Overview

Dataset statistics

Number of variables13
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory114.0 B

Variable types

Categorical7
Numeric5
DateTime1

Dataset

Description인천광역시 남동구 지방세 미환급 현황에 대한 데이터로(과세년도, 미환급유형, 납세자유형, 당해미환급 금액, 누적미환급 금액, 누적미환급금액증감, 데이터기준일)등을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15079457&srcSe=7661IVAWM27C61E190

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
미환급유형 has constant value ""Constant
데이터기준일자 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 4 (9.1%) zerosZeros

Reproduction

Analysis started2024-03-18 02:02:10.210661
Analysis finished2024-03-18 02:02:12.745004
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
인천광역시
44 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 44
100.0%

Length

2024-03-18T11:02:12.795528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:12.878515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 44
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
남동구
44 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남동구 44
100.0%

Length

2024-03-18T11:02:12.974724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:13.052483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동구 44
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
28200
44 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28200
2nd row28200
3rd row28200
4th row28200
5th row28200

Common Values

ValueCountFrequency (%)
28200 44
100.0%

Length

2024-03-18T11:02:13.128953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:13.200425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28200 44
100.0%

세목명
Categorical

Distinct6
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size484.0 B
자동차세
10 
지방소득세
10 
등록면허세
9 
재산세
9 
주민세
4 

Length

Max length5
Median length4
Mean length4.0909091
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 10
22.7%
지방소득세 10
22.7%
등록면허세 9
20.5%
재산세 9
20.5%
주민세 4
 
9.1%
취득세 2
 
4.5%

Length

2024-03-18T11:02:13.288770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:13.388020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 10
22.7%
지방소득세 10
22.7%
등록면허세 9
20.5%
재산세 9
20.5%
주민세 4
 
9.1%
취득세 2
 
4.5%

과세년도
Categorical

Distinct5
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size484.0 B
2022
10 
2020
9 
2021
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 (%)
2022 10
22.7%
2020 9
20.5%
2021 9
20.5%
2018 8
18.2%
2019 8
18.2%

Length

2024-03-18T11:02:13.493355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:13.578623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10
22.7%
2020 9
20.5%
2021 9
20.5%
2018 8
18.2%
2019 8
18.2%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
신규
44 

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 44
100.0%

Length

2024-03-18T11:02:13.681413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:13.760796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 44
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
개인
25 
법인
19 

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 25
56.8%
법인 19
43.2%

Length

2024-03-18T11:02:13.850388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:13.941783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 25
56.8%
법인 19
43.2%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean263.38636
Minimum1
Maximum3264
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-03-18T11:02:14.022645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median17.5
Q3116.75
95-th percentile1584.55
Maximum3264
Range3263
Interquartile range (IQR)111.75

Descriptive statistics

Standard deviation618.27924
Coefficient of variation (CV)2.3474231
Kurtosis13.427163
Mean263.38636
Median Absolute Deviation (MAD)16.5
Skewness3.4571766
Sum11589
Variance382269.22
MonotonicityNot monotonic
2024-03-18T11:02:14.151437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 6
 
13.6%
6 3
 
6.8%
2 2
 
4.5%
5 2
 
4.5%
7 1
 
2.3%
29 1
 
2.3%
122 1
 
2.3%
45 1
 
2.3%
19 1
 
2.3%
1783 1
 
2.3%
Other values (25) 25
56.8%
ValueCountFrequency (%)
1 6
13.6%
2 2
 
4.5%
3 1
 
2.3%
4 1
 
2.3%
5 2
 
4.5%
6 3
6.8%
7 1
 
2.3%
8 1
 
2.3%
12 1
 
2.3%
14 1
 
2.3%
ValueCountFrequency (%)
3264 1
2.3%
1783 1
2.3%
1672 1
2.3%
1089 1
2.3%
695 1
2.3%
584 1
2.3%
546 1
2.3%
514 1
2.3%
361 1
2.3%
337 1
2.3%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5282919.3
Minimum420
Maximum50239010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-03-18T11:02:14.527565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum420
5-th percentile5588
Q1112667.5
median879930
Q33914897.5
95-th percentile22043288
Maximum50239010
Range50238590
Interquartile range (IQR)3802230

Descriptive statistics

Standard deviation10752657
Coefficient of variation (CV)2.0353627
Kurtosis9.3393681
Mean5282919.3
Median Absolute Deviation (MAD)863340
Skewness2.9967576
Sum2.3244845 × 108
Variance1.1561963 × 1014
MonotonicityNot monotonic
2024-03-18T11:02:14.633249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
117540 1
 
2.3%
254400 1
 
2.3%
195170 1
 
2.3%
179020 1
 
2.3%
20043510 1
 
2.3%
4713850 1
 
2.3%
1188760 1
 
2.3%
2894400 1
 
2.3%
694510 1
 
2.3%
50239010 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
420 1
2.3%
2070 1
2.3%
4160 1
2.3%
13680 1
2.3%
13950 1
2.3%
19230 1
2.3%
36940 1
2.3%
69760 1
2.3%
79680 1
2.3%
93880 1
2.3%
ValueCountFrequency (%)
50239010 1
2.3%
42855830 1
2.3%
22396190 1
2.3%
20043510 1
2.3%
18693040 1
2.3%
17106900 1
2.3%
8165880 1
2.3%
7966350 1
2.3%
7552620 1
2.3%
4805210 1
2.3%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean532.27273
Minimum1
Maximum5358
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-03-18T11:02:14.732457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q19
median50
Q3251.5
95-th percentile2967.55
Maximum5358
Range5357
Interquartile range (IQR)242.5

Descriptive statistics

Standard deviation1102.6904
Coefficient of variation (CV)2.0716643
Kurtosis8.6542844
Mean532.27273
Median Absolute Deviation (MAD)46
Skewness2.8133488
Sum23420
Variance1215926.2
MonotonicityNot monotonic
2024-03-18T11:02:14.840199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
9 4
 
9.1%
13 3
 
6.8%
2 3
 
6.8%
3 2
 
4.5%
1 2
 
4.5%
20 2
 
4.5%
72 1
 
2.3%
243 1
 
2.3%
3073 1
 
2.3%
84 1
 
2.3%
Other values (24) 24
54.5%
ValueCountFrequency (%)
1 2
4.5%
2 3
6.8%
3 2
4.5%
5 1
 
2.3%
9 4
9.1%
12 1
 
2.3%
13 3
6.8%
16 1
 
2.3%
20 2
4.5%
21 1
 
2.3%
ValueCountFrequency (%)
5358 1
2.3%
3269 1
2.3%
3073 1
2.3%
2370 1
2.3%
1593 1
2.3%
1465 1
2.3%
1408 1
2.3%
1364 1
2.3%
881 1
2.3%
850 1
2.3%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9553924.3
Minimum13950
Maximum78853610
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-03-18T11:02:14.951180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13950
5-th percentile27719
Q1253935
median2475790
Q37449202.5
95-th percentile36706876
Maximum78853610
Range78839660
Interquartile range (IQR)7195267.5

Descriptive statistics

Standard deviation17799492
Coefficient of variation (CV)1.8630556
Kurtosis7.3798994
Mean9553924.3
Median Absolute Deviation (MAD)2297640
Skewness2.6896739
Sum4.2037267 × 108
Variance3.1682191 × 1014
MonotonicityNot monotonic
2024-03-18T11:02:15.066022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
166480 1
 
2.3%
1601530 1
 
2.3%
262180 1
 
2.3%
486020 1
 
2.3%
34725050 1
 
2.3%
9883740 1
 
2.3%
4853760 1
 
2.3%
3066380 1
 
2.3%
695960 1
 
2.3%
78853610 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
13950 1
2.3%
19230 1
2.3%
20300 1
2.3%
69760 1
2.3%
70180 1
2.3%
93880 1
2.3%
166480 1
2.3%
171980 1
2.3%
203360 1
2.3%
203420 1
2.3%
ValueCountFrequency (%)
78853610 1
2.3%
71573320 1
2.3%
36918070 1
2.3%
35510110 1
2.3%
34725050 1
2.3%
33799760 1
2.3%
18257470 1
2.3%
17104260 1
2.3%
16817070 1
2.3%
10291120 1
2.3%

누적미환급금액증감
Real number (ℝ)

ZEROS 

Distinct41
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1128.485
Minimum0
Maximum21351.97
Zeros4
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-03-18T11:02:15.175593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q129.13
median93.77
Q3170.2525
95-th percentile5605.405
Maximum21351.97
Range21351.97
Interquartile range (IQR)141.1225

Descriptive statistics

Standard deviation4089.2541
Coefficient of variation (CV)3.6236672
Kurtosis18.347951
Mean1128.485
Median Absolute Deviation (MAD)76.895
Skewness4.3065318
Sum49653.34
Variance16721999
MonotonicityNot monotonic
2024-03-18T11:02:15.271662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0.0 4
 
9.1%
41.64 1
 
2.3%
13.53 1
 
2.3%
171.49 1
 
2.3%
73.25 1
 
2.3%
109.67 1
 
2.3%
308.3 1
 
2.3%
5.94 1
 
2.3%
0.21 1
 
2.3%
56.96 1
 
2.3%
Other values (31) 31
70.5%
ValueCountFrequency (%)
0.0 4
9.1%
0.21 1
 
2.3%
2.83 1
 
2.3%
5.31 1
 
2.3%
5.94 1
 
2.3%
7.01 1
 
2.3%
10.95 1
 
2.3%
13.53 1
 
2.3%
34.33 1
 
2.3%
41.32 1
 
2.3%
ValueCountFrequency (%)
21351.97 1
2.3%
16609.52 1
2.3%
6439.18 1
2.3%
880.68 1
2.3%
529.53 1
2.3%
450.68 1
2.3%
308.3 1
2.3%
304.58 1
2.3%
280.69 1
2.3%
240.71 1
2.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
Minimum2024-01-03 00:00:00
Maximum2024-01-03 00:00:00
2024-03-18T11:02:15.350111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:15.418050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-18T11:02:12.186290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:10.518700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.044450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.364623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.738502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:12.255966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:10.601691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.109021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.436488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.816617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:12.329482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:10.678633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.168849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.503127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.884559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:12.399311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:10.742036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.230104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.575597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.964165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:12.468598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:10.822036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.299988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:11.671798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:12.096614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T11:02:15.479299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.2950.506
과세년도0.0001.0000.0000.0000.0000.3020.0000.000
납세자유형0.0000.0001.0000.4880.4510.2970.2950.156
당해미환급건수0.0000.0000.4881.0000.9800.9450.7950.000
당해미환급금액0.0000.0000.4510.9801.0000.9480.9020.000
누적미환급건수0.0000.3020.2970.9450.9481.0000.8430.000
누적미환급금액0.2950.0000.2950.7950.9020.8431.0000.000
누적미환급금액증감0.5060.0000.1560.0000.0000.0000.0001.000
2024-03-18T11:02:15.582115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도납세자유형세목명
과세년도1.0000.0000.000
납세자유형0.0001.0000.000
세목명0.0000.0001.000
2024-03-18T11:02:15.652723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도납세자유형
당해미환급건수1.0000.9350.9780.9460.0470.0000.0000.331
당해미환급금액0.9351.0000.9220.940-0.1120.0000.0000.285
누적미환급건수0.9780.9221.0000.9580.1540.0000.1840.293
누적미환급금액0.9460.9400.9581.0000.1470.2050.0000.324
누적미환급금액증감0.047-0.1120.1540.1471.0000.3370.0000.093
세목명0.0000.0000.0000.2050.3371.0000.0000.000
과세년도0.0000.0000.1840.0000.0000.0001.0000.000
납세자유형0.3310.2850.2930.3240.0930.0000.0001.000

Missing values

2024-03-18T11:02:12.556121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T11:02:12.692050image/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

시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감데이터기준일자
0인천광역시남동구28200등록면허세2018신규개인7117540916648041.642024-01-03
1인천광역시남동구28200등록면허세2018신규법인1416052720306439.182024-01-03
2인천광역시남동구28200자동차세2018신규개인361480521085010291120114.172024-01-03
3인천광역시남동구28200자동차세2018신규법인598992701523638260304.582024-01-03
4인천광역시남동구28200재산세2018신규개인2192302192300.02024-01-03
5인천광역시남동구28200주민세2018신규개인2139502139500.02024-01-03
6인천광역시남동구28200지방소득세2018신규개인337816588088116817070105.942024-01-03
7인천광역시남동구28200지방소득세2018신규법인261209630562629350117.372024-01-03
8인천광역시남동구28200등록면허세2019신규개인33694012203420450.682024-01-03
9인천광역시남동구28200자동차세2019신규개인5147966350136418257470129.182024-01-03
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감데이터기준일자
34인천광역시남동구28200등록면허세2022신규개인154681602053152013.532024-01-03
35인천광역시남동구28200등록면허세2022신규법인4796809203360155.222024-01-03
36인천광역시남동구28200자동차세2022신규개인16722239619030733691807064.842024-01-03
37인천광역시남동구28200자동차세2022신규법인1152317850243396843071.212024-01-03
38인천광역시남동구28200재산세2022신규개인37860590722322230169.842024-01-03
39인천광역시남동구28200재산세2022신규법인61368013293463021351.972024-01-03
40인천광역시남동구28200주민세2022신규개인128131802390219010.952024-01-03
41인천광역시남동구28200주민세2022신규법인1938801938800.02024-01-03
42인천광역시남동구28200지방소득세2022신규개인32644285583053587157332067.012024-01-03
43인천광역시남동구28200지방소득세2022신규법인14115768053212618083.662024-01-03