Overview

Dataset statistics

Number of variables12
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory106.2 B

Variable types

Categorical7
Numeric5

Dataset

Description미환급 유형별 미환급금 현황 및 연간 누적률에 대한 데이터로 시도명, 시군구명, 자치단체코드, 세목명, 과세년도, 미환급유형, 납세자유형, 당해미환급건수 등의 항목을 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15079613

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 7 (17.1%) zerosZeros

Reproduction

Analysis started2023-12-11 00:29:32.902721
Analysis finished2023-12-11 00:29:35.707047
Duration2.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
경상남도
41 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 41
100.0%

Length

2023-12-11T09:29:35.776659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:29:35.882234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 41
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
김해시
41 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
김해시 41
100.0%

Length

2023-12-11T09:29:35.992526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:29:36.097208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김해시 41
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
48250
41 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48250
2nd row48250
3rd row48250
4th row48250
5th row48250

Common Values

ValueCountFrequency (%)
48250 41
100.0%

Length

2023-12-11T09:29:36.202791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:29:36.294203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48250 41
100.0%

세목명
Categorical

Distinct6
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
자동차세
10 
지방소득세
10 
재산세
8 
등록면허세
5 
주민세
5 

Length

Max length5
Median length4
Mean length3.9756098
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 10
24.4%
지방소득세 10
24.4%
재산세 8
19.5%
등록면허세 5
12.2%
주민세 5
12.2%
취득세 3
 
7.3%

Length

2023-12-11T09:29:36.406124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:29:36.520694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 10
24.4%
지방소득세 10
24.4%
재산세 8
19.5%
등록면허세 5
12.2%
주민세 5
12.2%
취득세 3
 
7.3%

과세년도
Categorical

Distinct5
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size460.0 B
2021
10 
2019
9 
2020
9 
2018
8 
2017
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 10
24.4%
2019 9
22.0%
2020 9
22.0%
2018 8
19.5%
2017 5
12.2%

Length

2023-12-11T09:29:36.644436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:29:36.769392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 10
24.4%
2019 9
22.0%
2020 9
22.0%
2018 8
19.5%
2017 5
12.2%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
신규
41 

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 41
100.0%

Length

2023-12-11T09:29:36.879586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:29:36.989293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 41
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
개인
24 
법인
17 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 24
58.5%
법인 17
41.5%

Length

2023-12-11T09:29:37.103204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:29:37.218558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 24
58.5%
법인 17
41.5%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean152.70732
Minimum1
Maximum990
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-11T09:29:37.339302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median24
Q3104
95-th percentile790
Maximum990
Range989
Interquartile range (IQR)101

Descriptive statistics

Standard deviation271.33275
Coefficient of variation (CV)1.7768157
Kurtosis2.6352873
Mean152.70732
Median Absolute Deviation (MAD)23
Skewness1.9704025
Sum6261
Variance73621.462
MonotonicityNot monotonic
2023-12-11T09:29:37.459228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 5
 
12.2%
3 4
 
9.8%
2 3
 
7.3%
4 3
 
7.3%
15 2
 
4.9%
790 2
 
4.9%
257 1
 
2.4%
35 1
 
2.4%
31 1
 
2.4%
47 1
 
2.4%
Other values (18) 18
43.9%
ValueCountFrequency (%)
1 5
12.2%
2 3
7.3%
3 4
9.8%
4 3
7.3%
6 1
 
2.4%
11 1
 
2.4%
13 1
 
2.4%
15 2
 
4.9%
24 1
 
2.4%
31 1
 
2.4%
ValueCountFrequency (%)
990 1
2.4%
790 2
4.9%
783 1
2.4%
691 1
2.4%
528 1
2.4%
363 1
2.4%
257 1
2.4%
194 1
2.4%
152 1
2.4%
104 1
2.4%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3365573.9
Minimum10
Maximum30004990
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-11T09:29:37.577815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile8070
Q148770
median726390
Q32524690
95-th percentile17411840
Maximum30004990
Range30004980
Interquartile range (IQR)2475920

Descriptive statistics

Standard deviation6380969.9
Coefficient of variation (CV)1.895953
Kurtosis7.8296223
Mean3365573.9
Median Absolute Deviation (MAD)708530
Skewness2.7415367
Sum1.3798853 × 108
Variance4.0716777 × 1013
MonotonicityNot monotonic
2023-12-11T09:29:37.723600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
2146500 1
 
2.4%
64400 1
 
2.4%
32340 1
 
2.4%
11969080 1
 
2.4%
1273640 1
 
2.4%
17860 1
 
2.4%
2500430 1
 
2.4%
286890 1
 
2.4%
30004990 1
 
2.4%
4986830 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
10 1
2.4%
6370 1
2.4%
8070 1
2.4%
9290 1
2.4%
17860 1
2.4%
21290 1
2.4%
32340 1
2.4%
32460 1
2.4%
38520 1
2.4%
48350 1
2.4%
ValueCountFrequency (%)
30004990 1
2.4%
19336800 1
2.4%
17411840 1
2.4%
14623530 1
2.4%
11969080 1
2.4%
6364920 1
2.4%
6039860 1
2.4%
4986830 1
2.4%
3616810 1
2.4%
2734490 1
2.4%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean310.90244
Minimum1
Maximum2297
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-11T09:29:37.834400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median55
Q3246
95-th percentile1449
Maximum2297
Range2296
Interquartile range (IQR)241

Descriptive statistics

Standard deviation571.31925
Coefficient of variation (CV)1.8376159
Kurtosis4.4011022
Mean310.90244
Median Absolute Deviation (MAD)52
Skewness2.2574606
Sum12747
Variance326405.69
MonotonicityNot monotonic
2023-12-11T09:29:37.942808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 3
 
7.3%
2 3
 
7.3%
4 2
 
4.9%
3 2
 
4.9%
51 2
 
4.9%
70 1
 
2.4%
45 1
 
2.4%
1405 1
 
2.4%
162 1
 
2.4%
43 1
 
2.4%
Other values (24) 24
58.5%
ValueCountFrequency (%)
1 3
7.3%
2 3
7.3%
3 2
4.9%
4 2
4.9%
5 1
 
2.4%
8 1
 
2.4%
15 1
 
2.4%
16 1
 
2.4%
21 1
 
2.4%
31 1
 
2.4%
ValueCountFrequency (%)
2297 1
2.4%
2001 1
2.4%
1449 1
2.4%
1405 1
2.4%
1256 1
2.4%
955 1
2.4%
758 1
2.4%
427 1
2.4%
395 1
2.4%
275 1
2.4%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6351769
Minimum10
Maximum58979180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-11T09:29:38.064779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile18980
Q1238860
median1878270
Q35148000
95-th percentile36470470
Maximum58979180
Range58979170
Interquartile range (IQR)4909140

Descriptive statistics

Standard deviation12490389
Coefficient of variation (CV)1.9664425
Kurtosis9.0791753
Mean6351769
Median Absolute Deviation (MAD)1688180
Skewness2.9817333
Sum2.6042253 × 108
Variance1.5600981 × 1014
MonotonicityNot monotonic
2023-12-11T09:29:38.443314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
3313880 1
 
2.4%
1193410 1
 
2.4%
190760 1
 
2.4%
18234430 1
 
2.4%
3126880 1
 
2.4%
551670 1
 
2.4%
2504030 1
 
2.4%
286890 1
 
2.4%
42671360 1
 
2.4%
5267430 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
10 1
2.4%
6370 1
2.4%
18980 1
2.4%
32470 1
2.4%
48350 1
2.4%
91910 1
2.4%
158420 1
2.4%
190090 1
2.4%
190760 1
2.4%
194670 1
2.4%
ValueCountFrequency (%)
58979180 1
2.4%
42671360 1
2.4%
36470470 1
2.4%
20235740 1
2.4%
18234430 1
2.4%
13295610 1
2.4%
11084520 1
2.4%
6930690 1
2.4%
5612210 1
2.4%
5267430 1
2.4%

누적미환급금액증감
Real number (ℝ)

ZEROS 

Distinct35
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1173.7612
Minimum0
Maximum24853.28
Zeros7
Zeros (%)17.1%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-11T09:29:38.559221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.63
median55.47
Q3158.58
95-th percentile6129.39
Maximum24853.28
Range24853.28
Interquartile range (IQR)152.95

Descriptive statistics

Standard deviation4183.927
Coefficient of variation (CV)3.5645469
Kurtosis27.067301
Mean1173.7612
Median Absolute Deviation (MAD)55.44
Skewness4.9944929
Sum48124.21
Variance17505245
MonotonicityNot monotonic
2023-12-11T09:29:38.679643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0.0 7
 
17.1%
54.39 1
 
2.4%
88.61 1
 
2.4%
145.51 1
 
2.4%
2988.86 1
 
2.4%
0.14 1
 
2.4%
42.21 1
 
2.4%
5.63 1
 
2.4%
1753.12 1
 
2.4%
128.24 1
 
2.4%
Other values (25) 25
61.0%
ValueCountFrequency (%)
0.0 7
17.1%
0.03 1
 
2.4%
0.14 1
 
2.4%
4.17 1
 
2.4%
5.63 1
 
2.4%
6.42 1
 
2.4%
10.8 1
 
2.4%
22.47 1
 
2.4%
33.36 1
 
2.4%
33.62 1
 
2.4%
ValueCountFrequency (%)
24853.28 1
2.4%
9420.67 1
2.4%
6129.39 1
2.4%
2988.86 1
2.4%
1753.12 1
2.4%
489.86 1
2.4%
389.77 1
2.4%
259.72 1
2.4%
238.73 1
2.4%
186.57 1
2.4%

Interactions

2023-12-11T09:29:34.980420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:33.257730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:33.671319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:34.091840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:34.511661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:35.060007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:33.333400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:33.747243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:34.181837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:34.603725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:35.142782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:33.415373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:33.835839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:34.268992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:34.685650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:35.231245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:33.494229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:33.925575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:34.352025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:34.782871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:35.331009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:33.587447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:34.011636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:34.439553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:34.886022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:29:38.757349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.0000.484
과세년도0.0001.0000.0000.1380.0000.0000.0000.000
납세자유형0.0000.0001.0000.1600.0000.0870.0000.000
당해미환급건수0.0000.1380.1601.0000.9630.9910.8950.000
당해미환급금액0.0000.0000.0000.9631.0000.9900.9570.000
누적미환급건수0.0000.0000.0870.9910.9901.0000.9460.000
누적미환급금액0.0000.0000.0000.8950.9570.9461.0000.000
누적미환급금액증감0.4840.0000.0000.0000.0000.0000.0001.000
2023-12-11T09:29:38.858683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형세목명과세년도
납세자유형1.0000.0000.000
세목명0.0001.0000.000
과세년도0.0000.0001.000
2023-12-11T09:29:38.944628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도납세자유형
당해미환급건수1.0000.8430.9360.7370.1000.0000.0430.089
당해미환급금액0.8431.0000.8010.856-0.0640.0000.0000.000
누적미환급건수0.9360.8011.0000.8110.3060.0000.0000.000
누적미환급금액0.7370.8560.8111.0000.3470.0000.0000.000
누적미환급금액증감0.100-0.0640.3060.3471.0000.3450.0000.000
세목명0.0000.0000.0000.0000.3451.0000.0000.000
과세년도0.0430.0000.0000.0000.0000.0001.0000.000
납세자유형0.0890.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-11T09:29:35.471900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:29:35.648070image/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
0경상남도김해시48250자동차세2017신규개인2572146500395331388054.39
1경상남도김해시48250자동차세2017신규법인3874092065115188055.47
2경상남도김해시48250재산세2017신규개인13178620161900906.42
3경상남도김해시48250지방소득세2017신규개인1942734490275365378033.62
4경상남도김해시48250지방소득세2017신규법인1192901518980104.31
5경상남도김해시48250등록면허세2018신규개인3483503483500.0
6경상남도김해시48250자동차세2018신규개인3633616810758693069091.62
7경상남도김해시48250자동차세2018신규법인407263901051878270158.58
8경상남도김해시48250재산세2018신규개인154877031238860389.77
9경상남도김해시48250재산세2018신규법인1101100.0
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
31경상남도김해시48250등록면허세2021신규개인2644008411934101753.12
32경상남도김해시48250자동차세2021신규개인9901933680022973647047088.61
33경상남도김해시48250자동차세2021신규법인10422554802465148000128.24
34경상남도김해시48250재산세2021신규개인4769700089119270071.12
35경상남도김해시48250재산세2021신규법인2919102919100.0
36경상남도김해시48250주민세2021신규개인2385205123995606129.39
37경상남도김해시48250주민세2021신규법인41104608397350259.72
38경상남도김해시48250지방소득세2021신규개인79017411840200158979180238.73
39경상남도김해시48250지방소득세2021신규법인316039860701108452083.52
40경상남도김해시48250취득세2021신규개인121290220269509420.67