Overview

Dataset statistics

Number of variables12
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory105.5 B

Variable types

Categorical7
Numeric5

Dataset

Description지방세 유형별 미환급 유형 및 미환급 금액에 대한 데이터를 제공합니다. 자치단체의 지방세 환급금 해소노력 확인이 가능합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=350&beforeMenuCd=DOM_000000201001001000&publicdatapk=15079069

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 3 other fieldsHigh correlation
누적미환급금액 is highly overall correlated with 당해미환급건수 and 4 other fieldsHigh correlation
누적미환급금액증감 is highly overall correlated with 누적미환급건수 and 1 other fieldsHigh correlation
납세자유형 is highly overall correlated with 누적미환급금액High correlation
당해미환급금액 has unique valuesUnique
누적미환급금액증감 has 7 (13.5%) zerosZeros

Reproduction

Analysis started2024-01-09 22:23:18.078089
Analysis finished2024-01-09 22:23:20.560737
Duration2.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
충청남도
52 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 52
100.0%

Length

2024-01-10T07:23:20.622744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:23:20.713704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 52
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
아산시
52 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아산시 52
100.0%

Length

2024-01-10T07:23:20.807488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:23:20.896859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아산시 52
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
44200
52 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44200
2nd row44200
3rd row44200
4th row44200
5th row44200

Common Values

ValueCountFrequency (%)
44200 52
100.0%

Length

2024-01-10T07:23:20.991297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:23:21.098886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44200 52
100.0%

세목명
Categorical

Distinct6
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
지방소득세
16 
자동차세
15 
재산세
10 
등록면허세
7 
주민세
3 

Length

Max length5
Median length4
Mean length4.1730769
Min length3

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 16
30.8%
자동차세 15
28.8%
재산세 10
19.2%
등록면허세 7
13.5%
주민세 3
 
5.8%
취득세 1
 
1.9%

Length

2024-01-10T07:23:21.193410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:23:21.280939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 16
30.8%
자동차세 15
28.8%
재산세 10
19.2%
등록면허세 7
13.5%
주민세 3
 
5.8%
취득세 1
 
1.9%

과세년도
Categorical

Distinct5
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size548.0 B
2021
19 
2020
12 
2019
10 
2017
6 
2018
5 

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 19
36.5%
2020 12
23.1%
2019 10
19.2%
2017 6
 
11.5%
2018 5
 
9.6%

Length

2024-01-10T07:23:21.372871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:23:21.471156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 19
36.5%
2020 12
23.1%
2019 10
19.2%
2017 6
 
11.5%
2018 5
 
9.6%

미환급유형
Categorical

Distinct3
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
신규
38 
송달분 미수령
10 
주소불명
4 

Length

Max length7
Median length2
Mean length3.1153846
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신규 38
73.1%
송달분 미수령 10
 
19.2%
주소불명 4
 
7.7%

Length

2024-01-10T07:23:21.596727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:23:21.688875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 38
61.3%
송달분 10
 
16.1%
미수령 10
 
16.1%
주소불명 4
 
6.5%

납세자유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
개인
27 
법인
25 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 27
51.9%
법인 25
48.1%

Length

2024-01-10T07:23:21.765361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:23:21.837918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 27
51.9%
법인 25
48.1%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)51.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.826923
Minimum1
Maximum880
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-01-10T07:23:21.910955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q363
95-th percentile418.6
Maximum880
Range879
Interquartile range (IQR)61

Descriptive statistics

Standard deviation188.80893
Coefficient of variation (CV)2.19988
Kurtosis9.3748524
Mean85.826923
Median Absolute Deviation (MAD)4
Skewness3.0089326
Sum4463
Variance35648.813
MonotonicityNot monotonic
2024-01-10T07:23:22.000371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 10
19.2%
3 6
 
11.5%
2 6
 
11.5%
4 3
 
5.8%
11 2
 
3.8%
5 2
 
3.8%
12 2
 
3.8%
8 2
 
3.8%
32 1
 
1.9%
31 1
 
1.9%
Other values (17) 17
32.7%
ValueCountFrequency (%)
1 10
19.2%
2 6
11.5%
3 6
11.5%
4 3
 
5.8%
5 2
 
3.8%
6 1
 
1.9%
8 2
 
3.8%
11 2
 
3.8%
12 2
 
3.8%
30 1
 
1.9%
ValueCountFrequency (%)
880 1
1.9%
819 1
1.9%
423 1
1.9%
415 1
1.9%
355 1
1.9%
323 1
1.9%
302 1
1.9%
159 1
1.9%
154 1
1.9%
102 1
1.9%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325868.3
Minimum3630
Maximum31020630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-01-10T07:23:22.119398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3630
5-th percentile10685.5
Q164957.5
median311015
Q33314335
95-th percentile15068554
Maximum31020630
Range31017000
Interquartile range (IQR)3249377.5

Descriptive statistics

Standard deviation6311648.9
Coefficient of variation (CV)1.8977447
Kurtosis7.4027884
Mean3325868.3
Median Absolute Deviation (MAD)299180
Skewness2.588893
Sum1.7294515 × 108
Variance3.9836912 × 1013
MonotonicityNot monotonic
2024-01-10T07:23:22.268779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1492420 1
 
1.9%
23650 1
 
1.9%
13171080 1
 
1.9%
313070 1
 
1.9%
272730 1
 
1.9%
8573540 1
 
1.9%
15010 1
 
1.9%
65580 1
 
1.9%
299950 1
 
1.9%
50190 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
3630 1
1.9%
7200 1
1.9%
9470 1
1.9%
11680 1
1.9%
11990 1
1.9%
14030 1
1.9%
15010 1
1.9%
20190 1
1.9%
23650 1
1.9%
24760 1
1.9%
ValueCountFrequency (%)
31020630 1
1.9%
21291660 1
1.9%
17387690 1
1.9%
13171080 1
1.9%
13036340 1
1.9%
10943210 1
1.9%
10360530 1
1.9%
8921900 1
1.9%
8850150 1
1.9%
8573540 1
1.9%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean359.40385
Minimum1
Maximum1911
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-01-10T07:23:22.406362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q19.75
median64
Q3330.25
95-th percentile1736.65
Maximum1911
Range1910
Interquartile range (IQR)320.5

Descriptive statistics

Standard deviation585.89356
Coefficient of variation (CV)1.6301817
Kurtosis1.6157369
Mean359.40385
Median Absolute Deviation (MAD)61.5
Skewness1.7133531
Sum18689
Variance343271.27
MonotonicityNot monotonic
2024-01-10T07:23:22.535836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 5
 
9.6%
10 4
 
7.7%
31 3
 
5.8%
1594 3
 
5.8%
3 3
 
5.8%
1911 3
 
5.8%
1124 2
 
3.8%
23 2
 
3.8%
793 2
 
3.8%
113 2
 
3.8%
Other values (20) 23
44.2%
ValueCountFrequency (%)
1 5
9.6%
2 1
 
1.9%
3 3
5.8%
4 1
 
1.9%
6 1
 
1.9%
8 1
 
1.9%
9 1
 
1.9%
10 4
7.7%
12 1
 
1.9%
14 1
 
1.9%
ValueCountFrequency (%)
1911 3
5.8%
1594 3
5.8%
1124 2
3.8%
947 1
 
1.9%
793 2
3.8%
586 1
 
1.9%
532 1
 
1.9%
263 1
 
1.9%
230 1
 
1.9%
203 2
3.8%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11168306
Minimum7200
Maximum49514680
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-01-10T07:23:22.674808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7200
5-th percentile18529
Q1382107.5
median3685385
Q316909290
95-th percentile44754122
Maximum49514680
Range49507480
Interquartile range (IQR)16527182

Descriptive statistics

Standard deviation14946847
Coefficient of variation (CV)1.3383271
Kurtosis0.82561448
Mean11168306
Median Absolute Deviation (MAD)3661170
Skewness1.3907841
Sum5.8075192 × 108
Variance2.2340824 × 1014
MonotonicityNot monotonic
2024-01-10T07:23:22.809269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
31543410 3
 
5.8%
9783010 3
 
5.8%
49514680 3
 
5.8%
1064150 3
 
5.8%
15254320 2
 
3.8%
40859120 2
 
3.8%
1993030 2
 
3.8%
16909290 2
 
3.8%
3822230 2
 
3.8%
28036220 2
 
3.8%
Other values (28) 28
53.8%
ValueCountFrequency (%)
7200 1
1.9%
11990 1
1.9%
14030 1
1.9%
22210 1
1.9%
23670 1
1.9%
24760 1
1.9%
43940 1
1.9%
56650 1
1.9%
88400 1
1.9%
123890 1
1.9%
ValueCountFrequency (%)
49514680 3
5.8%
40859120 2
3.8%
31543410 3
5.8%
28036220 2
3.8%
21702110 1
 
1.9%
21662240 1
 
1.9%
16909290 2
3.8%
15254320 2
3.8%
11301710 1
 
1.9%
10758900 1
 
1.9%

누적미환급금액증감
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct44
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21091.981
Minimum0
Maximum868864
Zeros7
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-01-10T07:23:22.943294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q121.25
median100.5
Q31321.25
95-th percentile37262
Maximum868864
Range868864
Interquartile range (IQR)1300

Descriptive statistics

Standard deviation120726.24
Coefficient of variation (CV)5.7237981
Kurtosis50.453272
Mean21091.981
Median Absolute Deviation (MAD)100.5
Skewness7.0602969
Sum1096783
Variance1.4574825 × 1010
MonotonicityNot monotonic
2024-01-10T07:23:23.073599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 7
 
13.5%
27 2
 
3.8%
12 2
 
3.8%
59 1
 
1.9%
123 1
 
1.9%
48 1
 
1.9%
1523 1
 
1.9%
255 1
 
1.9%
2020 1
 
1.9%
18313 1
 
1.9%
Other values (34) 34
65.4%
ValueCountFrequency (%)
0 7
13.5%
9 1
 
1.9%
10 1
 
1.9%
12 2
 
3.8%
14 1
 
1.9%
19 1
 
1.9%
22 1
 
1.9%
27 2
 
3.8%
30 1
 
1.9%
31 1
 
1.9%
ValueCountFrequency (%)
868864 1
1.9%
83651 1
1.9%
58195 1
1.9%
20135 1
1.9%
18313 1
1.9%
16537 1
1.9%
8321 1
1.9%
4021 1
1.9%
3487 1
1.9%
3059 1
1.9%

Interactions

2024-01-10T07:23:19.741785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:18.437129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:18.742185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:19.074605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:19.408449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:20.077340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:18.492369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:18.806453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:19.135733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:19.466694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:20.142379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:18.555980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:18.877992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:19.206677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:19.537274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:20.210834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:18.625295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:18.948452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:19.277955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:19.614487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:20.270758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:18.684410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:19.013700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:19.346347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:23:19.680643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:23:23.166830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.1730.2330.000
과세년도0.0001.0000.3040.0000.2880.2240.3910.6310.000
미환급유형0.0000.3041.0000.0000.0000.0000.0000.4260.279
납세자유형0.0000.0000.0001.0000.2400.2830.6040.6110.000
당해미환급건수0.0000.2880.0000.2401.0000.7660.8710.6650.000
당해미환급금액0.0000.2240.0000.2830.7661.0000.8300.832NaN
누적미환급건수0.1730.3910.0000.6040.8710.8301.0000.9110.612
누적미환급금액0.2330.6310.4260.6110.6650.8320.9111.0000.439
누적미환급금액증감0.0000.0000.2790.0000.000NaN0.6120.4391.000
2024-01-10T07:23:23.272519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명미환급유형납세자유형
과세년도1.0000.0000.2320.000
세목명0.0001.0000.0000.000
미환급유형0.2320.0001.0000.000
납세자유형0.0000.0000.0001.000
2024-01-10T07:23:23.353636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도미환급유형납세자유형
당해미환급건수1.0000.7970.6590.5370.0720.0000.1030.0000.282
당해미환급금액0.7971.0000.5360.584-0.1500.0000.1280.0000.175
누적미환급건수0.6590.5361.0000.8890.5750.0780.2390.0000.426
누적미환급금액0.5370.5840.8891.0000.5570.1230.4060.1990.550
누적미환급금액증감0.072-0.1500.5750.5571.0000.0000.0000.4470.000
세목명0.0000.0000.0780.1230.0001.0000.0000.0000.000
과세년도0.1030.1280.2390.4060.0000.0001.0000.2320.000
미환급유형0.0000.0000.0000.1990.4470.0000.2321.0000.000
납세자유형0.2820.1750.4260.5500.0000.0000.0000.0001.000

Missing values

2024-01-10T07:23:20.356715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:23:20.496417image/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
0충청남도아산시44200자동차세2017신규개인1591492420230237981059
1충청남도아산시44200자동차세2017신규법인88538023305340258
2충청남도아산시44200재산세2017신규개인39470943940364
3충청남도아산시44200재산세2017신규법인1247601247600
4충청남도아산시44200지방소득세2017신규개인691254000109190875052
5충청남도아산시44200지방소득세2017신규법인2104130412389019
6충청남도아산시44200자동차세2018신규개인30289219005321130171027
7충청남도아산시44200자동차세2018신규법인3384055056114589036
8충청남도아산시44200재산세2018신규개인53604401440438012
9충청남도아산시44200지방소득세2018신규개인15488501502631075890022
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
42충청남도아산시44200재산세2021송달분 미수령개인1201901571690929083651
43충청남도아산시44200재산세2021신규개인75130363401571690929030
44충청남도아산시44200재산세2021신규법인2330312010361841010
45충청남도아산시44200주민세2021신규개인311680623670103
46충청남도아산시44200지방소득세2021송달분 미수령개인125880101594495146808321
47충청남도아산시44200지방소득세2021신규개인81921291660159449514680133
48충청남도아산시44200지방소득세2021주소불명개인424470015944951468020135
49충청남도아산시44200지방소득세2021송달분 미수령법인370090644085912058195
50충청남도아산시44200지방소득세2021신규법인3131020630644085912032
51충청남도아산시44200취득세2021신규개인1884001884000