Overview

Dataset statistics

Number of variables12
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory108.3 B

Variable types

Categorical7
Numeric5

Dataset

Description경상남도 사천시 지방세 미환급 현황(2018 ~ 2020년)에 대한 데이터로 미환급 유형별 미환급금 현황 및 연간 누적률을 제공합니다.
Author경상남도 사천시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15079592

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
당해미환급건수 is highly overall correlated with 당해미환급금액High correlation
당해미환급금액 is highly overall correlated with 당해미환급건수 and 1 other fieldsHigh correlation
누적미환급건수 is highly overall correlated with 누적미환급금액 and 2 other fieldsHigh correlation
누적미환급금액 is highly overall correlated with 누적미환급건수 and 3 other fieldsHigh correlation
누적미환급금액증감 is highly overall correlated with 당해미환급금액 and 2 other fieldsHigh correlation
과세년도 is highly overall correlated with 누적미환급금액High correlation
납세자유형 is highly overall correlated with 누적미환급건수 and 1 other fieldsHigh correlation
당해미환급금액 has unique valuesUnique
누적미환급금액증감 has 2 (8.0%) zerosZeros

Reproduction

Analysis started2023-12-10 22:48:54.768630
Analysis finished2023-12-10 22:48:57.629734
Duration2.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
경상남도
25 

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 25
100.0%

Length

2023-12-11T07:48:57.688857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:48:57.777600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 25
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
사천시
25 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사천시 25
100.0%

Length

2023-12-11T07:48:57.865535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:48:57.950110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사천시 25
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
48240
25 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48240
2nd row48240
3rd row48240
4th row48240
5th row48240

Common Values

ValueCountFrequency (%)
48240 25
100.0%

Length

2023-12-11T07:48:58.037852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:48:58.112691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48240 25
100.0%

세목명
Categorical

Distinct4
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
자동차세
11 
지방소득세
10 
재산세
3 
등록면허세
 
1

Length

Max length5
Median length4
Mean length4.32
Min length3

Unique

Unique1 ?
Unique (%)4.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 11
44.0%
지방소득세 10
40.0%
재산세 3
 
12.0%
등록면허세 1
 
4.0%

Length

2023-12-11T07:48:58.418999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:48:58.509893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 11
44.0%
지방소득세 10
40.0%
재산세 3
 
12.0%
등록면허세 1
 
4.0%

과세년도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2020
9 
2018
8 
2019
8 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2020 9
36.0%
2018 8
32.0%
2019 8
32.0%

Length

2023-12-11T07:48:58.610950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:48:58.698865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 9
36.0%
2018 8
32.0%
2019 8
32.0%

미환급유형
Categorical

Distinct4
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
신규
15 
주소불명
5 
기타
3 
송달분 미수령
2 

Length

Max length7
Median length2
Mean length2.8
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신규 15
60.0%
주소불명 5
 
20.0%
기타 3
 
12.0%
송달분 미수령 2
 
8.0%

Length

2023-12-11T07:48:58.788481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:48:58.873015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 15
55.6%
주소불명 5
 
18.5%
기타 3
 
11.1%
송달분 2
 
7.4%
미수령 2
 
7.4%

납세자유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
개인
18 
법인
7 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 18
72.0%
법인 7
 
28.0%

Length

2023-12-11T07:48:58.958387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:48:59.032432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 18
72.0%
법인 7
 
28.0%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.92
Minimum1
Maximum115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T07:48:59.105085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median4
Q311
95-th percentile92.6
Maximum115
Range114
Interquartile range (IQR)10

Descriptive statistics

Standard deviation32.807418
Coefficient of variation (CV)1.6469587
Kurtosis2.6795529
Mean19.92
Median Absolute Deviation (MAD)3
Skewness1.9114735
Sum498
Variance1076.3267
MonotonicityNot monotonic
2023-12-11T07:48:59.199367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 7
28.0%
2 3
12.0%
4 3
12.0%
71 1
 
4.0%
10 1
 
4.0%
33 1
 
4.0%
115 1
 
4.0%
9 1
 
4.0%
46 1
 
4.0%
3 1
 
4.0%
Other values (5) 5
20.0%
ValueCountFrequency (%)
1 7
28.0%
2 3
12.0%
3 1
 
4.0%
4 3
12.0%
5 1
 
4.0%
7 1
 
4.0%
9 1
 
4.0%
10 1
 
4.0%
11 1
 
4.0%
33 1
 
4.0%
ValueCountFrequency (%)
115 1
4.0%
98 1
4.0%
71 1
4.0%
65 1
4.0%
46 1
4.0%
33 1
4.0%
11 1
4.0%
10 1
4.0%
9 1
4.0%
7 1
4.0%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean289056.4
Minimum1270
Maximum1891170
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T07:48:59.299788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1270
5-th percentile5196
Q115580
median58120
Q3417810
95-th percentile970106
Maximum1891170
Range1889900
Interquartile range (IQR)402230

Descriptive statistics

Standard deviation448589.3
Coefficient of variation (CV)1.5519093
Kurtosis5.9563099
Mean289056.4
Median Absolute Deviation (MAD)53040
Skewness2.2840406
Sum7226410
Variance2.0123236 × 1011
MonotonicityNot monotonic
2023-12-11T07:48:59.405372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
9300 1
 
4.0%
645390 1
 
4.0%
525890 1
 
4.0%
1891170 1
 
4.0%
174120 1
 
4.0%
9840 1
 
4.0%
54970 1
 
4.0%
128840 1
 
4.0%
8460 1
 
4.0%
984690 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1270 1
4.0%
5080 1
4.0%
5660 1
4.0%
8460 1
4.0%
9300 1
4.0%
9840 1
4.0%
15580 1
4.0%
15680 1
4.0%
27680 1
4.0%
30250 1
4.0%
ValueCountFrequency (%)
1891170 1
4.0%
984690 1
4.0%
911770 1
4.0%
695750 1
4.0%
645390 1
4.0%
525890 1
4.0%
417810 1
4.0%
316680 1
4.0%
174120 1
4.0%
149800 1
4.0%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.4
Minimum1
Maximum259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T07:48:59.506754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.2
Q112
median110
Q3157
95-th percentile254
Maximum259
Range258
Interquartile range (IQR)145

Descriptive statistics

Standard deviation86.965031
Coefficient of variation (CV)0.92123974
Kurtosis-0.79016345
Mean94.4
Median Absolute Deviation (MAD)93
Skewness0.61470655
Sum2360
Variance7562.9167
MonotonicityNot monotonic
2023-12-11T07:48:59.592682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
118 3
12.0%
110 3
12.0%
157 3
12.0%
6 2
 
8.0%
60 2
 
8.0%
234 2
 
8.0%
259 2
 
8.0%
12 1
 
4.0%
15 1
 
4.0%
4 1
 
4.0%
Other values (5) 5
20.0%
ValueCountFrequency (%)
1 1
4.0%
4 1
4.0%
5 1
4.0%
6 2
8.0%
10 1
4.0%
12 1
4.0%
15 1
4.0%
17 1
4.0%
23 1
4.0%
60 2
8.0%
ValueCountFrequency (%)
259 2
8.0%
234 2
8.0%
157 3
12.0%
118 3
12.0%
110 3
12.0%
60 2
8.0%
23 1
 
4.0%
17 1
 
4.0%
15 1
 
4.0%
12 1
 
4.0%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1166949.6
Minimum15680
Maximum3235730
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T07:48:59.676326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15680
5-th percentile44160
Q1149800
median1056380
Q31973810
95-th percentile3235730
Maximum3235730
Range3220050
Interquartile range (IQR)1824010

Descriptive statistics

Standard deviation1060060.8
Coefficient of variation (CV)0.90840321
Kurtosis-0.48549805
Mean1166949.6
Median Absolute Deviation (MAD)917430
Skewness0.74154374
Sum29173740
Variance1.1237288 × 1012
MonotonicityNot monotonic
2023-12-11T07:48:59.772422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1056380 3
12.0%
1522960 3
12.0%
3235730 3
12.0%
44160 2
 
8.0%
753510 2
 
8.0%
1973810 2
 
8.0%
2201710 2
 
8.0%
60310 1
 
4.0%
360840 1
 
4.0%
149800 1
 
4.0%
Other values (5) 5
20.0%
ValueCountFrequency (%)
15680 1
4.0%
44160 2
8.0%
60310 1
4.0%
88290 1
4.0%
115280 1
4.0%
149800 1
4.0%
360840 1
4.0%
464860 1
4.0%
527090 1
4.0%
753510 2
8.0%
ValueCountFrequency (%)
3235730 3
12.0%
2201710 2
8.0%
1973810 2
8.0%
1522960 3
12.0%
1056380 3
12.0%
753510 2
8.0%
527090 1
 
4.0%
464860 1
 
4.0%
360840 1
 
4.0%
149800 1
 
4.0%

누적미환급금액증감
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7337.0592
Minimum0
Maximum59231.5
Zeros2
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T07:48:59.859579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.046
Q145.98
median118.89
Q33716.4
95-th percentile34375.062
Maximum59231.5
Range59231.5
Interquartile range (IQR)3670.42

Descriptive statistics

Standard deviation14948.431
Coefficient of variation (CV)2.0373873
Kurtosis5.5928929
Mean7337.0592
Median Absolute Deviation (MAD)118.89
Skewness2.3998379
Sum183426.48
Variance2.2345559 × 108
MonotonicityNot monotonic
2023-12-11T07:48:59.965718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.0 2
 
8.0%
11258.92 1
 
4.0%
118.89 1
 
4.0%
0.23 1
 
4.0%
71.1 1
 
4.0%
1758.33 1
 
4.0%
32783.43 1
 
4.0%
109.71 1
 
4.0%
260.8 1
 
4.0%
25924.94 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
0.0 2
8.0%
0.23 1
4.0%
0.71 1
4.0%
9.77 1
4.0%
13.94 1
4.0%
45.98 1
4.0%
63.68 1
4.0%
71.1 1
4.0%
80.35 1
4.0%
109.71 1
4.0%
ValueCountFrequency (%)
59231.5 1
4.0%
34772.97 1
4.0%
32783.43 1
4.0%
25924.94 1
4.0%
11258.92 1
4.0%
9675.1 1
4.0%
3716.4 1
4.0%
2520.37 1
4.0%
1758.33 1
4.0%
769.29 1
4.0%

Interactions

2023-12-11T07:48:56.929669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:55.142741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:55.608717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:56.068396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:56.505136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:57.043970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:55.231361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:55.700250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:56.171435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:56.589015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:57.141624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:55.339180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:55.787304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:56.265979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:56.692575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:57.211849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:55.437019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:55.867241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:56.334074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:56.766320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:57.286369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:55.519840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:55.963098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:56.412614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:56.839669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:49:00.050435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.3800.7400.000
과세년도0.0001.0000.0000.0000.0600.0000.4730.7240.000
미환급유형0.0000.0001.0000.1340.0000.0000.3070.1650.528
납세자유형0.0000.0000.1341.0000.0000.0000.5880.7390.000
당해미환급건수0.0000.0600.0000.0001.0000.9860.5730.6260.000
당해미환급금액0.0000.0000.0000.0000.9861.0000.5780.6630.000
누적미환급건수0.3800.4730.3070.5880.5730.5781.0001.0000.783
누적미환급금액0.7400.7240.1650.7390.6260.6631.0001.0000.367
누적미환급금액증감0.0000.0000.5280.0000.0000.0000.7830.3671.000
2023-12-11T07:49:00.146048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도납세자유형미환급유형세목명
과세년도1.0000.0000.0000.000
납세자유형0.0001.0000.0460.000
미환급유형0.0000.0461.0000.000
세목명0.0000.0000.0001.000
2023-12-11T07:49:00.224627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도미환급유형납세자유형
당해미환급건수1.0000.9030.1170.112-0.4790.0000.0000.0000.000
당해미환급금액0.9031.0000.1190.220-0.5450.0000.0000.0000.000
누적미환급건수0.1170.1191.0000.9190.6560.2990.3790.2340.659
누적미환급금액0.1120.2200.9191.0000.5840.4270.5500.1290.654
누적미환급금액증감-0.479-0.5450.6560.5841.0000.0000.0000.4380.000
세목명0.0000.0000.2990.4270.0001.0000.0000.0000.000
과세년도0.0000.0000.3790.5500.0000.0001.0000.0000.000
미환급유형0.0000.0000.2340.1290.4380.0000.0001.0000.046
납세자유형0.0000.0000.6590.6540.0000.0000.0000.0461.000

Missing values

2023-12-11T07:48:57.398730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:48:57.566070image/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
0경상남도사천시48240자동차세2018기타개인29300118105638011258.92
1경상남도사천시48240자동차세2018신규개인71645390118105638063.68
2경상남도사천시48240자동차세2018주소불명개인12768011810563803716.4
3경상남도사천시48240자동차세2018신규법인43025064416045.98
4경상남도사천시48240자동차세2018주소불명법인15080644160769.29
5경상남도사천시48240재산세2018신규개인105494012603109.77
6경상남도사천시48240지방소득세2018기타개인112706075351059231.5
7경상남도사천시48240지방소득세2018신규개인334178106075351080.35
8경상남도사천시48240자동차세2019신규개인1159117702341973810116.48
9경상남도사천시48240자동차세2019주소불명개인15660234197381034772.97
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
15경상남도사천시48240지방소득세2019신규법인3876705882900.71
16경상남도사천시48240등록면허세2020신규개인1156801156800.0
17경상남도사천시48240자동차세2020신규개인989846902592201710123.59
18경상남도사천시48240자동차세2020주소불명개인18460259220171025924.94
19경상남도사천시48240자동차세2020신규법인1112884023464860260.8
20경상남도사천시48240재산세2020신규개인55497017115280109.71
21경상남도사천시48240지방소득세2020기타개인19840157323573032783.43
22경상남도사천시48240지방소득세2020송달분 미수령개인417412015732357301758.33
23경상남도사천시48240지방소득세2020신규개인651891170157323573071.1
24경상남도사천시48240지방소득세2020신규법인7525890105270900.23