Overview

Dataset statistics

Number of variables12
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory106.6 B

Variable types

Categorical7
Numeric5

Dataset

Description지방세 미환급 현황, 미환급 유형별 미환급금 현황 및 연간 누적률 제공, 자치단체의 환급금 해소노력 확인 가능, 지방세 환급현황
Author강원특별자치도 양양군
URLhttps://www.data.go.kr/data/15079486/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
당해미환급건수 is highly overall correlated with 당해미환급금액 and 2 other fieldsHigh correlation
당해미환급금액 is highly overall correlated with 당해미환급건수 and 2 other fieldsHigh correlation
누적미환급건수 is highly overall correlated with 당해미환급건수 and 2 other fieldsHigh correlation
누적미환급금액 is highly overall correlated with 당해미환급건수 and 2 other fieldsHigh correlation
누적미환급금액증감 is highly overall correlated with 미환급유형High correlation
미환급유형 is highly overall correlated with 누적미환급금액증감High correlation
미환급유형 is highly imbalanced (77.0%)Imbalance
당해미환급금액 has unique valuesUnique
누적미환급금액증감 has 6 (16.7%) zerosZeros

Reproduction

Analysis started2024-03-14 11:46:23.963326
Analysis finished2024-03-14 11:46:30.360397
Duration6.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size416.0 B
강원도
36 

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 36
100.0%

Length

2024-03-14T20:46:30.538693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:46:30.857355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 36
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size416.0 B
양양군
36 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양양군 36
100.0%

Length

2024-03-14T20:46:31.064836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:46:31.376695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양양군 36
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size416.0 B
42830
36 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row42830
2nd row42830
3rd row42830
4th row42830
5th row42830

Common Values

ValueCountFrequency (%)
42830 36
100.0%

Length

2024-03-14T20:46:31.710585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:46:32.027997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
42830 36
100.0%

세목명
Categorical

Distinct6
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size416.0 B
자동차세
11 
지방소득세
9 
재산세
7 
등록면허세
6 
주민세
2 

Length

Max length5
Median length4
Mean length4.1944444
Min length3

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 11
30.6%
지방소득세 9
25.0%
재산세 7
19.4%
등록면허세 6
16.7%
주민세 2
 
5.6%
담배소비세 1
 
2.8%

Length

2024-03-14T20:46:32.393940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:46:32.747799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 11
30.6%
지방소득세 9
25.0%
재산세 7
19.4%
등록면허세 6
16.7%
주민세 2
 
5.6%
담배소비세 1
 
2.8%

과세년도
Categorical

Distinct5
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size416.0 B
2020
10 
2017
7 
2018
7 
2019
6 
2021
6 

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 (%)
2020 10
27.8%
2017 7
19.4%
2018 7
19.4%
2019 6
16.7%
2021 6
16.7%

Length

2024-03-14T20:46:33.105535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:46:33.443476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 10
27.8%
2017 7
19.4%
2018 7
19.4%
2019 6
16.7%
2021 6
16.7%

미환급유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size416.0 B
신규
34 
사망
 
1
기타
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)5.6%

Sample

1st row신규
2nd row사망
3rd row신규
4th row신규
5th row신규

Common Values

ValueCountFrequency (%)
신규 34
94.4%
사망 1
 
2.8%
기타 1
 
2.8%

Length

2024-03-14T20:46:33.836674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:46:34.170758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 34
94.4%
사망 1
 
2.8%
기타 1
 
2.8%

납세자유형
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size416.0 B
개인
22 
법인
14 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row개인
3rd row개인
4th row법인
5th row개인

Common Values

ValueCountFrequency (%)
개인 22
61.1%
법인 14
38.9%

Length

2024-03-14T20:46:34.492072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:46:34.816654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 22
61.1%
법인 14
38.9%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.472222
Minimum1
Maximum227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size452.0 B
2024-03-14T20:46:35.130788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q314.5
95-th percentile100.5
Maximum227
Range226
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation47.058314
Coefficient of variation (CV)2.2986422
Kurtosis13.235185
Mean20.472222
Median Absolute Deviation (MAD)3
Skewness3.6211066
Sum737
Variance2214.4849
MonotonicityNot monotonic
2024-03-14T20:46:35.497275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 7
19.4%
2 7
19.4%
3 3
 
8.3%
4 3
 
8.3%
76 1
 
2.8%
227 1
 
2.8%
12 1
 
2.8%
11 1
 
2.8%
174 1
 
2.8%
8 1
 
2.8%
Other values (10) 10
27.8%
ValueCountFrequency (%)
1 7
19.4%
2 7
19.4%
3 3
8.3%
4 3
8.3%
5 1
 
2.8%
8 1
 
2.8%
9 1
 
2.8%
10 1
 
2.8%
11 1
 
2.8%
12 1
 
2.8%
ValueCountFrequency (%)
227 1
2.8%
174 1
2.8%
76 1
2.8%
41 1
2.8%
31 1
2.8%
25 1
2.8%
19 1
2.8%
17 1
2.8%
16 1
2.8%
14 1
2.8%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean591684.44
Minimum3410
Maximum4722520
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size452.0 B
2024-03-14T20:46:35.863025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410
5-th percentile6242.5
Q128197.5
median60845
Q3462087.5
95-th percentile3302042.5
Maximum4722520
Range4719110
Interquartile range (IQR)433890

Descriptive statistics

Standard deviation1123709.6
Coefficient of variation (CV)1.8991704
Kurtosis5.5905907
Mean591684.44
Median Absolute Deviation (MAD)54000
Skewness2.445176
Sum21300640
Variance1.2627232 × 1012
MonotonicityNot monotonic
2024-03-14T20:46:36.261252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
7200 1
 
2.8%
47560 1
 
2.8%
115200 1
 
2.8%
11390 1
 
2.8%
1060660 1
 
2.8%
45540 1
 
2.8%
431020 1
 
2.8%
3410 1
 
2.8%
55020 1
 
2.8%
3396670 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
3410 1
2.8%
5950 1
2.8%
6340 1
2.8%
7200 1
2.8%
9220 1
2.8%
10490 1
2.8%
11390 1
2.8%
21140 1
2.8%
27020 1
2.8%
28590 1
2.8%
ValueCountFrequency (%)
4722520 1
2.8%
3396670 1
2.8%
3270500 1
2.8%
2158260 1
2.8%
2002830 1
2.8%
1060660 1
2.8%
944290 1
2.8%
854750 1
2.8%
555290 1
2.8%
431020 1
2.8%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.916667
Minimum1
Maximum328
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size452.0 B
2024-03-14T20:46:36.622984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.75
Q14
median11.5
Q346.75
95-th percentile208
Maximum328
Range327
Interquartile range (IQR)42.75

Descriptive statistics

Standard deviation76.883353
Coefficient of variation (CV)1.7506646
Kurtosis7.8609496
Mean43.916667
Median Absolute Deviation (MAD)9.5
Skewness2.8046837
Sum1581
Variance5911.05
MonotonicityNot monotonic
2024-03-14T20:46:37.012853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
4 5
 
13.9%
2 4
 
11.1%
1 2
 
5.6%
23 2
 
5.6%
9 2
 
5.6%
61 2
 
5.6%
176 1
 
2.8%
12 1
 
2.8%
304 1
 
2.8%
35 1
 
2.8%
Other values (15) 15
41.7%
ValueCountFrequency (%)
1 2
 
5.6%
2 4
11.1%
3 1
 
2.8%
4 5
13.9%
6 1
 
2.8%
7 1
 
2.8%
9 2
 
5.6%
10 1
 
2.8%
11 1
 
2.8%
12 1
 
2.8%
ValueCountFrequency (%)
328 1
2.8%
304 1
2.8%
176 1
2.8%
116 1
2.8%
88 1
2.8%
75 1
2.8%
67 1
2.8%
61 2
5.6%
42 1
2.8%
35 1
2.8%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1004351.9
Minimum7200
Maximum6232240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size452.0 B
2024-03-14T20:46:37.398870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7200
5-th percentile14977.5
Q168762.5
median221270
Q31149602.5
95-th percentile4722280
Maximum6232240
Range6225040
Interquartile range (IQR)1080840

Descriptive statistics

Standard deviation1568054.8
Coefficient of variation (CV)1.5612602
Kurtosis3.5271148
Mean1004351.9
Median Absolute Deviation (MAD)207735
Skewness2.0256164
Sum36156670
Variance2.4587958 × 1012
MonotonicityNot monotonic
2024-03-14T20:46:37.825351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
679490 2
 
5.6%
274770 2
 
5.6%
4722200 1
 
2.8%
114470 1
 
2.8%
2117910 1
 
2.8%
121150 1
 
2.8%
495960 1
 
2.8%
10650 1
 
2.8%
55350 1
 
2.8%
7200 1
 
2.8%
Other values (24) 24
66.7%
ValueCountFrequency (%)
7200 1
2.8%
10650 1
2.8%
16420 1
2.8%
21140 1
2.8%
30180 1
2.8%
47560 1
2.8%
52570 1
2.8%
55350 1
2.8%
57730 1
2.8%
72440 1
2.8%
ValueCountFrequency (%)
6232240 1
2.8%
4722520 1
2.8%
4722200 1
2.8%
3795940 1
2.8%
2349450 1
2.8%
2170930 1
2.8%
2117910 1
2.8%
2073810 1
2.8%
1209850 1
2.8%
1129520 1
2.8%

누적미환급금액증감
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean302.84833
Minimum0
Maximum1732.81
Zeros6
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size452.0 B
2024-03-14T20:46:38.213455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114.975
median83.81
Q3230.29
95-th percentile1299.4225
Maximum1732.81
Range1732.81
Interquartile range (IQR)215.315

Descriptive statistics

Standard deviation471.11447
Coefficient of variation (CV)1.5556119
Kurtosis2.3503876
Mean302.84833
Median Absolute Deviation (MAD)83.81
Skewness1.8227752
Sum10902.54
Variance221948.85
MonotonicityNot monotonic
2024-03-14T20:46:38.627346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.0 6
 
16.7%
0.6 2
 
5.6%
119.62 1
 
2.8%
1128.86 1
 
2.8%
90.56 1
 
2.8%
742.31 1
 
2.8%
14.6 1
 
2.8%
89.53 1
 
2.8%
39.0 1
 
2.8%
212.3 1
 
2.8%
Other values (20) 20
55.6%
ValueCountFrequency (%)
0.0 6
16.7%
0.6 2
 
5.6%
14.6 1
 
2.8%
15.1 1
 
2.8%
32.15 1
 
2.8%
39.0 1
 
2.8%
44.94 1
 
2.8%
45.42 1
 
2.8%
45.6 1
 
2.8%
71.42 1
 
2.8%
ValueCountFrequency (%)
1732.81 1
2.8%
1545.25 1
2.8%
1217.48 1
2.8%
1128.86 1
2.8%
916.91 1
2.8%
905.0 1
2.8%
742.31 1
2.8%
618.9 1
2.8%
284.26 1
2.8%
212.3 1
2.8%

Interactions

2024-03-14T20:46:29.044964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:24.535840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:25.740922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:26.956328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:28.304851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:29.187922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:24.770446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:25.982880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:27.196456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:28.439836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:29.413489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:25.005433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:26.213403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:27.433961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:28.582366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:29.568417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:25.247379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:26.458981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:27.686331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:28.739307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:29.723699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:25.492310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:26.705371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:27.931237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:46:28.889780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T20:46:38.909052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.5530.0000.7270.000
과세년도0.0001.0000.1450.0000.4240.0000.2590.1480.221
미환급유형0.0000.1451.0000.0000.0000.0000.0000.0000.977
납세자유형0.0000.0000.0001.0000.1100.0000.5590.0000.000
당해미환급건수0.0000.4240.0000.1101.0000.8820.8740.8400.000
당해미환급금액0.5530.0000.0000.0000.8821.0000.7490.8650.000
누적미환급건수0.0000.2590.0000.5590.8740.7491.0000.8940.000
누적미환급금액0.7270.1480.0000.0000.8400.8650.8941.0000.000
누적미환급금액증감0.0000.2210.9770.0000.0000.0000.0000.0001.000
2024-03-14T20:46:39.214407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도미환급유형납세자유형세목명
과세년도1.0000.0900.0000.000
미환급유형0.0901.0000.0000.000
납세자유형0.0000.0001.0000.000
세목명0.0000.0000.0001.000
2024-03-14T20:46:39.669812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도미환급유형납세자유형
당해미환급건수1.0000.7170.8390.6890.0520.0000.1590.0000.116
당해미환급금액0.7171.0000.5300.849-0.3150.3650.0000.0000.000
누적미환급건수0.8390.5301.0000.7360.4550.0000.1630.0000.376
누적미환급금액0.6890.8490.7361.0000.1690.3440.0940.0000.000
누적미환급금액증감0.052-0.3150.4550.1691.0000.0000.0860.7380.000
세목명0.0000.3650.0000.3440.0001.0000.0000.0000.000
과세년도0.1590.0000.1630.0940.0860.0001.0000.0900.000
미환급유형0.0000.0000.0000.0000.7380.0000.0901.0000.000
납세자유형0.1160.0000.3760.0000.0000.0000.0000.0001.000

Missing values

2024-03-14T20:46:29.950471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T20:46:30.240784image/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

시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
0강원도양양군42830등록면허세2017신규개인17200172000.0
1강원도양양군42830자동차세2017사망개인541300616794901545.25
2강원도양양군42830자동차세2017신규개인1722775061679490198.35
3강원도양양군42830자동차세2017신규법인35607078127044.94
4강원도양양군42830재산세2017신규개인210490430180187.7
5강원도양양군42830지방소득세2017기타개인12702023274770916.91
6강원도양양군42830지방소득세2017신규개인101599302327477071.81
7강원도양양군42830등록면허세2018신규개인1922021642078.09
8강원도양양군42830등록면허세2018신규법인310308031030800.0
9강원도양양군42830자동차세2018신규개인1410979075789280618.9
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
26강원도양양군42830재산세2020신규법인33410410650212.3
27강원도양양군42830주민세2020신규개인1550202553500.6
28강원도양양군42830지방소득세2020신규개인31339667088472220039.0
29강원도양양군42830지방소득세2020신규법인82158260921709300.6
30강원도양양군42830자동차세2021신규개인1742002830328379594089.53
31강원도양양군42830자동차세2021신규법인115552901963637014.6
32강원도양양군42830재산세2021신규개인126396035538740742.31
33강원도양양군42830주민세2021신규법인1577301577300.0
34강원도양양군42830지방소득세2021신규개인2273270500304623224090.56
35강원도양양군42830지방소득세2021신규법인41911901223494501128.86