Overview

Dataset statistics

Number of variables12
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory107.3 B

Variable types

Categorical7
Numeric5

Dataset

Description2017~2021년도 충청남도 보령시 지방세 관련 미환급 유형별 미환급금 현황 및 연간 누적률 현황 항목에 대한 자료를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=350&beforeMenuCd=DOM_000000201001001000&publicdatapk=15079102

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
미환급유형 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
당해미환급금액 has unique valuesUnique
누적미환급금액 has unique valuesUnique
누적미환급금액증감 has 3 (9.7%) zerosZeros

Reproduction

Analysis started2024-01-09 21:03:21.368914
Analysis finished2024-01-09 21:03:23.901408
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
충청남도
31 

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 31
100.0%

Length

2024-01-10T06:03:23.969198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:03:24.081031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 31
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
보령시
31 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보령시 31
100.0%

Length

2024-01-10T06:03:24.169012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:03:24.249849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보령시 31
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
44180
31 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44180
2nd row44180
3rd row44180
4th row44180
5th row44180

Common Values

ValueCountFrequency (%)
44180 31
100.0%

Length

2024-01-10T06:03:24.343373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:03:24.424482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44180 31
100.0%

세목명
Categorical

Distinct6
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size380.0 B
자동차세
10 
재산세
7 
지방소득세
7 
등록면허세
3 
주민세
3 

Length

Max length5
Median length4
Mean length3.9677419
Min length3

Unique

Unique1 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 10
32.3%
재산세 7
22.6%
지방소득세 7
22.6%
등록면허세 3
 
9.7%
주민세 3
 
9.7%
취득세 1
 
3.2%

Length

2024-01-10T06:03:24.525140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:03:24.637520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 10
32.3%
재산세 7
22.6%
지방소득세 7
22.6%
등록면허세 3
 
9.7%
주민세 3
 
9.7%
취득세 1
 
3.2%

과세년도
Categorical

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
2020
9 
2021
9 
2018
5 
2017
4 
2019
4 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2018

Common Values

ValueCountFrequency (%)
2020 9
29.0%
2021 9
29.0%
2018 5
16.1%
2017 4
12.9%
2019 4
12.9%

Length

2024-01-10T06:03:24.761378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:03:24.866085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 9
29.0%
2021 9
29.0%
2018 5
16.1%
2017 4
12.9%
2019 4
12.9%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
신규
31 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신규 31
100.0%

Length

2024-01-10T06:03:24.967319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:03:25.051826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 31
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
개인
20 
법인
11 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 20
64.5%
법인 11
35.5%

Length

2024-01-10T06:03:25.142313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:03:25.232409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 20
64.5%
법인 11
35.5%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)61.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.322581
Minimum1
Maximum216
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-10T06:03:25.322982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median6
Q342.5
95-th percentile107
Maximum216
Range215
Interquartile range (IQR)40.5

Descriptive statistics

Standard deviation46.952023
Coefficient of variation (CV)1.6012241
Kurtosis7.7500911
Mean29.322581
Median Absolute Deviation (MAD)5
Skewness2.5627846
Sum909
Variance2204.4925
MonotonicityNot monotonic
2024-01-10T06:03:25.431810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 7
22.6%
2 3
 
9.7%
5 2
 
6.5%
11 2
 
6.5%
45 2
 
6.5%
4 2
 
6.5%
38 1
 
3.2%
120 1
 
3.2%
6 1
 
3.2%
216 1
 
3.2%
Other values (9) 9
29.0%
ValueCountFrequency (%)
1 7
22.6%
2 3
9.7%
3 1
 
3.2%
4 2
 
6.5%
5 2
 
6.5%
6 1
 
3.2%
7 1
 
3.2%
11 2
 
6.5%
16 1
 
3.2%
20 1
 
3.2%
ValueCountFrequency (%)
216 1
3.2%
120 1
3.2%
94 1
3.2%
87 1
3.2%
65 1
3.2%
54 1
3.2%
45 2
6.5%
40 1
3.2%
38 1
3.2%
20 1
3.2%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean422344.19
Minimum610
Maximum2122170
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-10T06:03:25.546293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum610
5-th percentile3230
Q128250
median80070
Q3685985
95-th percentile1552725
Maximum2122170
Range2121560
Interquartile range (IQR)657735

Descriptive statistics

Standard deviation575536.02
Coefficient of variation (CV)1.362718
Kurtosis1.8051862
Mean422344.19
Median Absolute Deviation (MAD)79350
Skewness1.5651283
Sum13092670
Variance3.3124171 × 1011
MonotonicityNot monotonic
2024-01-10T06:03:25.916238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
597600 1
 
3.2%
21580 1
 
3.2%
21850 1
 
3.2%
365830 1
 
3.2%
1807210 1
 
3.2%
720 1
 
3.2%
5740 1
 
3.2%
481810 1
 
3.2%
87310 1
 
3.2%
2122170 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
610 1
3.2%
720 1
3.2%
5740 1
3.2%
9030 1
3.2%
11530 1
3.2%
21580 1
3.2%
21850 1
3.2%
23250 1
3.2%
33250 1
3.2%
33370 1
3.2%
ValueCountFrequency (%)
2122170 1
3.2%
1807210 1
3.2%
1298240 1
3.2%
1228510 1
3.2%
1162520 1
3.2%
868870 1
3.2%
851370 1
3.2%
774370 1
3.2%
597600 1
3.2%
481810 1
3.2%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.225806
Minimum1
Maximum580
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-10T06:03:26.029042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.5
Q15
median37
Q3128
95-th percentile356.5
Maximum580
Range579
Interquartile range (IQR)123

Descriptive statistics

Standard deviation136.50976
Coefficient of variation (CV)1.4487513
Kurtosis4.6454498
Mean94.225806
Median Absolute Deviation (MAD)34
Skewness2.1096249
Sum2921
Variance18634.914
MonotonicityNot monotonic
2024-01-10T06:03:26.153377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2 3
 
9.7%
6 2
 
6.5%
1 2
 
6.5%
3 2
 
6.5%
258 1
 
3.2%
110 1
 
3.2%
42 1
 
3.2%
580 1
 
3.2%
10 1
 
3.2%
166 1
 
3.2%
Other values (16) 16
51.6%
ValueCountFrequency (%)
1 2
6.5%
2 3
9.7%
3 2
6.5%
4 1
 
3.2%
6 2
6.5%
10 1
 
3.2%
25 1
 
3.2%
28 1
 
3.2%
30 1
 
3.2%
33 1
 
3.2%
ValueCountFrequency (%)
580 1
3.2%
386 1
3.2%
327 1
3.2%
258 1
3.2%
240 1
3.2%
175 1
3.2%
166 1
3.2%
146 1
3.2%
110 1
3.2%
92 1
3.2%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1384542.3
Minimum610
Maximum6291570
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-10T06:03:26.282732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum610
5-th percentile15440
Q1134510
median495120
Q32363465
95-th percentile4741200
Maximum6291570
Range6290960
Interquartile range (IQR)2228955

Descriptive statistics

Standard deviation1811939.4
Coefficient of variation (CV)1.308692
Kurtosis0.57727115
Mean1384542.3
Median Absolute Deviation (MAD)429520
Skewness1.3417635
Sum42920810
Variance3.2831245 × 1012
MonotonicityNot monotonic
2024-01-10T06:03:26.399741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
2579970 1
 
3.2%
391800 1
 
3.2%
21850 1
 
3.2%
366440 1
 
3.2%
4335720 1
 
3.2%
66320 1
 
3.2%
184310 1
 
3.2%
1179300 1
 
3.2%
638370 1
 
3.2%
6291570 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
610 1
3.2%
9030 1
3.2%
21850 1
3.2%
63070 1
3.2%
64360 1
3.2%
65600 1
3.2%
66320 1
3.2%
100760 1
3.2%
168260 1
3.2%
178570 1
3.2%
ValueCountFrequency (%)
6291570 1
3.2%
4965540 1
3.2%
4516860 1
3.2%
4335720 1
3.2%
3933670 1
3.2%
3445200 1
3.2%
3354340 1
3.2%
2579970 1
3.2%
2146960 1
3.2%
1179300 1
3.2%

누적미환급금액증감
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean757.5371
Minimum0
Maximum9111.11
Zeros3
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-10T06:03:26.510307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q170.655
median229.63
Q3496.775
95-th percentile2570.265
Maximum9111.11
Range9111.11
Interquartile range (IQR)426.12

Descriptive statistics

Standard deviation1701.2515
Coefficient of variation (CV)2.2457666
Kurtosis20.532921
Mean757.5371
Median Absolute Deviation (MAD)218.1
Skewness4.2964734
Sum23483.65
Variance2894256.8
MonotonicityNot monotonic
2024-01-10T06:03:26.619280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 3
 
9.7%
331.72 1
 
3.2%
229.63 1
 
3.2%
0.17 1
 
3.2%
139.91 1
 
3.2%
9111.11 1
 
3.2%
3110.98 1
 
3.2%
144.76 1
 
3.2%
631.15 1
 
3.2%
196.47 1
 
3.2%
Other values (19) 19
61.3%
ValueCountFrequency (%)
0.0 3
9.7%
0.17 1
 
3.2%
7.68 1
 
3.2%
11.53 1
 
3.2%
12.46 1
 
3.2%
66.55 1
 
3.2%
74.76 1
 
3.2%
116.84 1
 
3.2%
139.91 1
 
3.2%
144.76 1
 
3.2%
ValueCountFrequency (%)
9111.11 1
3.2%
3110.98 1
3.2%
2029.55 1
3.2%
1715.57 1
3.2%
1448.74 1
3.2%
916.52 1
3.2%
631.15 1
3.2%
504.23 1
3.2%
489.32 1
3.2%
471.49 1
3.2%

Interactions

2024-01-10T06:03:23.265367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:21.688058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:22.057903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:22.439249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:22.865259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:23.337769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:21.756836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:22.136189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:22.511369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:22.947132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:23.411800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:21.823374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:22.208235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:22.581393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:23.025272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:23.489889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:21.896388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:22.294740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:22.659690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:23.108549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:23.566557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:21.973314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:22.371473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:22.762893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:03:23.186997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:03:26.697998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.0000.000
과세년도0.0001.0000.0000.0000.3470.0000.0000.080
납세자유형0.0000.0001.0000.4800.0000.4190.2090.421
당해미환급건수0.0000.0000.4801.0000.9510.9280.9430.000
당해미환급금액0.0000.3470.0000.9511.0000.8980.8860.000
누적미환급건수0.0000.0000.4190.9280.8981.0000.9750.000
누적미환급금액0.0000.0000.2090.9430.8860.9751.0000.000
누적미환급금액증감0.0000.0800.4210.0000.0000.0000.0001.000
2024-01-10T06:03:26.805845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명납세자유형
과세년도1.0000.0000.000
세목명0.0001.0000.000
납세자유형0.0000.0001.000
2024-01-10T06:03:26.901659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도납세자유형
당해미환급건수1.0000.8410.9590.8820.0580.0000.0000.253
당해미환급금액0.8411.0000.8360.863-0.1880.0000.1350.117
누적미환급건수0.9590.8361.0000.9620.2340.0000.0000.267
누적미환급금액0.8820.8630.9621.0000.2490.0000.0000.190
누적미환급금액증감0.058-0.1880.2340.2491.0000.0000.0000.482
세목명0.0000.0000.0000.0000.0001.0000.0000.000
과세년도0.0000.1350.0000.0000.0000.0001.0000.000
납세자유형0.2530.1170.2670.1900.4820.0000.0001.000

Missing values

2024-01-10T06:03:23.672345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:03:23.836621image/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
0충청남도보령시44180자동차세2017신규개인385976001752579970331.72
1충청남도보령시44180자동차세2017신규법인221580253918001715.57
2충청남도보령시44180재산세2017신규개인73325028168260406.05
3충청남도보령시44180지방소득세2017신규개인2042356047918450116.84
4충청남도보령시44180자동차세2018신규개인657743702403354340333.17
5충청남도보령시44180자동차세2018신규법인58007030471870489.32
6충청남도보령시44180재산세2018신규개인113337039201630504.23
7충청남도보령시44180지방소득세2018신규개인45122851092214696074.76
8충청남도보령시44180지방소득세2018신규법인261026100.0
9충청남도보령시44180자동차세2019신규개인8711625203274516860288.54
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
21충청남도보령시44180지방소득세2020신규개인408513701663933670362.04
22충청남도보령시44180등록면허세2021신규개인43769010100760167.34
23충청남도보령시44180자동차세2021신규개인21621221705806291570196.47
24충청남도보령시44180자동차세2021신규법인68731042638370631.15
25충청남도보령시44180재산세2021신규개인454818101101179300144.76
26충청남도보령시44180재산세2021신규법인2574061843103110.98
27충청남도보령시44180주민세2021신규개인17203663209111.11
28충청남도보령시44180지방소득세2021신규개인12018072102584335720139.91
29충청남도보령시44180지방소득세2021신규법인136583033664400.17
30충청남도보령시44180취득세2021신규개인1218501218500.0