
 
8.1%
4 19
 
7.4%
5 17
 
6.6%
3 16
 
6.2%
9 14
 
5.4%
6 11
 
4.3%
8 7
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 237
91.9%
Space Separator 21
 
8.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 100
42.2%
1 26
 
11.0%
2 22
 
9.3%
4 19
 
8.0%
5 17
 
7.2%
3 16
 
6.8%
9 14
 
5.9%
6 11
 
4.6%
8 7
 
3.0%
7 5
 
2.1%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 258
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 100
38.8%
1 26
 
10.1%
2 22
 
8.5%
21
 
8.1%
4 19
 
7.4%
5 17
 
6.6%
3 16
 
6.2%
9 14
 
5.4%
6 11
 
4.3%
8 7
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 258
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 100
38.8%
1 26
 
10.1%
2 22
 
8.5%
21
 
8.1%
4 19
 
7.4%
5 17
 
6.6%
3 16
 
6.2%
9 14
 
5.4%
6 11
 
4.3%
8 7
 
2.7%

미수납 금액
Text

Distinct37
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-13T02:58:12.819485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6
Min length1

Characters and Unicode

Total characters324
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

Unique36 ?
Unique (%)66.7%

Sample

1st row
2nd row
3rd row192262000
4th row48639000
5th row27031000
ValueCountFrequency (%)
192262000 1
 
2.8%
48639000 1
 
2.8%
38017000 1
 
2.8%
648266000 1
 
2.8%
880344000 1
 
2.8%
7745000 1
 
2.8%
222598000 1
 
2.8%
294133000 1
 
2.8%
28909000 1
 
2.8%
415628000 1
 
2.8%
Other values (26) 26
72.2%
2023-12-13T02:58:13.275355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 125
38.6%
2 29
 
9.0%
3 22
 
6.8%
4 20
 
6.2%
8 20
 
6.2%
5 20
 
6.2%
6 19
 
5.9%
18
 
5.6%
1 18
 
5.6%
7 17
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 306
94.4%
Space Separator 18
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 125
40.8%
2 29
 
9.5%
3 22
 
7.2%
4 20
 
6.5%
8 20
 
6.5%
5 20
 
6.5%
6 19
 
6.2%
1 18
 
5.9%
7 17
 
5.6%
9 16
 
5.2%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 324
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 125
38.6%
2 29
 
9.0%
3 22
 
6.8%
4 20
 
6.2%
8 20
 
6.2%
5 20
 
6.2%
6 19
 
5.9%
18
 
5.6%
1 18
 
5.6%
7 17
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 324
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 125
38.6%
2 29
 
9.0%
3 22
 
6.8%
4 20
 
6.2%
8 20
 
6.2%
5 20
 
6.2%
6 19
 
5.9%
18
 
5.6%
1 18
 
5.6%
7 17
 
5.2%

징수율
Categorical

Distinct15
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Memory size564.0 B
11 
100
11 
96
8 
97
6 
95
4 
Other values (10)
14 

Length

Max length3
Median length2
Mean length1.962963
Min length1

Unique

Unique7 ?
Unique (%)13.0%

Sample

1st row
2nd row
3rd row97
4th row96
5th row100

Common Values

ValueCountFrequency (%)
11
20.4%
100 11
20.4%
96 8
14.8%
97 6
11.1%
95 4
 
7.4%
94 3
 
5.6%
0 2
 
3.7%
99 2
 
3.7%
61 1
 
1.9%
98 1
 
1.9%
Other values (5) 5
9.3%

Length

2023-12-13T02:58:13.475220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
100 11
25.6%
96 8
18.6%
97 6
14.0%
95 4
 
9.3%
94 3
 
7.0%
0 2
 
4.7%
99 2
 
4.7%
61 1
 
2.3%
98 1
 
2.3%
44 1
 
2.3%
Other values (4) 4
 
9.3%

데이터 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
Minimum2020-12-31 00:00:00
Maximum2020-12-31 00:00:00
2023-12-13T02:58:13.619741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:58:13.740120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T02:58:13.837654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
과세년도1.0000.0000.3110.3110.2430.1980.1440.295
세목명0.0001.0000.7780.7780.6790.6130.6880.830
부과금액0.3110.7781.0001.0001.0001.0001.0000.985
수납급액0.3110.7781.0001.0001.0001.0001.0000.985
환급금액0.2430.6791.0001.0001.0001.0001.0000.980
결손금액0.1980.6131.0001.0001.0001.0001.0000.958
미수납 금액0.1440.6881.0001.0001.0001.0001.0000.979
징수율0.2950.8300.9850.9850.9800.9580.9791.000
2023-12-13T02:58:13.975389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명징수율과세년도
세목명1.0000.4580.000
징수율0.4581.0000.134
과세년도0.0000.1341.000
2023-12-13T02:58:14.071868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명징수율
과세년도1.0000.0000.134
세목명0.0001.0000.458
징수율0.1340.4581.000

Missing values

2023-12-13T02:58:08.623778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:58:08.800498image/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 금액징수율데이터 기준일자
0전라북도남원시451902017도축세2020-12-31
1전라북도남원시451902017레저세2020-12-31
2전라북도남원시451902017재산세67639450006534530000121000037153000192262000972020-12-31
3전라북도남원시451902017주민세1179715000113069500094800038100048639000962020-12-31
4전라북도남원시451902017취득세163971360001637010500047892000270310001002020-12-31
5전라북도남원시451902017자동차세1125499600010637229000729520001793000615974000952020-12-31
6전라북도남원시451902017과년도수입20211840001241700000258288000121129000658355000612020-12-31
7전라북도남원시451902017담배소비세545436800054543680001002020-12-31
8전라북도남원시451902017도시계획세2020-12-31
9전라북도남원시451902017등록면허세147006700014655230001495000012400044200001002020-12-31
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율데이터 기준일자
44전라북도남원시451902020취득세20545799000203990350008133200011199000135565000992020-12-31
45전라북도남원시451902020자동차세120163740001146888400010275000064000547426000952020-12-31
46전라북도남원시451902020과년도수입23907160001133030000469315000266344000991342000472020-12-31
47전라북도남원시451902020담배소비세5516237000551623700058520001002020-12-31
48전라북도남원시451902020도시계획세02020-12-31
49전라북도남원시451902020등록면허세20972880002089385000158080004300078600001002020-12-31
50전라북도남원시451902020지방교육세68434130006597962000372660008372000237079000962020-12-31
51전라북도남원시451902020지방소득세947137500093434870002586850005517000122371000992020-12-31
52전라북도남원시451902020지방소비세11533700000115337000001002020-12-31
53전라북도남원시451902020지역자원시설세122881600011611470006140002213500045534000942020-12-31