Overview

Dataset statistics

Number of variables11
Number of observations272
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.4 KiB
Average record size in memory95.5 B

Variable types

Numeric5
Categorical6

Dataset

Description체납액 규모별 체납 건수를 납세자 유형별로 제공지방자치단체의 체납세 일제정리 정책 수립시 기초자료 활용과세연도별 발생된 체납건수 및 체납액
Author경상북도 경산시
URLhttps://www.data.go.kr/data/15079721/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
연번 is highly overall correlated with 과세년도High correlation
체납건수 is highly overall correlated with 체납금액 and 3 other fieldsHigh correlation
체납금액 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
누적체납건수 is highly overall correlated with 체납건수 and 3 other fieldsHigh correlation
누적체납금액 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
과세년도 is highly overall correlated with 연번High correlation
세목명 is highly overall correlated with 체납건수 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
체납건수 has 106 (39.0%) zerosZeros
체납금액 has 106 (39.0%) zerosZeros

Reproduction

Analysis started2024-03-16 04:12:14.033389
Analysis finished2024-03-16 04:12:19.270785
Duration5.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct272
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136.5
Minimum1
Maximum272
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-16T13:12:19.396749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.55
Q168.75
median136.5
Q3204.25
95-th percentile258.45
Maximum272
Range271
Interquartile range (IQR)135.5

Descriptive statistics

Standard deviation78.663842
Coefficient of variation (CV)0.57629188
Kurtosis-1.2
Mean136.5
Median Absolute Deviation (MAD)68
Skewness0
Sum37128
Variance6188
MonotonicityStrictly increasing
2024-03-16T13:12:19.633869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
181 1
 
0.4%
187 1
 
0.4%
186 1
 
0.4%
185 1
 
0.4%
184 1
 
0.4%
183 1
 
0.4%
182 1
 
0.4%
180 1
 
0.4%
138 1
 
0.4%
Other values (262) 262
96.3%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
272 1
0.4%
271 1
0.4%
270 1
0.4%
269 1
0.4%
268 1
0.4%
267 1
0.4%
266 1
0.4%
265 1
0.4%
264 1
0.4%
263 1
0.4%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
경상북도
272 

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 272
100.0%

Length

2024-03-16T13:12:19.827112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:12:19.981458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 272
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
경산시
272 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경산시 272
100.0%

Length

2024-03-16T13:12:20.175073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:12:20.392352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경산시 272
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
47290
272 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47290
2nd row47290
3rd row47290
4th row47290
5th row47290

Common Values

ValueCountFrequency (%)
47290 272
100.0%

Length

2024-03-16T13:12:20.565320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:12:20.722916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47290 272
100.0%

과세년도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023
96 
2021
88 
2022
88 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2023 96
35.3%
2021 88
32.4%
2022 88
32.4%

Length

2024-03-16T13:12:20.872038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:12:21.089404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 96
35.3%
2021 88
32.4%
2022 88
32.4%

세목명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
취득세
24 
등록세
24 
면허세
24 
주민세
24 
재산세
24 
Other values (7)
152 

Length

Max length7
Median length5
Mean length4.1176471
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 24
8.8%
등록세 24
8.8%
면허세 24
8.8%
주민세 24
8.8%
재산세 24
8.8%
자동차세 24
8.8%
종합토지세 24
8.8%
등록면허세 24
8.8%
사업소세 24
8.8%
지역자원시설세 24
8.8%
Other values (2) 32
11.8%

Length

2024-03-16T13:12:21.320353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 24
8.8%
등록세 24
8.8%
면허세 24
8.8%
주민세 24
8.8%
재산세 24
8.8%
자동차세 24
8.8%
종합토지세 24
8.8%
등록면허세 24
8.8%
사업소세 24
8.8%
지역자원시설세 24
8.8%
Other values (2) 32
11.8%

체납액구간
Categorical

Distinct8
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
10만원이하금액
34 
30만원이하금액
34 
50만원이하금액
34 
100만원이하금액
34 
500만원이하금액
34 
Other values (3)
102 

Length

Max length11
Median length10
Mean length9.125
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10만원이하금액
2nd row10만원이하금액
3rd row10만원이하금액
4th row10만원이하금액
5th row10만원이하금액

Common Values

ValueCountFrequency (%)
10만원이하금액 34
12.5%
30만원이하금액 34
12.5%
50만원이하금액 34
12.5%
100만원이하금액 34
12.5%
500만원이하금액 34
12.5%
1000만원이하금액 34
12.5%
5000만원이하금액 34
12.5%
10000만원이하금액 34
12.5%

Length

2024-03-16T13:12:21.614817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:12:21.804088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원이하금액 34
12.5%
30만원이하금액 34
12.5%
50만원이하금액 34
12.5%
100만원이하금액 34
12.5%
500만원이하금액 34
12.5%
1000만원이하금액 34
12.5%
5000만원이하금액 34
12.5%
10000만원이하금액 34
12.5%

체납건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct103
Distinct (%)37.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1643.1397
Minimum0
Maximum16977
Zeros106
Zeros (%)39.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-16T13:12:22.009539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median29
Q31606.5
95-th percentile9975.25
Maximum16977
Range16977
Interquartile range (IQR)1606.5

Descriptive statistics

Standard deviation3323.6765
Coefficient of variation (CV)2.0227595
Kurtosis9.9994496
Mean1643.1397
Median Absolute Deviation (MAD)29
Skewness3.0306163
Sum446934
Variance11046825
MonotonicityNot monotonic
2024-03-16T13:12:22.599849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 106
39.0%
995 8
 
2.9%
449 8
 
2.9%
583 7
 
2.6%
28 7
 
2.6%
6 6
 
2.2%
4104 5
 
1.8%
16977 5
 
1.8%
4578 4
 
1.5%
5933 4
 
1.5%
Other values (93) 112
41.2%
ValueCountFrequency (%)
0 106
39.0%
3 1
 
0.4%
4 1
 
0.4%
6 6
 
2.2%
8 1
 
0.4%
9 1
 
0.4%
14 1
 
0.4%
16 1
 
0.4%
17 1
 
0.4%
18 2
 
0.7%
ValueCountFrequency (%)
16977 5
1.8%
16950 1
 
0.4%
16217 1
 
0.4%
10055 4
1.5%
10052 1
 
0.4%
10037 1
 
0.4%
10022 1
 
0.4%
9937 1
 
0.4%
5933 4
1.5%
5925 1
 
0.4%

체납금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct108
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8107154 × 108
Minimum0
Maximum2.3588717 × 109
Zeros106
Zeros (%)39.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-16T13:12:22.884965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5263080
Q393692195
95-th percentile9.4899531 × 108
Maximum2.3588717 × 109
Range2.3588717 × 109
Interquartile range (IQR)93692195

Descriptive statistics

Standard deviation4.4248009 × 108
Coefficient of variation (CV)2.4436755
Kurtosis13.488708
Mean1.8107154 × 108
Median Absolute Deviation (MAD)5263080
Skewness3.5847921
Sum4.925146 × 1010
Variance1.9578863 × 1017
MonotonicityNot monotonic
2024-03-16T13:12:23.091318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 106
39.0%
15904630 8
 
2.9%
9572320 7
 
2.6%
7828840 7
 
2.6%
1269690 6
 
2.2%
3012870 6
 
2.2%
2358871670 5
 
1.8%
488898360 5
 
1.8%
229034260 4
 
1.5%
67144220 4
 
1.5%
Other values (98) 114
41.9%
ValueCountFrequency (%)
0 106
39.0%
197080 1
 
0.4%
303870 1
 
0.4%
386430 1
 
0.4%
541680 1
 
0.4%
726690 1
 
0.4%
782884 1
 
0.4%
852180 1
 
0.4%
868390 1
 
0.4%
1253990 1
 
0.4%
ValueCountFrequency (%)
2358871670 5
1.8%
2343974350 1
 
0.4%
2087979730 1
 
0.4%
1883624830 1
 
0.4%
1643713310 1
 
0.4%
1405864140 1
 
0.4%
1353241550 1
 
0.4%
1065859900 2
 
0.7%
953230580 1
 
0.4%
945530090 1
 
0.4%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct131
Distinct (%)48.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6333.0699
Minimum1
Maximum53563
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-16T13:12:23.311192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q135
median243
Q36335
95-th percentile33079.4
Maximum53563
Range53562
Interquartile range (IQR)6300

Descriptive statistics

Standard deviation11827.988
Coefficient of variation (CV)1.8676548
Kurtosis5.5188956
Mean6333.0699
Median Absolute Deviation (MAD)240
Skewness2.4046619
Sum1722595
Variance1.3990131 × 108
MonotonicityNot monotonic
2024-03-16T13:12:23.564168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
243 24
 
8.8%
170 12
 
4.4%
27 12
 
4.4%
1 11
 
4.0%
3 9
 
3.3%
2982 8
 
2.9%
1404 8
 
2.9%
1987 8
 
2.9%
166 7
 
2.6%
15 6
 
2.2%
Other values (121) 167
61.4%
ValueCountFrequency (%)
1 11
4.0%
3 9
3.3%
4 1
 
0.4%
5 1
 
0.4%
6 3
 
1.1%
7 6
2.2%
13 3
 
1.1%
14 3
 
1.1%
15 6
2.2%
20 3
 
1.1%
ValueCountFrequency (%)
53563 4
1.5%
53562 1
 
0.4%
53493 1
 
0.4%
52262 1
 
0.4%
36586 4
1.5%
36585 1
 
0.4%
36543 1
 
0.4%
36045 1
 
0.4%
30653 4
1.5%
30652 1
 
0.4%

누적체납금액
Real number (ℝ)

HIGH CORRELATION 

Distinct135
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9665783 × 108
Minimum6710
Maximum6.4175922 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-16T13:12:23.821465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6710
5-th percentile185900
Q14289270
median33691650
Q34.3377128 × 108
95-th percentile4.0587206 × 109
Maximum6.4175922 × 109
Range6.4175855 × 109
Interquartile range (IQR)4.2948201 × 108

Descriptive statistics

Standard deviation1.4623816 × 109
Coefficient of variation (CV)2.099139
Kurtosis6.058645
Mean6.9665783 × 108
Median Absolute Deviation (MAD)33505750
Skewness2.58929
Sum1.8949093 × 1011
Variance2.13856 × 1018
MonotonicityNot monotonic
2024-03-16T13:12:24.043783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2447190 24
 
8.8%
20449000 12
 
4.4%
8665650 12
 
4.4%
185900 9
 
3.3%
49596280 8
 
2.9%
33691650 8
 
2.9%
24119330 8
 
2.9%
6710 8
 
2.9%
10146190 6
 
2.2%
73307140 6
 
2.2%
Other values (125) 171
62.9%
ValueCountFrequency (%)
6710 8
2.9%
89670 3
 
1.1%
185900 9
3.3%
203790 1
 
0.4%
310580 1
 
0.4%
745470 1
 
0.4%
868390 1
 
0.4%
1276400 6
2.2%
1564570 1
 
0.4%
2386940 3
 
1.1%
ValueCountFrequency (%)
6417592220 4
1.5%
6416412520 1
 
0.4%
6375872260 1
 
0.4%
6334806750 1
 
0.4%
5949347410 1
 
0.4%
5837003130 1
 
0.4%
5147879110 1
 
0.4%
4451181920 1
 
0.4%
4193289820 1
 
0.4%
4058720550 4
1.5%

Interactions

2024-03-16T13:12:17.644416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:14.554442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:15.269248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:16.231661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:16.999449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:17.884819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:14.755762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:15.403127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:16.370445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:17.126762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:18.102895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:14.892039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:15.642982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:16.565572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:17.264110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:18.321239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:15.012373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:15.796264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:16.702713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:17.386733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:18.512213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:15.137423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:15.929749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:16.846353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:17.505266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:12:24.178587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
연번1.0000.9440.0000.7590.2020.2820.2510.305
과세년도0.9441.0000.0000.0000.5530.3270.4530.567
세목명0.0000.0001.0000.0000.8700.5940.8180.672
체납액구간0.7590.0000.0001.0000.0000.0000.0000.000
체납건수0.2020.5530.8700.0001.0000.8190.9120.823
체납금액0.2820.3270.5940.0000.8191.0000.7860.850
누적체납건수0.2510.4530.8180.0000.9120.7861.0000.812
누적체납금액0.3050.5670.6720.0000.8230.8500.8121.000
2024-03-16T13:12:24.335764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명과세년도
체납액구간1.0000.0000.000
세목명0.0001.0000.000
과세년도0.0000.0001.000
2024-03-16T13:12:24.464827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
연번1.0000.1170.1600.0830.1510.9200.0000.494
체납건수0.1171.0000.9470.8740.8190.2700.5250.000
체납금액0.1600.9471.0000.8220.8660.2040.2970.000
누적체납건수0.0830.8740.8221.0000.8520.3210.5140.000
누적체납금액0.1510.8190.8660.8521.0000.2940.3620.000
과세년도0.9200.2700.2040.3210.2941.0000.0000.000
세목명0.0000.5250.2970.5140.3620.0001.0000.000
체납액구간0.4940.0000.0000.0000.0000.0000.0001.000

Missing values

2024-03-16T13:12:18.848799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:12:19.107706image/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

연번시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
01경상북도경산시472902021취득세10만원이하금액9726690873736220
12경상북도경산시472902021등록세10만원이하금액003185900
23경상북도경산시472902021면허세10만원이하금액002432447190
34경상북도경산시472902021주민세10만원이하금액34533888222012021160217370
45경상북도경산시472902021재산세10만원이하금액1222457055204972176001560
56경상북도경산시472902021자동차세10만원이하금액17067686836014758680894020
67경상북도경산시472902021종합토지세10만원이하금액001415098770
78경상북도경산시472902021등록면허세10만원이하금액4497828840140424119330
89경상북도경산시472902021사업소세10만원이하금액00189670
910경상북도경산시472902021지역자원시설세10만원이하금액0016710
연번시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
262263경상북도경산시472902023지방소득세10000만원이하금액1906188362483060396334806750
263264경상북도경산시472902023재산세10000만원이하금액53461065859900141072510816370
264265경상북도경산시472902023주민세10000만원이하금액1005522903426026914641409580
265266경상북도경산시472902023등록면허세10000만원이하금액99515904630298249596280
266267경상북도경산시472902023지역자원시설세10000만원이하금액283012870354289270
267268경상북도경산시472902023자동차세10000만원이하금액169772358871670535636417592220
268269경상북도경산시472902023담배소비세10000만원이하금액223510226670223510226670
269270경상북도경산시472902023면허세10000만원이하금액002432447190
270271경상북도경산시472902023종합토지세10000만원이하금액0017020449000
271272경상북도경산시472902023사업소세10000만원이하금액00278665650