Overview

Dataset statistics

Number of variables12
Number of observations162
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.4 KiB
Average record size in memory103.8 B

Variable types

Numeric5
Categorical6
DateTime1

Dataset

Description평창군 지방세 체납현황에 대한 데이터로, 과세년도, 세목명, 체납액구간, 체납건수, 체납금액, 누적체납건수, 누적체납금액을 제공합니다.(2017~2021)
Author강원도 평창군
URLhttps://www.data.go.kr/data/15080525/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일자 has constant value ""Constant
순번 is highly overall correlated with 과세년도High correlation
체납건수 is highly overall correlated with 누적체납건수High correlation
체납금액 is highly overall correlated with 누적체납금액High correlation
누적체납건수 is highly overall correlated with 체납건수High correlation
누적체납금액 is highly overall correlated with 체납금액High correlation
과세년도 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:02:05.143846
Analysis finished2023-12-12 18:02:09.015996
Duration3.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct162
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.5
Minimum1
Maximum162
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:02:09.117108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.05
Q141.25
median81.5
Q3121.75
95-th percentile153.95
Maximum162
Range161
Interquartile range (IQR)80.5

Descriptive statistics

Standard deviation46.909487
Coefficient of variation (CV)0.57557653
Kurtosis-1.2
Mean81.5
Median Absolute Deviation (MAD)40.5
Skewness0
Sum13203
Variance2200.5
MonotonicityStrictly increasing
2023-12-13T03:02:09.318146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
123 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
112 1
 
0.6%
Other values (152) 152
93.8%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
162 1
0.6%
161 1
0.6%
160 1
0.6%
159 1
0.6%
158 1
0.6%
157 1
0.6%
156 1
0.6%
155 1
0.6%
154 1
0.6%
153 1
0.6%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
강원도
162 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원도 162
100.0%

Length

2023-12-13T03:02:09.505362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:02:09.619961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 162
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
평창군
162 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
평창군 162
100.0%

Length

2023-12-13T03:02:09.740748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:02:09.860954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
평창군 162
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
42760
162 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row42760
2nd row42760
3rd row42760
4th row42760
5th row42760

Common Values

ValueCountFrequency (%)
42760 162
100.0%

Length

2023-12-13T03:02:09.980478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:02:10.406376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
42760 162
100.0%

과세년도
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2021
38 
2020
37 
2018
32 
2019
32 
2017
23 

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 (%)
2021 38
23.5%
2020 37
22.8%
2018 32
19.8%
2019 32
19.8%
2017 23
14.2%

Length

2023-12-13T03:02:10.527585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:02:10.685566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 38
23.5%
2020 37
22.8%
2018 32
19.8%
2019 32
19.8%
2017 23
14.2%

세목명
Categorical

Distinct7
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
지방소득세
42 
재산세
37 
취득세
37 
주민세
17 
자동차세
16 
Other values (2)
13 

Length

Max length7
Median length3
Mean length3.8765432
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row등록면허세
2nd row자동차세
3rd row자동차세
4th row자동차세
5th row재산세

Common Values

ValueCountFrequency (%)
지방소득세 42
25.9%
재산세 37
22.8%
취득세 37
22.8%
주민세 17
10.5%
자동차세 16
 
9.9%
지역자원시설세 8
 
4.9%
등록면허세 5
 
3.1%

Length

2023-12-13T03:02:10.833536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:02:10.995941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 42
25.9%
재산세 37
22.8%
취득세 37
22.8%
주민세 17
10.5%
자동차세 16
 
9.9%
지역자원시설세 8
 
4.9%
등록면허세 5
 
3.1%

체납액구간
Categorical

Distinct11
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
10만원 미만
35 
10만원~30만원미만
28 
30만원~50만원미만
20 
50만원~1백만원미만
18 
1백만원~3백만원미만
17 
Other values (6)
44 

Length

Max length11
Median length11
Mean length10.08642
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10만원 미만
2nd row10만원 미만
3rd row10만원~30만원미만
4th row30만원~50만원미만
5th row10만원 미만

Common Values

ValueCountFrequency (%)
10만원 미만 35
21.6%
10만원~30만원미만 28
17.3%
30만원~50만원미만 20
12.3%
50만원~1백만원미만 18
11.1%
1백만원~3백만원미만 17
10.5%
3백만원~5백만원미만 12
 
7.4%
5백만원~1천만원미만 11
 
6.8%
1천만원~3천만원미만 9
 
5.6%
3천만원~5천만원미만 6
 
3.7%
5천만원~1억원미만 4
 
2.5%

Length

2023-12-13T03:02:11.175406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 35
17.8%
미만 35
17.8%
10만원~30만원미만 28
14.2%
30만원~50만원미만 20
10.2%
50만원~1백만원미만 18
9.1%
1백만원~3백만원미만 17
8.6%
3백만원~5백만원미만 12
 
6.1%
5백만원~1천만원미만 11
 
5.6%
1천만원~3천만원미만 9
 
4.6%
3천만원~5천만원미만 6
 
3.0%
Other values (2) 6
 
3.0%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean211.82716
Minimum1
Maximum5805
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:02:11.338645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median8
Q352
95-th percentile853.4
Maximum5805
Range5804
Interquartile range (IQR)50

Descriptive statistics

Standard deviation723.91899
Coefficient of variation (CV)3.4174984
Kurtosis37.397969
Mean211.82716
Median Absolute Deviation (MAD)7
Skewness5.7232741
Sum34316
Variance524058.7
MonotonicityNot monotonic
2023-12-13T03:02:11.522815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 26
 
16.0%
2 20
 
12.3%
3 12
 
7.4%
4 8
 
4.9%
8 5
 
3.1%
5 5
 
3.1%
10 5
 
3.1%
18 4
 
2.5%
6 4
 
2.5%
7 3
 
1.9%
Other values (58) 70
43.2%
ValueCountFrequency (%)
1 26
16.0%
2 20
12.3%
3 12
7.4%
4 8
 
4.9%
5 5
 
3.1%
6 4
 
2.5%
7 3
 
1.9%
8 5
 
3.1%
9 2
 
1.2%
10 5
 
3.1%
ValueCountFrequency (%)
5805 1
0.6%
5277 1
0.6%
2724 1
0.6%
2363 1
0.6%
2165 1
0.6%
1815 1
0.6%
1443 1
0.6%
1165 1
0.6%
854 1
0.6%
842 1
0.6%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct162
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25313765
Minimum37080
Maximum1.7102865 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:02:11.722462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37080
5-th percentile219680
Q12040957.5
median10497535
Q336480920
95-th percentile1.0225889 × 108
Maximum1.7102865 × 108
Range1.7099157 × 108
Interquartile range (IQR)34439962

Descriptive statistics

Standard deviation33346292
Coefficient of variation (CV)1.3173186
Kurtosis3.6388994
Mean25313765
Median Absolute Deviation (MAD)9682710
Skewness1.9146364
Sum4.1008298 × 109
Variance1.1119752 × 1015
MonotonicityNot monotonic
2023-12-13T03:02:11.893119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1165260 1
 
0.6%
6521770 1
 
0.6%
904660 1
 
0.6%
5680750 1
 
0.6%
11659290 1
 
0.6%
36055530 1
 
0.6%
47007750 1
 
0.6%
10264440 1
 
0.6%
6317460 1
 
0.6%
18172770 1
 
0.6%
Other values (152) 152
93.8%
ValueCountFrequency (%)
37080 1
0.6%
41340 1
0.6%
46340 1
0.6%
121150 1
0.6%
135520 1
0.6%
143320 1
0.6%
158440 1
0.6%
178440 1
0.6%
211320 1
0.6%
378520 1
0.6%
ValueCountFrequency (%)
171028650 1
0.6%
141263600 1
0.6%
130104530 1
0.6%
125810040 1
0.6%
117977690 1
0.6%
116676660 1
0.6%
114089260 1
0.6%
103019070 1
0.6%
102380450 1
0.6%
99949170 1
0.6%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean609.32099
Minimum1
Maximum16008
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:02:12.087940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median19.5
Q3106.5
95-th percentile2602.65
Maximum16008
Range16007
Interquartile range (IQR)100.5

Descriptive statistics

Standard deviation2082.6757
Coefficient of variation (CV)3.4180272
Kurtosis32.65713
Mean609.32099
Median Absolute Deviation (MAD)17.5
Skewness5.379195
Sum98710
Variance4337538.1
MonotonicityNot monotonic
2023-12-13T03:02:12.321636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 12
 
7.4%
1 11
 
6.8%
3 6
 
3.7%
5 6
 
3.7%
4 5
 
3.1%
6 5
 
3.1%
9 4
 
2.5%
11 4
 
2.5%
12 4
 
2.5%
13 4
 
2.5%
Other values (79) 101
62.3%
ValueCountFrequency (%)
1 11
6.8%
2 12
7.4%
3 6
3.7%
4 5
3.1%
5 6
3.7%
6 5
3.1%
7 2
 
1.2%
8 3
 
1.9%
9 4
 
2.5%
10 2
 
1.2%
ValueCountFrequency (%)
16008 1
0.6%
14626 1
0.6%
9349 1
0.6%
6625 1
0.6%
6134 1
0.6%
5996 1
0.6%
4810 1
0.6%
3771 1
0.6%
2606 1
0.6%
2539 1
0.6%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct162
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51484549
Minimum46340
Maximum3.7109122 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:02:12.495898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46340
5-th percentile744671.5
Q15704690
median24127920
Q374488255
95-th percentile1.9232876 × 108
Maximum3.7109122 × 108
Range3.7104488 × 108
Interquartile range (IQR)68783565

Descriptive statistics

Standard deviation70197487
Coefficient of variation (CV)1.3634671
Kurtosis7.3230926
Mean51484549
Median Absolute Deviation (MAD)21178090
Skewness2.4989128
Sum8.340497 × 109
Variance4.9276872 × 1015
MonotonicityNot monotonic
2023-12-13T03:02:12.657039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3027360 1
 
0.6%
16527050 1
 
0.6%
1518490 1
 
0.6%
11330070 1
 
0.6%
23123230 1
 
0.6%
90791480 1
 
0.6%
81498820 1
 
0.6%
16959510 1
 
0.6%
32447980 1
 
0.6%
40308260 1
 
0.6%
Other values (152) 152
93.8%
ValueCountFrequency (%)
46340 1
0.6%
83420 1
0.6%
135520 1
0.6%
256670 1
0.6%
363630 1
0.6%
522070 1
0.6%
665390 1
0.6%
691060 1
0.6%
741820 1
0.6%
798850 1
0.6%
ValueCountFrequency (%)
371091220 1
0.6%
358906610 1
0.6%
343772290 1
0.6%
340048970 1
0.6%
240753220 1
0.6%
235197780 1
0.6%
234098470 1
0.6%
198785370 1
0.6%
193449820 1
0.6%
171028650 1
0.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2022-09-21 00:00:00
Maximum2022-09-21 00:00:00
2023-12-13T03:02:12.812475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:12.938303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T03:02:07.932387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:05.586304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:06.150510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:06.757708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:07.329092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:08.066032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:05.691130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:06.279568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:06.868963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:07.438107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:08.191715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:05.779327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:06.414042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:06.975552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:07.554360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:08.346423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:05.909861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:06.536613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:07.094065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:07.682182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:08.518487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:06.024117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:06.657267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:07.223344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:07.799189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:02:13.024848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
순번1.0000.9920.5160.0000.0000.1710.0000.280
과세년도0.9921.0000.0000.0000.0000.0000.0000.143
세목명0.5160.0001.0000.2160.2170.0000.4460.114
체납액구간0.0000.0000.2161.0000.0000.5620.0000.371
체납건수0.0000.0000.2170.0001.0000.6530.9170.688
체납금액0.1710.0000.0000.5620.6531.0000.6120.798
누적체납건수0.0000.0000.4460.0000.9170.6121.0000.689
누적체납금액0.2800.1430.1140.3710.6880.7980.6891.000
2023-12-13T03:02:13.160383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명과세년도
체납액구간1.0000.1050.000
세목명0.1051.0000.000
과세년도0.0000.0001.000
2023-12-13T03:02:13.267723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
순번1.0000.0850.2790.0080.2390.8560.2890.000
체납건수0.0851.0000.3090.9470.3710.0000.1290.000
체납금액0.2790.3091.0000.1800.9540.0000.0000.278
누적체납건수0.0080.9470.1801.0000.3100.0000.1680.000
누적체납금액0.2390.3710.9540.3101.0000.0920.0650.182
과세년도0.8560.0000.0000.0000.0921.0000.0000.000
세목명0.2890.1290.0000.1680.0650.0001.0000.105
체납액구간0.0000.0000.2780.0000.1820.0000.1051.000

Missing values

2023-12-13T03:02:08.714495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:02:08.937937image/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

순번시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액데이터기준일자
01강원도평창군427602017등록면허세10만원 미만85116526021230273602022-09-21
12강원도평창군427602017자동차세10만원 미만1937493530799312551102022-09-21
23강원도평창군427602017자동차세10만원~30만원미만15024835880490786251702022-09-21
34강원도평창군427602017자동차세30만원~50만원미만26378401033232102022-09-21
45강원도평창군427602017재산세10만원 미만1443242706004810888496502022-09-21
56강원도평창군427602017재산세10만원~30만원미만6910443670222345943002022-09-21
67강원도평창군427602017재산세1백만원~3백만원미만456101609121583402022-09-21
78강원도평창군427602017재산세30만원~50만원미만39539701861673602022-09-21
89강원도평창군427602017재산세50만원~1백만원미만7438850026173092702022-09-21
910강원도평창군427602017주민세10만원 미만61199947001764243767102022-09-21
순번시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액데이터기준일자
152153강원도평창군427602021취득세10만원 미만3212283804918943902022-09-21
153154강원도평창군427602021취득세10만원~30만원미만1829855505497153902022-09-21
154155강원도평창군427602021취득세1백만원~3백만원미만172888896034582974402022-09-21
155156강원도평창군427602021취득세1억원~3억원미만111408926011140892602022-09-21
156157강원도평창군427602021취득세1천만원~3천만원미만46089190091509374702022-09-21
157158강원도평창군427602021취득세30만원~50만원미만831286001558708002022-09-21
158159강원도평창군427602021취득세3백만원~5백만원미만4155085105191653902022-09-21
159160강원도평창군427602021취득세3천만원~5천만원미만1323528001323528002022-09-21
160161강원도평창군427602021취득세50만원~1백만원미만4323048019140261402022-09-21
161162강원도평창군427602021취득세5백만원~1천만원미만3176309004240300902022-09-21