Overview

Dataset statistics

Number of variables12
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory107.0 B

Variable types

Categorical7
Numeric5

Dataset

Description지방세 개방형 데이터 구축자료중 2017년~2021년도에 대한 경상남도 진주시 지방세 미환급현황에 대한 자료제공입니다.
Author경상남도 진주시
URLhttps://www.data.go.kr/data/15080410/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 (67.0%)Imbalance
당해미환급금액 has unique valuesUnique
누적미환급금액증감 has 5 (15.2%) zerosZeros

Reproduction

Analysis started2024-04-06 08:12:30.237709
Analysis finished2024-04-06 08:12:37.375041
Duration7.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
경상남도
33 

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 33
100.0%

Length

2024-04-06T17:12:37.495428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:12:37.775575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 33
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
진주시
33 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진주시 33
100.0%

Length

2024-04-06T17:12:38.059663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:12:38.236203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진주시 33
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
48170
33 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48170
2nd row48170
3rd row48170
4th row48170
5th row48170

Common Values

ValueCountFrequency (%)
48170 33
100.0%

Length

2024-04-06T17:12:38.426141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:12:38.611868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48170 33
100.0%

세목명
Categorical

Distinct6
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size396.0 B
자동차세
11 
지방소득세
11 
재산세
4 
주민세
4 
등록면허세
2 

Length

Max length5
Median length4
Mean length4.1212121
Min length3

Unique

Unique1 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 11
33.3%
지방소득세 11
33.3%
재산세 4
 
12.1%
주민세 4
 
12.1%
등록면허세 2
 
6.1%
취득세 1
 
3.0%

Length

2024-04-06T17:12:38.827604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:12:39.070338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 11
33.3%
지방소득세 11
33.3%
재산세 4
 
12.1%
주민세 4
 
12.1%
등록면허세 2
 
6.1%
취득세 1
 
3.0%

과세년도
Categorical

Distinct5
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size396.0 B
2019
8 
2021
8 
2017
7 
2018
5 
2020
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 (%)
2019 8
24.2%
2021 8
24.2%
2017 7
21.2%
2018 5
15.2%
2020 5
15.2%

Length

2024-04-06T17:12:39.327481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:12:39.668298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 8
24.2%
2021 8
24.2%
2017 7
21.2%
2018 5
15.2%
2020 5
15.2%

미환급유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
신규
31 
폐업 또는 부도
 
2

Length

Max length8
Median length2
Mean length2.3636364
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신규 31
93.9%
폐업 또는 부도 2
 
6.1%

Length

2024-04-06T17:12:39.913545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:12:40.180818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 31
83.8%
폐업 2
 
5.4%
또는 2
 
5.4%
부도 2
 
5.4%

납세자유형
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
개인
18 
법인
15 

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 18
54.5%
법인 15
45.5%

Length

2024-04-06T17:12:40.468330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:12:40.639602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 18
54.5%
법인 15
45.5%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.393939
Minimum1
Maximum510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-06T17:12:40.831341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median10
Q387
95-th percentile391
Maximum510
Range509
Interquartile range (IQR)85

Descriptive statistics

Standard deviation133.24412
Coefficient of variation (CV)1.7910615
Kurtosis4.3224552
Mean74.393939
Median Absolute Deviation (MAD)9
Skewness2.2266552
Sum2455
Variance17753.996
MonotonicityNot monotonic
2024-04-06T17:12:41.075820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 6
18.2%
2 3
 
9.1%
8 3
 
9.1%
97 1
 
3.0%
451 1
 
3.0%
11 1
 
3.0%
351 1
 
3.0%
37 1
 
3.0%
510 1
 
3.0%
4 1
 
3.0%
Other values (14) 14
42.4%
ValueCountFrequency (%)
1 6
18.2%
2 3
9.1%
4 1
 
3.0%
5 1
 
3.0%
6 1
 
3.0%
7 1
 
3.0%
8 3
9.1%
10 1
 
3.0%
11 1
 
3.0%
12 1
 
3.0%
ValueCountFrequency (%)
510 1
3.0%
451 1
3.0%
351 1
3.0%
251 1
3.0%
205 1
3.0%
137 1
3.0%
132 1
3.0%
97 1
3.0%
87 1
3.0%
53 1
3.0%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean802565.76
Minimum150
Maximum4525180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-06T17:12:41.346740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150
5-th percentile1022
Q112180
median139200
Q31184380
95-th percentile3515752
Maximum4525180
Range4525030
Interquartile range (IQR)1172200

Descriptive statistics

Standard deviation1246831.2
Coefficient of variation (CV)1.5535564
Kurtosis2.4444337
Mean802565.76
Median Absolute Deviation (MAD)137930
Skewness1.7934148
Sum26484670
Variance1.554588 × 1012
MonotonicityNot monotonic
2024-04-06T17:12:41.626180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
680270 1
 
3.0%
25600 1
 
3.0%
3330 1
 
3.0%
4101280 1
 
3.0%
240060 1
 
3.0%
12180 1
 
3.0%
3125400 1
 
3.0%
6070 1
 
3.0%
7200 1
 
3.0%
139200 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
150 1
3.0%
650 1
3.0%
1270 1
3.0%
1800 1
3.0%
3330 1
3.0%
5560 1
3.0%
6070 1
3.0%
7200 1
3.0%
12180 1
3.0%
13660 1
3.0%
ValueCountFrequency (%)
4525180 1
3.0%
4101280 1
3.0%
3125400 1
3.0%
2688590 1
3.0%
2490040 1
3.0%
1869540 1
3.0%
1433860 1
3.0%
1198040 1
3.0%
1184380 1
3.0%
832680 1
3.0%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157.63636
Minimum1
Maximum1233
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-06T17:12:41.874947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q110
median25
Q3162
95-th percentile754.6
Maximum1233
Range1232
Interquartile range (IQR)152

Descriptive statistics

Standard deviation282.31718
Coefficient of variation (CV)1.7909394
Kurtosis6.3274841
Mean157.63636
Median Absolute Deviation (MAD)23
Skewness2.473631
Sum5202
Variance79702.989
MonotonicityNot monotonic
2024-04-06T17:12:42.631568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 3
 
9.1%
10 3
 
9.1%
2 2
 
6.1%
4 2
 
6.1%
40 2
 
6.1%
22 2
 
6.1%
45 1
 
3.0%
25 1
 
3.0%
747 1
 
3.0%
55 1
 
3.0%
Other values (15) 15
45.5%
ValueCountFrequency (%)
1 3
9.1%
2 2
6.1%
4 2
6.1%
10 3
9.1%
11 1
 
3.0%
12 1
 
3.0%
14 1
 
3.0%
18 1
 
3.0%
22 2
6.1%
25 1
 
3.0%
ValueCountFrequency (%)
1233 1
3.0%
766 1
3.0%
747 1
3.0%
499 1
3.0%
406 1
3.0%
334 1
3.0%
294 1
3.0%
197 1
3.0%
162 1
3.0%
110 1
3.0%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1826969.1
Minimum150
Maximum11079940
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-06T17:12:42.864200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150
5-th percentile4758
Q143800
median658780
Q31827850
95-th percentile7278978
Maximum11079940
Range11079790
Interquartile range (IQR)1784050

Descriptive statistics

Standard deviation2687058.6
Coefficient of variation (CV)1.470774
Kurtosis3.7869473
Mean1826969.1
Median Absolute Deviation (MAD)636640
Skewness2.0079207
Sum60289980
Variance7.2202839 × 1012
MonotonicityNot monotonic
2024-04-06T17:12:43.092188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1295420 2
 
6.1%
658780 2
 
6.1%
1220440 1
 
3.0%
7200 1
 
3.0%
502670 1
 
3.0%
124300 1
 
3.0%
5264050 1
 
3.0%
43800 1
 
3.0%
25600 1
 
3.0%
552590 1
 
3.0%
Other values (21) 21
63.6%
ValueCountFrequency (%)
150 1
3.0%
3330 1
3.0%
5710 1
3.0%
7200 1
3.0%
18030 1
3.0%
25600 1
3.0%
26080 1
3.0%
39740 1
3.0%
43800 1
3.0%
97670 1
3.0%
ValueCountFrequency (%)
11079940 1
3.0%
7869900 1
3.0%
6885030 1
3.0%
5264050 1
3.0%
5144340 1
3.0%
4895430 1
3.0%
3025890 1
3.0%
2654300 1
3.0%
1827850 1
3.0%
1336420 1
3.0%

누적미환급금액증감
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10472.145
Minimum0
Maximum199195.38
Zeros5
Zeros (%)15.2%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-06T17:12:43.333486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q126.61
median85.12
Q3192.71
95-th percentile62699.962
Maximum199195.38
Range199195.38
Interquartile range (IQR)166.1

Descriptive statistics

Standard deviation38652.858
Coefficient of variation (CV)3.6910161
Kurtosis19.321257
Mean10472.145
Median Absolute Deviation (MAD)78.92
Skewness4.3052845
Sum345580.8
Variance1.4940434 × 109
MonotonicityNot monotonic
2024-04-06T17:12:43.583145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 5
 
15.2%
79.41 1
 
3.0%
161.85 1
 
3.0%
6.2 1
 
3.0%
192.71 1
 
3.0%
22.64 1
 
3.0%
26.61 1
 
3.0%
873.73 1
 
3.0%
144.85 1
 
3.0%
621.58 1
 
3.0%
Other values (19) 19
57.6%
ValueCountFrequency (%)
0.0 5
15.2%
2.7 1
 
3.0%
6.2 1
 
3.0%
22.64 1
 
3.0%
26.61 1
 
3.0%
34.99 1
 
3.0%
54.33 1
 
3.0%
55.57 1
 
3.0%
67.88 1
 
3.0%
68.43 1
 
3.0%
ValueCountFrequency (%)
199195.38 1
3.0%
102001.57 1
3.0%
36498.89 1
3.0%
3263.76 1
3.0%
920.53 1
3.0%
873.73 1
3.0%
621.58 1
3.0%
455.15 1
3.0%
192.71 1
3.0%
190.92 1
3.0%

Interactions

2024-04-06T17:12:35.896504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:31.461234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:32.585725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:33.954977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:34.988072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:36.147192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:31.686594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:32.852580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:34.102387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:35.199101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:36.303151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:31.829466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:33.100124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:34.242916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:35.361173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:36.469826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:32.055417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:33.380228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:34.384932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:35.505458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:36.632100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:32.243533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:33.685988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:34.651230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:35.665874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:12:43.771476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.0000.0000.000
과세년도0.0001.0000.0000.0000.0780.1400.0000.5200.248
미환급유형0.0000.0001.0000.0000.0000.0000.0000.0000.859
납세자유형0.0000.0000.0001.0000.4380.4580.3730.2910.269
당해미환급건수0.0000.0780.0000.4381.0000.8970.9910.9870.000
당해미환급금액0.0000.1400.0000.4580.8971.0000.8860.8300.000
누적미환급건수0.0000.0000.0000.3730.9910.8861.0000.9570.000
누적미환급금액0.0000.5200.0000.2910.9870.8300.9571.0000.000
누적미환급금액증감0.0000.2480.8590.2690.0000.0000.0000.0001.000
2024-04-06T17:12:43.994218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미환급유형과세년도세목명납세자유형
미환급유형1.0000.0000.0000.000
과세년도0.0001.0000.0000.000
세목명0.0000.0001.0000.000
납세자유형0.0000.0000.0001.000
2024-04-06T17:12:44.173184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도미환급유형납세자유형
당해미환급건수1.0000.8750.9290.7910.2240.0000.0000.0000.425
당해미환급금액0.8751.0000.8400.769-0.0320.0000.0000.0000.326
누적미환급건수0.9290.8401.0000.8710.3870.0000.0000.0000.359
누적미환급금액0.7910.7690.8711.0000.4590.0000.3270.0000.294
누적미환급금액증감0.224-0.0320.3870.4591.0000.0000.1910.6360.165
세목명0.0000.0000.0000.0000.0001.0000.0000.0000.000
과세년도0.0000.0000.0000.3270.1910.0001.0000.0000.000
미환급유형0.0000.0000.0000.0000.6360.0000.0001.0000.000
납세자유형0.4250.3260.3590.2940.1650.0000.0000.0001.000

Missing values

2024-04-06T17:12:36.878305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:12:37.249742image/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
0경상남도진주시48170자동차세2017신규개인97680270162122044079.41
1경상남도진주시48170자동차세2017신규법인1213920022289660108.09
2경상남도진주시48170재산세2017신규개인21932042608034.99
3경상남도진주시48170주민세2017신규법인115011500.0
4경상남도진주시48170지방소득세2017신규개인531184380110182785054.33
5경상남도진주시48170지방소득세2017신규법인5650101295420199195.38
6경상남도진주시48170지방소득세2017폐업 또는 부도법인183268010129542055.57
7경상남도진주시48170자동차세2018신규개인1321433860294265430085.12
8경상남도진주시48170자동차세2018신규법인173673204065878079.35
9경상남도진주시48170자동차세2018폐업 또는 부도법인118004065878036498.89
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
23경상남도진주시48170지방소득세2020신규개인2513125400406526405068.43
24경상남도진주시48170지방소득세2020신규법인660701443800621.58
25경상남도진주시48170등록면허세2021신규개인4256004256000.0
26경상남도진주시48170등록면허세2021신규법인17200172000.0
27경상남도진주시48170자동차세2021신규개인5104525180123311079940144.85
28경상남도진주시48170자동차세2021신규법인85675052552590873.73
29경상남도진주시48170재산세2021신규개인374671705559147026.61
30경상남도진주시48170주민세2021신규개인879640109767022.64
31경상남도진주시48170지방소득세2021신규개인35126885907477869900192.71
32경상남도진주시48170지방소득세2021신규법인11705980257497806.2