Overview

Dataset statistics

Number of variables11
Number of observations72
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory96.8 B

Variable types

Numeric6
Categorical5

Dataset

Description연도별 지방세 과세 및 비과세 현황을 세목별로 제공-항목 : 취득세, 주민세, 재산세, 자동차세, 레저세, 담배소비세, 지방소비세, 등록면허세, 도시계획세, 지역자원시설세, 지방소득세, 교육세 등
Author인천광역시 옹진군
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15079400&srcSe=7661IVAWM27C61E190

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
순번 is highly overall correlated with 과세년도High correlation
과세년도 is highly overall correlated with 순번High correlation
과세건수 is highly overall correlated with 비과세건수 and 2 other fieldsHigh correlation
과세금액 is highly overall correlated with 비과세금액 and 1 other fieldsHigh correlation
비과세건수 is highly overall correlated with 과세건수 and 1 other fieldsHigh correlation
비과세금액 is highly overall correlated with 과세건수 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 과세건수 and 1 other fieldsHigh correlation
순번 has unique valuesUnique
과세건수 has 14 (19.4%) zerosZeros
과세금액 has 14 (19.4%) zerosZeros
비과세건수 has 27 (37.5%) zerosZeros
비과세금액 has 27 (37.5%) zerosZeros

Reproduction

Analysis started2024-01-28 05:20:31.120535
Analysis finished2024-01-28 05:20:35.103571
Duration3.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.5
Minimum1
Maximum72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-01-28T14:20:35.167504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.55
Q118.75
median36.5
Q354.25
95-th percentile68.45
Maximum72
Range71
Interquartile range (IQR)35.5

Descriptive statistics

Standard deviation20.92845
Coefficient of variation (CV)0.57338218
Kurtosis-1.2
Mean36.5
Median Absolute Deviation (MAD)18
Skewness0
Sum2628
Variance438
MonotonicityStrictly increasing
2024-01-28T14:20:35.289649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
38 1
 
1.4%
54 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
Other values (62) 62
86.1%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
72 1
1.4%
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
인천광역시
72 

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 72
100.0%

Length

2024-01-28T14:20:35.414005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:20:35.512977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 72
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
옹진군
72 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
옹진군 72
100.0%

Length

2024-01-28T14:20:35.608231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:20:35.700731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
옹진군 72
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
28720
72 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28720
2nd row28720
3rd row28720
4th row28720
5th row28720

Common Values

ValueCountFrequency (%)
28720 72
100.0%

Length

2024-01-28T14:20:35.796547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:20:35.884023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28720 72
100.0%

과세년도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.4861
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-01-28T14:20:35.958853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2019.5
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7032947
Coefficient of variation (CV)0.00084342977
Kurtosis-1.2626873
Mean2019.4861
Median Absolute Deviation (MAD)1.5
Skewness-0.010750381
Sum145403
Variance2.9012128
MonotonicityIncreasing
2024-01-28T14:20:36.062741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2021 13
18.1%
2017 12
16.7%
2018 12
16.7%
2019 12
16.7%
2020 12
16.7%
2022 11
15.3%
ValueCountFrequency (%)
2017 12
16.7%
2018 12
16.7%
2019 12
16.7%
2020 12
16.7%
2021 13
18.1%
2022 11
15.3%
ValueCountFrequency (%)
2022 11
15.3%
2021 13
18.1%
2020 12
16.7%
2019 12
16.7%
2018 12
16.7%
2017 12
16.7%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size708.0 B
취득세
6 
주민세
6 
재산세
6 
자동차세
6 
레저세
6 
Other values (8)
42 

Length

Max length7
Median length5
Mean length4.1666667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 6
8.3%
주민세 6
8.3%
재산세 6
8.3%
자동차세 6
8.3%
레저세 6
8.3%
담배소비세 6
8.3%
지방소비세 6
8.3%
등록면허세 6
8.3%
지역자원시설세 6
8.3%
지방소득세 6
8.3%
Other values (3) 12
16.7%

Length

2024-01-28T14:20:36.179442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 6
8.3%
주민세 6
8.3%
재산세 6
8.3%
자동차세 6
8.3%
레저세 6
8.3%
담배소비세 6
8.3%
지방소비세 6
8.3%
등록면허세 6
8.3%
지역자원시설세 6
8.3%
지방소득세 6
8.3%
Other values (3) 12
16.7%

과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct59
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13963.236
Minimum0
Maximum64482
Zeros14
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-01-28T14:20:36.301675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q174.25
median6285
Q317310.75
95-th percentile62405.65
Maximum64482
Range64482
Interquartile range (IQR)17236.5

Descriptive statistics

Standard deviation18448.066
Coefficient of variation (CV)1.3211884
Kurtosis1.9280402
Mean13963.236
Median Absolute Deviation (MAD)6285
Skewness1.6740318
Sum1005353
Variance3.4033115 × 108
MonotonicityNot monotonic
2024-01-28T14:20:36.444216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14
 
19.4%
5127 1
 
1.4%
274 1
 
1.4%
6 1
 
1.4%
17258 1
 
1.4%
6755 1
 
1.4%
6042 1
 
1.4%
62209 1
 
1.4%
5352 1
 
1.4%
10550 1
 
1.4%
Other values (49) 49
68.1%
ValueCountFrequency (%)
0 14
19.4%
6 1
 
1.4%
7 1
 
1.4%
9 1
 
1.4%
45 1
 
1.4%
84 1
 
1.4%
87 1
 
1.4%
107 1
 
1.4%
274 1
 
1.4%
474 1
 
1.4%
ValueCountFrequency (%)
64482 1
1.4%
64124 1
1.4%
63869 1
1.4%
62646 1
1.4%
62209 1
1.4%
61908 1
1.4%
39046 1
1.4%
38370 1
1.4%
37948 1
1.4%
37223 1
1.4%

과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct59
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8923188 × 109
Minimum0
Maximum1.3184667 × 1010
Zeros14
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-01-28T14:20:36.592444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18.44633 × 108
median2.4967925 × 109
Q37.3726272 × 109
95-th percentile1.1698588 × 1010
Maximum1.3184667 × 1010
Range1.3184667 × 1010
Interquartile range (IQR)6.5279942 × 109

Descriptive statistics

Standard deviation3.9418922 × 109
Coefficient of variation (CV)1.0127362
Kurtosis-0.35631238
Mean3.8923188 × 109
Median Absolute Deviation (MAD)1.9374905 × 109
Skewness0.93564357
Sum2.8024695 × 1011
Variance1.5538514 × 1019
MonotonicityNot monotonic
2024-01-28T14:20:36.763549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14
 
19.4%
9640833000 1
 
1.4%
2399599000 1
 
1.4%
3499500000 1
 
1.4%
815359000 1
 
1.4%
11176478000 1
 
1.4%
4232522000 1
 
1.4%
3752244000 1
 
1.4%
13184667000 1
 
1.4%
979017000 1
 
1.4%
Other values (49) 49
68.1%
ValueCountFrequency (%)
0 14
19.4%
11867000 1
 
1.4%
722924000 1
 
1.4%
781027000 1
 
1.4%
815359000 1
 
1.4%
854391000 1
 
1.4%
895199000 1
 
1.4%
896514000 1
 
1.4%
935169000 1
 
1.4%
939983000 1
 
1.4%
ValueCountFrequency (%)
13184667000 1
1.4%
13001296000 1
1.4%
12594705000 1
1.4%
12315435000 1
1.4%
11193895000 1
1.4%
11176478000 1
1.4%
9785412000 1
1.4%
9739805000 1
1.4%
9640833000 1
1.4%
9404818000 1
1.4%

비과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)62.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1342.9028
Minimum0
Maximum11874
Zeros27
Zeros (%)37.5%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-01-28T14:20:36.903325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median364.5
Q31402.75
95-th percentile8171.4
Maximum11874
Range11874
Interquartile range (IQR)1402.75

Descriptive statistics

Standard deviation2538.2395
Coefficient of variation (CV)1.8901141
Kurtosis6.9303045
Mean1342.9028
Median Absolute Deviation (MAD)364.5
Skewness2.7022605
Sum96689
Variance6442659.6
MonotonicityNot monotonic
2024-01-28T14:20:37.017227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 27
37.5%
1 2
 
2.8%
686 1
 
1.4%
793 1
 
1.4%
8508 1
 
1.4%
1832 1
 
1.4%
652 1
 
1.4%
1267 1
 
1.4%
46 1
 
1.4%
693 1
 
1.4%
Other values (35) 35
48.6%
ValueCountFrequency (%)
0 27
37.5%
1 2
 
2.8%
3 1
 
1.4%
13 1
 
1.4%
15 1
 
1.4%
33 1
 
1.4%
37 1
 
1.4%
46 1
 
1.4%
86 1
 
1.4%
643 1
 
1.4%
ValueCountFrequency (%)
11874 1
1.4%
10352 1
1.4%
8652 1
1.4%
8508 1
1.4%
7896 1
1.4%
6207 1
1.4%
5647 1
1.4%
2837 1
1.4%
2340 1
1.4%
2183 1
1.4%

비과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct44
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9536369 × 108
Minimum0
Maximum2.464772 × 109
Zeros27
Zeros (%)37.5%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-01-28T14:20:37.137835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8845000
Q391749750
95-th percentile1.6916357 × 109
Maximum2.464772 × 109
Range2.464772 × 109
Interquartile range (IQR)91749750

Descriptive statistics

Standard deviation6.3958309 × 108
Coefficient of variation (CV)2.1654086
Kurtosis3.6894899
Mean2.9536369 × 108
Median Absolute Deviation (MAD)8845000
Skewness2.2140988
Sum2.1266186 × 1010
Variance4.0906653 × 1017
MonotonicityNot monotonic
2024-01-28T14:20:37.551504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 27
37.5%
9000 2
 
2.8%
3000 2
 
2.8%
93361000 1
 
1.4%
91335000 1
 
1.4%
27971000 1
 
1.4%
101045000 1
 
1.4%
13000 1
 
1.4%
1439757000 1
 
1.4%
3586000 1
 
1.4%
Other values (34) 34
47.2%
ValueCountFrequency (%)
0 27
37.5%
3000 2
 
2.8%
9000 2
 
2.8%
13000 1
 
1.4%
26000 1
 
1.4%
31000 1
 
1.4%
3066000 1
 
1.4%
3586000 1
 
1.4%
14104000 1
 
1.4%
14340000 1
 
1.4%
ValueCountFrequency (%)
2464772000 1
1.4%
2391327000 1
1.4%
2241168000 1
1.4%
1735100000 1
1.4%
1656074000 1
1.4%
1630286000 1
1.4%
1550284000 1
1.4%
1485626000 1
1.4%
1439757000 1
1.4%
1283917000 1
1.4%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
2022-08-31
72 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-31
2nd row2022-08-31
3rd row2022-08-31
4th row2022-08-31
5th row2022-08-31

Common Values

ValueCountFrequency (%)
2022-08-31 72
100.0%

Length

2024-01-28T14:20:37.667126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:20:37.744597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-31 72
100.0%

Interactions

2024-01-28T14:20:34.333769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:31.395791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:31.903778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:32.800223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:33.348189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:33.843823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:34.431983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:31.474795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:31.988752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:32.921026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:33.422304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:33.920048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:34.502872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:31.568036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:32.068098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:33.018545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:33.496872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:34.004320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:34.595279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:31.649655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:32.150643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:33.108415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:33.567555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:34.093789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:34.680323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:31.733154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:32.575419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:33.188509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:33.651986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:34.177704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:34.758982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:31.816174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:32.707152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:33.271186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:33.760893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:20:34.253380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T14:20:37.802895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번과세년도세목명과세건수과세금액비과세건수비과세금액
순번1.0000.9430.0000.0000.0000.0000.000
과세년도0.9431.0000.0000.0000.0000.0000.000
세목명0.0000.0001.0000.8980.8530.6240.667
과세건수0.0000.0000.8981.0000.6370.8270.576
과세금액0.0000.0000.8530.6371.0000.7910.854
비과세건수0.0000.0000.6240.8270.7911.0000.774
비과세금액0.0000.0000.6670.5760.8540.7741.000
2024-01-28T14:20:37.912121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번과세년도과세건수과세금액비과세건수비과세금액세목명
순번1.0000.9860.1020.1360.012-0.0560.000
과세년도0.9861.0000.0740.1250.0750.0240.000
과세건수0.1020.0741.0000.3990.6800.5510.673
과세금액0.1360.1250.3991.0000.3580.5180.571
비과세건수0.0120.0750.6800.3581.0000.8980.313
비과세금액-0.0560.0240.5510.5180.8981.0000.383
세목명0.0000.0000.6730.5710.3130.3831.000

Missing values

2024-01-28T14:20:34.873099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T14:20:35.047469image/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

순번시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액데이터기준일
01인천광역시옹진군287202017취득세512796408330006869462460002022-08-31
12인천광역시옹진군287202017등록세00330660002022-08-31
23인천광역시옹진군287202017주민세12557896514000710146060002022-08-31
34인천광역시옹진군287202017재산세352907340332000564714856260002022-08-31
45인천광역시옹진군287202017자동차세1664521245510001450901570002022-08-31
56인천광역시옹진군287202017레저세00002022-08-31
67인천광역시옹진군287202017담배소비세1072490662000002022-08-31
78인천광역시옹진군287202017지방소비세00002022-08-31
89인천광역시옹진군287202017등록면허세25251722924000697264840002022-08-31
910인천광역시옹진군287202017지역자원시설세5489130012960001160758570002022-08-31
순번시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액데이터기준일
6263인천광역시옹진군287202022주민세1058910006120002183141040002022-08-31
6364인천광역시옹진군287202022재산세3904687371690001035224647720002022-08-31
6465인천광역시옹진군287202022자동차세1690523094990001800853180002022-08-31
6566인천광역시옹진군287202022레저세4511867000002022-08-31
6667인천광역시옹진군287202022담배소비세6342502923000002022-08-31
6768인천광역시옹진군287202022지방소비세94731563000002022-08-31
6869인천광역시옹진군287202022등록면허세197027810270002837161500002022-08-31
6970인천광역시옹진군287202022지역자원시설세6528924426000020091908310002022-08-31
7071인천광역시옹진군287202022지방소득세89014597905000002022-08-31
7172인천광역시옹진군287202022교육세64124399047000086260002022-08-31