Overview

Dataset statistics

Number of variables12
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory107.1 B

Variable types

Categorical7
Numeric5

Dataset

Description지방세 미환급 현황 및 연간 누적 현황 제공
Author경상남도 창원시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15078695

Alerts

시도명 has constant value ""Constant
과세년도 has constant value ""Constant
자치단체코드 is highly overall correlated with 시군구명High correlation
시군구명 is highly overall correlated with 자치단체코드High correlation
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 3 other fieldsHigh correlation
세목명 is highly overall correlated with 누적미환급건수 and 1 other fieldsHigh correlation
미환급유형 is highly imbalanced (65.8%)Imbalance
당해미환급금액 has unique valuesUnique
누적미환급금액증감 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:23:36.485508
Analysis finished2023-12-11 00:23:38.983255
Duration2.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
창원시
32 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
창원시 32
100.0%

Length

2023-12-11T09:23:39.033101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:23:39.109441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
창원시 32
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
진해구
9 
의창구
7 
마산회원구
7 
성산구
5 
마산합포구
4 

Length

Max length5
Median length3
Mean length3.6875
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의창구
2nd row마산회원구
3rd row진해구
4th row의창구
5th row성산구

Common Values

ValueCountFrequency (%)
진해구 9
28.1%
의창구 7
21.9%
마산회원구 7
21.9%
성산구 5
15.6%
마산합포구 4
12.5%

Length

2023-12-11T09:23:39.191952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:23:39.280286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진해구 9
28.1%
의창구 7
21.9%
마산회원구 7
21.9%
성산구 5
15.6%
마산합포구 4
12.5%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
48129
9 
48121
7 
48127
7 
48123
5 
48125
4 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48121
2nd row48127
3rd row48129
4th row48121
5th row48123

Common Values

ValueCountFrequency (%)
48129 9
28.1%
48121 7
21.9%
48127 7
21.9%
48123 5
15.6%
48125 4
12.5%

Length

2023-12-11T09:23:39.368585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:23:39.448149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48129 9
28.1%
48121 7
21.9%
48127 7
21.9%
48123 5
15.6%
48125 4
12.5%

세목명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
지방소득세
12 
자동차세
9 
재산세
5 
등록면허세
3 
주민세
3 

Length

Max length5
Median length4
Mean length4.21875
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 12
37.5%
자동차세 9
28.1%
재산세 5
15.6%
등록면허세 3
 
9.4%
주민세 3
 
9.4%

Length

2023-12-11T09:23:39.549433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:23:39.640364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 12
37.5%
자동차세 9
28.1%
재산세 5
15.6%
등록면허세 3
 
9.4%
주민세 3
 
9.4%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
2020
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 32
100.0%

Length

2023-12-11T09:23:39.956409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:23:40.026065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 32
100.0%

미환급유형
Categorical

IMBALANCE 

Distinct5
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
신규
28 
기타
 
1
국외이주
 
1
송달분 미수령
 
1
주소불명
 
1

Length

Max length7
Median length2
Mean length2.28125
Min length2

Unique

Unique4 ?
Unique (%)12.5%

Sample

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

Common Values

ValueCountFrequency (%)
신규 28
87.5%
기타 1
 
3.1%
국외이주 1
 
3.1%
송달분 미수령 1
 
3.1%
주소불명 1
 
3.1%

Length

2023-12-11T09:23:40.108157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:23:40.189214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 28
84.8%
기타 1
 
3.0%
국외이주 1
 
3.0%
송달분 1
 
3.0%
미수령 1
 
3.0%
주소불명 1
 
3.0%

납세자유형
Categorical

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
개인
23 
법인
9 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 23
71.9%
법인 9
 
28.1%

Length

2023-12-11T09:23:40.279794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:23:40.360047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 23
71.9%
법인 9
 
28.1%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.84375
Minimum1
Maximum321
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T09:23:40.452532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median6.5
Q380.5
95-th percentile260.45
Maximum321
Range320
Interquartile range (IQR)78.5

Descriptive statistics

Standard deviation87.981343
Coefficient of variation (CV)1.6042182
Kurtosis2.5943978
Mean54.84375
Median Absolute Deviation (MAD)5.5
Skewness1.8443371
Sum1755
Variance7740.7167
MonotonicityNot monotonic
2023-12-11T09:23:40.548901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 7
21.9%
4 3
 
9.4%
2 2
 
6.2%
103 2
 
6.2%
3 2
 
6.2%
8 1
 
3.1%
16 1
 
3.1%
9 1
 
3.1%
105 1
 
3.1%
54 1
 
3.1%
Other values (11) 11
34.4%
ValueCountFrequency (%)
1 7
21.9%
2 2
 
6.2%
3 2
 
6.2%
4 3
9.4%
5 1
 
3.1%
6 1
 
3.1%
7 1
 
3.1%
8 1
 
3.1%
9 1
 
3.1%
16 1
 
3.1%
ValueCountFrequency (%)
321 1
3.1%
261 1
3.1%
260 1
3.1%
172 1
3.1%
155 1
3.1%
105 1
3.1%
103 2
6.2%
73 1
3.1%
54 1
3.1%
49 1
3.1%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean931864.69
Minimum270
Maximum9113950
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T09:23:40.643792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum270
5-th percentile1722.5
Q111930
median229330
Q3840940
95-th percentile3375852.5
Maximum9113950
Range9113680
Interquartile range (IQR)829010

Descriptive statistics

Standard deviation1818228.5
Coefficient of variation (CV)1.9511723
Kurtosis13.390057
Mean931864.69
Median Absolute Deviation (MAD)221225
Skewness3.3765631
Sum29819670
Variance3.305955 × 1012
MonotonicityNot monotonic
2023-12-11T09:23:40.739371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
270 1
 
3.1%
12870 1
 
3.1%
684840 1
 
3.1%
1640 1
 
3.1%
9750 1
 
3.1%
219590 1
 
3.1%
287250 1
 
3.1%
1953970 1
 
3.1%
411320 1
 
3.1%
239070 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
270 1
3.1%
1640 1
3.1%
1790 1
3.1%
2290 1
3.1%
7200 1
3.1%
9010 1
3.1%
9750 1
3.1%
11330 1
3.1%
12130 1
3.1%
12870 1
3.1%
ValueCountFrequency (%)
9113950 1
3.1%
4454870 1
3.1%
2493020 1
3.1%
2398250 1
3.1%
2288240 1
3.1%
1953970 1
3.1%
1776940 1
3.1%
1115230 1
3.1%
749510 1
3.1%
684840 1
3.1%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean758.28125
Minimum4
Maximum2071
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T09:23:40.829098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4
Q125
median171
Q31594
95-th percentile2071
Maximum2071
Range2067
Interquartile range (IQR)1569

Descriptive statistics

Standard deviation870.97829
Coefficient of variation (CV)1.1486217
Kurtosis-1.7184611
Mean758.28125
Median Absolute Deviation (MAD)165
Skewness0.48883394
Sum24265
Variance758603.18
MonotonicityNot monotonic
2023-12-11T09:23:40.913863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1594 8
25.0%
2071 5
15.6%
171 4
12.5%
25 4
12.5%
78 4
12.5%
4 3
 
9.4%
14 3
 
9.4%
8 1
 
3.1%
ValueCountFrequency (%)
4 3
 
9.4%
8 1
 
3.1%
14 3
 
9.4%
25 4
12.5%
78 4
12.5%
171 4
12.5%
1594 8
25.0%
2071 5
15.6%
ValueCountFrequency (%)
2071 5
15.6%
1594 8
25.0%
171 4
12.5%
78 4
12.5%
25 4
12.5%
14 3
 
9.4%
8 1
 
3.1%
4 3
 
9.4%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11371397
Minimum19890
Maximum32891280
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T09:23:40.990658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19890
5-th percentile19890
Q1211650
median2357920
Q320595022
95-th percentile32891280
Maximum32891280
Range32871390
Interquartile range (IQR)20383372

Descriptive statistics

Standard deviation13811496
Coefficient of variation (CV)1.2145822
Kurtosis-1.2112445
Mean11371397
Median Absolute Deviation (MAD)2316355
Skewness0.76270106
Sum3.638847 × 108
Variance1.9075742 × 1014
MonotonicityNot monotonic
2023-12-11T09:23:41.072267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
32891280 8
25.0%
16496270 5
15.6%
1838290 4
12.5%
172920 4
12.5%
2357920 4
12.5%
19890 3
 
9.4%
224560 3
 
9.4%
63240 1
 
3.1%
ValueCountFrequency (%)
19890 3
 
9.4%
63240 1
 
3.1%
172920 4
12.5%
224560 3
 
9.4%
1838290 4
12.5%
2357920 4
12.5%
16496270 5
15.6%
32891280 8
25.0%
ValueCountFrequency (%)
32891280 8
25.0%
16496270 5
15.6%
2357920 4
12.5%
1838290 4
12.5%
224560 3
 
9.4%
172920 4
12.5%
63240 1
 
3.1%
19890 3
 
9.4%

누적미환급금액증감
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7835.8497
Minimum120.75
Maximum143675.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T09:23:41.159221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum120.75
5-th percentile209.4535
Q1385.655
median1352.37
Q34561.03
95-th percentile18349.611
Maximum143675.61
Range143554.86
Interquartile range (IQR)4175.375

Descriptive statistics

Standard deviation25321.082
Coefficient of variation (CV)3.2314405
Kurtosis29.129283
Mean7835.8497
Median Absolute Deviation (MAD)1095.55
Skewness5.3056851
Sum250747.19
Variance6.4115719 × 108
MonotonicityNot monotonic
2023-12-11T09:23:41.255215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
7266.67 1
 
3.1%
1644.83 1
 
3.1%
244.3 1
 
3.1%
143675.61 1
 
3.1%
24083.79 1
 
3.1%
973.78 1
 
3.1%
11350.4 1
 
3.1%
1583.31 1
 
3.1%
7896.52 1
 
3.1%
13658.01 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
120.75 1
3.1%
176.25 1
3.1%
236.62 1
3.1%
237.87 1
3.1%
244.3 1
3.1%
252.75 1
3.1%
260.89 1
3.1%
307.01 1
3.1%
411.87 1
3.1%
587.85 1
3.1%
ValueCountFrequency (%)
143675.61 1
3.1%
24083.79 1
3.1%
13658.01 1
3.1%
11350.4 1
3.1%
8995.94 1
3.1%
7896.52 1
3.1%
7451.09 1
3.1%
7266.67 1
3.1%
3659.15 1
3.1%
3432.96 1
3.1%

Interactions

2023-12-11T09:23:38.431148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:36.944630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.327885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.702520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:38.085837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:38.506220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.023333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.400368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.786205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:38.160316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:38.570760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.106556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.475632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.862329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:38.223927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:38.633720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.173898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.539171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.937461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:38.285348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:38.704041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.247379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:37.620525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:38.019933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:38.356080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:23:41.330301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드세목명미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
시군구명1.0001.0000.0000.0000.2670.4450.5840.0000.0000.359
자치단체코드1.0001.0000.0000.0000.2670.4450.5840.0000.0000.359
세목명0.0000.0001.0000.0000.0000.0000.0000.6670.6120.000
미환급유형0.0000.0000.0001.0000.0000.0000.0000.2680.2190.000
납세자유형0.2670.2670.0000.0001.0000.0000.1010.2890.3540.207
당해미환급건수0.4450.4450.0000.0000.0001.0000.8130.7400.7230.000
당해미환급금액0.5840.5840.0000.0000.1010.8131.0000.5090.4930.000
누적미환급건수0.0000.0000.6670.2680.2890.7400.5091.0001.0000.000
누적미환급금액0.0000.0000.6120.2190.3540.7230.4931.0001.0000.000
누적미환급금액증감0.3590.3590.0000.0000.2070.0000.0000.0000.0001.000
2023-12-11T09:23:41.430542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형세목명자치단체코드미환급유형시군구명
납세자유형1.0000.0000.3040.0000.304
세목명0.0001.0000.0000.0000.000
자치단체코드0.3040.0001.0000.0001.000
미환급유형0.0000.0000.0001.0000.000
시군구명0.3040.0001.0000.0001.000
2023-12-11T09:23:41.524923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감시군구명자치단체코드세목명미환급유형납세자유형
당해미환급건수1.0000.8350.7960.675-0.1050.2620.2620.0000.0000.000
당해미환급금액0.8351.0000.8290.802-0.2540.2410.2410.0000.0000.038
누적미환급건수0.7960.8291.0000.8620.1970.0000.0000.6150.1920.458
누적미환급금액0.6750.8020.8621.0000.2840.0000.0000.6150.1920.458
누적미환급금액증감-0.105-0.2540.1970.2841.0000.2740.2740.0000.0000.331
시군구명0.2620.2410.0000.0000.2741.0001.0000.0000.0000.304
자치단체코드0.2620.2410.0000.0000.2741.0001.0000.0000.0000.304
세목명0.0000.0000.6150.6150.0000.0000.0001.0000.0000.000
미환급유형0.0000.0000.1920.1920.0000.0000.0000.0001.0000.000
납세자유형0.0000.0380.4580.4580.3310.3040.3040.0000.0001.000

Missing values

2023-12-11T09:23:38.804355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:23:38.933112image/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
0창원시의창구48121등록면허세2020신규개인12704198907266.67
1창원시마산회원구48127등록면허세2020신규개인19010419890120.75
2창원시진해구48129등록면허세2020신규개인17200419890176.25
3창원시의창구48121자동차세2020신규개인3212288240207116496270620.92
4창원시성산구48123자동차세2020신규개인2602398250207116496270587.85
5창원시마산합포구48125자동차세2020신규개인734388302071164962703659.15
6창원시마산회원구48127자동차세2020신규개인17211152302071164962701379.18
7창원시진해구48129자동차세2020신규개인1037495102071164962702100.94
8창원시의창구48121자동차세2020신규법인494516601711838290307.01
9창원시성산구48123자동차세2020신규법인193591301711838290411.87
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
22창원시마산합포구48125지방소득세2020신규개인544454870159432891280638.32
23창원시마산회원구48127지방소득세2020신규개인10517769401594328912801751.01
24창원시진해구48129지방소득세2020국외이주개인323907015943289128013658.01
25창원시진해구48129지방소득세2020송달분 미수령개인44113201594328912807896.52
26창원시진해구48129지방소득세2020신규개인10319539701594328912801583.31
27창원시진해구48129지방소득세2020주소불명개인428725015943289128011350.4
28창원시의창구48121지방소득세2020신규법인9219590782357920973.78
29창원시성산구48123지방소득세2020신규법인16975078235792024083.79
30창원시마산합포구48125지방소득세2020신규법인21640782357920143675.61
31창원시마산회원구48127지방소득세2020신규법인8684840782357920244.3