Overview

Dataset statistics

Number of variables12
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory105.9 B

Variable types

Categorical7
Numeric5

Dataset

Description인천광역시 서구 2017년도부터 2021년도까지 세목별 당해미환급건수, 당해미환급금액, 누적미환급건수, 누적미환급금액을 포함하고 있습니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15078580&srcSe=7661IVAWM27C61E190

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
미환급유형 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 (8.9%) zerosZeros

Reproduction

Analysis started2024-01-28 14:09:54.659836
Analysis finished2024-01-28 14:09:56.829345
Duration2.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
인천광역시
45 

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 45
100.0%

Length

2024-01-28T23:09:56.879485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T23:09:56.952404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 45
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
서구
45 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서구 45
100.0%

Length

2024-01-28T23:09:57.030262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T23:09:57.108735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구 45
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
28260
45 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28260
2nd row28260
3rd row28260
4th row28260
5th row28260

Common Values

ValueCountFrequency (%)
28260 45
100.0%

Length

2024-01-28T23:09:57.184258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T23:09:57.255369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28260 45
100.0%

세목명
Categorical

Distinct6
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size492.0 B
자동차세
10 
지방소득세
10 
등록면허세
8 
재산세
7 
주민세
7 

Length

Max length5
Median length4
Mean length4.0222222
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 10
22.2%
지방소득세 10
22.2%
등록면허세 8
17.8%
재산세 7
15.6%
주민세 7
15.6%
취득세 3
 
6.7%

Length

2024-01-28T23:09:57.342719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T23:09:57.439331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 10
22.2%
지방소득세 10
22.2%
등록면허세 8
17.8%
재산세 7
15.6%
주민세 7
15.6%
취득세 3
 
6.7%

과세년도
Categorical

Distinct5
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size492.0 B
2021
11 
2019
10 
2017
8 
2018
8 
2020
8 

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 (%)
2021 11
24.4%
2019 10
22.2%
2017 8
17.8%
2018 8
17.8%
2020 8
17.8%

Length

2024-01-28T23:09:57.535718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T23:09:57.619049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 11
24.4%
2019 10
22.2%
2017 8
17.8%
2018 8
17.8%
2020 8
17.8%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
신규
45 

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 45
100.0%

Length

2024-01-28T23:09:57.719384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T23:09:57.790558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 45
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
개인
25 
법인
20 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 25
55.6%
법인 20
44.4%

Length

2024-01-28T23:09:57.862532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T23:09:57.937413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 25
55.6%
법인 20
44.4%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean142.91111
Minimum1
Maximum2446
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-01-28T23:09:58.014714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median14
Q362
95-th percentile585.4
Maximum2446
Range2445
Interquartile range (IQR)59

Descriptive statistics

Standard deviation396.84688
Coefficient of variation (CV)2.7768791
Kurtosis26.682309
Mean142.91111
Median Absolute Deviation (MAD)12
Skewness4.8256204
Sum6431
Variance157487.45
MonotonicityNot monotonic
2024-01-28T23:09:58.115361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 7
 
15.6%
4 4
 
8.9%
3 4
 
8.9%
2 3
 
6.7%
14 3
 
6.7%
844 1
 
2.2%
22 1
 
2.2%
6 1
 
2.2%
456 1
 
2.2%
10 1
 
2.2%
Other values (19) 19
42.2%
ValueCountFrequency (%)
1 7
15.6%
2 3
6.7%
3 4
8.9%
4 4
8.9%
5 1
 
2.2%
6 1
 
2.2%
10 1
 
2.2%
11 1
 
2.2%
14 3
6.7%
15 1
 
2.2%
ValueCountFrequency (%)
2446 1
2.2%
844 1
2.2%
599 1
2.2%
531 1
2.2%
456 1
2.2%
393 1
2.2%
219 1
2.2%
205 1
2.2%
176 1
2.2%
118 1
2.2%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9922496.9
Minimum80
Maximum2.106134 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-01-28T23:09:58.451759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum80
5-th percentile26090
Q1144960
median840790
Q32793020
95-th percentile43546404
Maximum2.106134 × 108
Range2.1061332 × 108
Interquartile range (IQR)2648060

Descriptive statistics

Standard deviation33200988
Coefficient of variation (CV)3.3460316
Kurtosis31.873938
Mean9922496.9
Median Absolute Deviation (MAD)765610
Skewness5.4074385
Sum4.4651236 × 108
Variance1.1023056 × 1015
MonotonicityNot monotonic
2024-01-28T23:09:58.563106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
144960 1
 
2.2%
172740 1
 
2.2%
1029810 1
 
2.2%
118620 1
 
2.2%
6976610 1
 
2.2%
840790 1
 
2.2%
189860 1
 
2.2%
2793020 1
 
2.2%
100130 1
 
2.2%
13180360 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
80 1
2.2%
12520 1
2.2%
25410 1
2.2%
28810 1
2.2%
32250 1
2.2%
75180 1
2.2%
79290 1
2.2%
99030 1
2.2%
100130 1
2.2%
118620 1
2.2%
ValueCountFrequency (%)
210613400 1
2.2%
68905940 1
2.2%
48076140 1
2.2%
25427460 1
2.2%
16833840 1
2.2%
13745290 1
2.2%
13180360 1
2.2%
9781060 1
2.2%
6976610 1
2.2%
5040430 1
2.2%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean262.02222
Minimum1
Maximum3425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-01-28T23:09:58.657081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median23
Q3138
95-th percentile1055.4
Maximum3425
Range3424
Interquartile range (IQR)132

Descriptive statistics

Standard deviation619.88956
Coefficient of variation (CV)2.36579
Kurtosis15.804201
Mean262.02222
Median Absolute Deviation (MAD)21
Skewness3.6877577
Sum11791
Variance384263.07
MonotonicityNot monotonic
2024-01-28T23:09:58.756873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2 4
 
8.9%
4 3
 
6.7%
8 2
 
4.4%
1 2
 
4.4%
76 2
 
4.4%
16 2
 
4.4%
1840 1
 
2.2%
13 1
 
2.2%
3 1
 
2.2%
1021 1
 
2.2%
Other values (26) 26
57.8%
ValueCountFrequency (%)
1 2
4.4%
2 4
8.9%
3 1
 
2.2%
4 3
6.7%
5 1
 
2.2%
6 1
 
2.2%
7 1
 
2.2%
8 2
4.4%
11 1
 
2.2%
13 1
 
2.2%
ValueCountFrequency (%)
3425 1
2.2%
1840 1
2.2%
1057 1
2.2%
1049 1
2.2%
1021 1
2.2%
994 1
2.2%
518 1
2.2%
395 1
2.2%
299 1
2.2%
190 1
2.2%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12253872
Minimum80
Maximum2.106134 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-01-28T23:09:58.860804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum80
5-th percentile80014
Q1348080
median2004210
Q34751460
95-th percentile48075960
Maximum2.106134 × 108
Range2.1061332 × 108
Interquartile range (IQR)4403380

Descriptive statistics

Standard deviation34577925
Coefficient of variation (CV)2.8217958
Kurtosis25.83134
Mean12253872
Median Absolute Deviation (MAD)1706420
Skewness4.8134309
Sum5.5142425 × 108
Variance1.1956329 × 1015
MonotonicityNot monotonic
2024-01-28T23:09:58.962593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
144960 1
 
2.2%
348080 1
 
2.2%
1134290 1
 
2.2%
175340 1
 
2.2%
15824640 1
 
2.2%
2181400 1
 
2.2%
2247970 1
 
2.2%
3233650 1
 
2.2%
199320 1
 
2.2%
25447860 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
80 1
2.2%
25400 1
2.2%
75260 1
2.2%
99030 1
2.2%
100760 1
2.2%
144960 1
2.2%
173770 1
2.2%
175340 1
2.2%
199320 1
2.2%
200400 1
2.2%
ValueCountFrequency (%)
210613400 1
2.2%
93077880 1
2.2%
50080350 1
2.2%
40058400 1
2.2%
25447860 1
2.2%
25340890 1
2.2%
16221530 1
2.2%
15824640 1
2.2%
13849770 1
2.2%
8507050 1
2.2%

누적미환급금액증감
Real number (ℝ)

ZEROS 

Distinct42
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean351.48644
Minimum0
Maximum10026.82
Zeros4
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-01-28T23:09:59.067389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115.78
median54.81
Q3102.88
95-th percentile967.84
Maximum10026.82
Range10026.82
Interquartile range (IQR)87.1

Descriptive statistics

Standard deviation1496.8454
Coefficient of variation (CV)4.2586149
Kurtosis42.264885
Mean351.48644
Median Absolute Deviation (MAD)44.66
Skewness6.4245985
Sum15816.89
Variance2240546.2
MonotonicityNot monotonic
2024-01-28T23:09:59.169481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0.0 4
 
8.9%
101.51 1
 
2.2%
47.82 1
 
2.2%
126.82 1
 
2.2%
159.45 1
 
2.2%
1084.01 1
 
2.2%
15.78 1
 
2.2%
99.06 1
 
2.2%
93.07 1
 
2.2%
54.81 1
 
2.2%
Other values (32) 32
71.1%
ValueCountFrequency (%)
0.0 4
8.9%
0.02 1
 
2.2%
0.11 1
 
2.2%
0.76 1
 
2.2%
4.17 1
 
2.2%
5.55 1
 
2.2%
10.15 1
 
2.2%
14.51 1
 
2.2%
15.78 1
 
2.2%
27.08 1
 
2.2%
ValueCountFrequency (%)
10026.82 1
2.2%
1306.57 1
2.2%
1084.01 1
2.2%
503.16 1
2.2%
394.09 1
2.2%
308.38 1
2.2%
213.06 1
2.2%
159.45 1
2.2%
133.32 1
2.2%
126.82 1
2.2%

Interactions

2024-01-28T23:09:56.269323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:54.946440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.253420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.598227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.956463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:56.332618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.006368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.314193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.677361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:56.016083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:56.413457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.066627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.371911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.755045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:56.082592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:56.486668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.131438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.452340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.828160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:56.149183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:56.554739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.194034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.526032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:55.891688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:09:56.206795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T23:09:59.238588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.2570.1570.3000.171
과세년도0.0001.0000.0000.5000.0000.1640.0000.000
납세자유형0.0000.0001.0000.1580.0410.3660.1690.085
당해미환급건수0.0000.5000.1581.0000.9460.9030.9130.000
당해미환급금액0.2570.0000.0410.9461.0000.7810.9950.000
누적미환급건수0.1570.1640.3660.9030.7811.0000.7810.000
누적미환급금액0.3000.0000.1690.9130.9950.7811.0000.000
누적미환급금액증감0.1710.0000.0850.0000.0000.0000.0001.000
2024-01-28T23:09:59.325760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형과세년도
세목명1.0000.0000.000
납세자유형0.0001.0000.000
과세년도0.0000.0001.000
2024-01-28T23:09:59.396648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도납세자유형
당해미환급건수1.0000.7420.9410.7000.1340.0000.2010.181
당해미환급금액0.7421.0000.6550.916-0.1780.1670.0000.018
누적미환급건수0.9410.6551.0000.7230.3730.0220.0960.246
누적미환급금액0.7000.9160.7231.0000.1030.1990.0000.194
누적미환급금액증감0.134-0.1780.3730.1031.0000.0460.0000.136
세목명0.0000.1670.0220.1990.0461.0000.0000.000
과세년도0.2010.0000.0960.0000.0000.0001.0000.000
납세자유형0.1810.0180.2460.1940.1360.0000.0001.000

Missing values

2024-01-28T23:09:56.641500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T23:09:56.780272image/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
0인천광역시서구28260등록면허세2017신규법인214496021449600.0
1인천광역시서구28260자동차세2017신규개인1761720730299297836073.09
2인천광역시서구28260자동차세2017신규법인264101004462291051.89
3인천광역시서구28260재산세2017신규개인479290810076027.08
4인천광역시서구28260주민세2017신규개인112520225400102.88
5인천광역시서구28260주민세2017신규법인1990301990300.0
6인천광역시서구28260지방소득세2017신규개인1182315550190346662049.71
7인천광역시서구28260지방소득세2017신규법인349498044951000.02
8인천광역시서구28260등록면허세2018신규개인1801800.0
9인천광역시서구28260등록면허세2018신규법인3288105173770503.16
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
35인천광역시서구28260등록면허세2021신규법인117355011708740308.38
36인천광역시서구28260자동차세2021신규개인8442542746018404005840057.54
37인천광역시서구28260자동차세2021신규법인7014797401723452570133.32
38인천광역시서구28260재산세2021신규개인44250349076475146089.79
39인천광역시서구28260재산세2021신규법인13225014326590010026.82
40인천광역시서구28260주민세2021신규개인225410233574101306.57
41인천광역시서구28260지방소득세2021신규개인24466890594034259307788035.08
42인천광역시서구28260지방소득세2021신규법인234807614048500803504.17
43인천광역시서구28260취득세2021신규개인5137452906138497700.76
44인천광역시서구28260취득세2021신규법인221061340022106134000.0