Overview

Dataset statistics

Number of variables12
Number of observations33
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory107.0 B

Variable types

Categorical7
Numeric5

Dataset

Description부산광역시해운대구_지방세미환급금현황_20211231
Author부산광역시 해운대구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15078943

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 3 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 2 other fieldsHigh correlation
납세자유형 is highly overall correlated with 당해미환급건수 and 1 other fieldsHigh correlation
누적미환급금액증감 has 1 (3.0%) missing valuesMissing
당해미환급금액 has unique valuesUnique
누적미환급금액 has unique valuesUnique
누적미환급금액증감 has 2 (6.1%) zerosZeros

Reproduction

Analysis started2023-12-10 16:39:18.233799
Analysis finished2023-12-10 16:39:22.328366
Duration4.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
부산광역시
33 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 33
100.0%

Length

2023-12-11T01:39:22.442858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:22.580228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 33
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
해운대구
33 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
해운대구 33
100.0%

Length

2023-12-11T01:39:22.720657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:22.837087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해운대구 33
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
26350
33 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26350
2nd row26350
3rd row26350
4th row26350
5th row26350

Common Values

ValueCountFrequency (%)
26350 33
100.0%

Length

2023-12-11T01:39:22.972730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:23.089414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26350 33
100.0%

세목명
Categorical

Distinct5
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size396.0 B
자동차세
10 
지방소득세
10 
등록면허세
6 
재산세
5 
주민세
2 

Length

Max length5
Median length4
Mean length4.2727273
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 10
30.3%
지방소득세 10
30.3%
등록면허세 6
18.2%
재산세 5
15.2%
주민세 2
 
6.1%

Length

2023-12-11T01:39:23.209589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:23.340159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 10
30.3%
지방소득세 10
30.3%
등록면허세 6
18.2%
재산세 5
15.2%
주민세 2
 
6.1%

과세년도
Categorical

Distinct5
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size396.0 B
2021
10 
2020
7 
2018
6 
2019
6 
2017
4 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2018

Common Values

ValueCountFrequency (%)
2021 10
30.3%
2020 7
21.2%
2018 6
18.2%
2019 6
18.2%
2017 4
 
12.1%

Length

2023-12-11T01:39:23.467552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:23.630430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 10
30.3%
2020 7
21.2%
2018 6
18.2%
2019 6
18.2%
2017 4
 
12.1%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
신규
33 

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 33
100.0%

Length

2023-12-11T01:39:23.782119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:23.885087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 33
100.0%

납세자유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
개인
17 
법인
16 

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 17
51.5%
법인 16
48.5%

Length

2023-12-11T01:39:24.007485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:24.147749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 17
51.5%
법인 16
48.5%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.181818
Minimum1
Maximum414
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-11T01:39:24.313537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median9
Q370
95-th percentile247.8
Maximum414
Range413
Interquartile range (IQR)68

Descriptive statistics

Standard deviation98.929411
Coefficient of variation (CV)1.7300851
Kurtosis5.9698347
Mean57.181818
Median Absolute Deviation (MAD)8
Skewness2.4339448
Sum1887
Variance9787.0284
MonotonicityNot monotonic
2023-12-11T01:39:24.449614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 5
 
15.2%
2 4
 
12.1%
3 2
 
6.1%
7 2
 
6.1%
78 1
 
3.0%
14 1
 
3.0%
414 1
 
3.0%
51 1
 
3.0%
29 1
 
3.0%
342 1
 
3.0%
Other values (14) 14
42.4%
ValueCountFrequency (%)
1 5
15.2%
2 4
12.1%
3 2
 
6.1%
5 1
 
3.0%
6 1
 
3.0%
7 2
 
6.1%
8 1
 
3.0%
9 1
 
3.0%
12 1
 
3.0%
13 1
 
3.0%
ValueCountFrequency (%)
414 1
3.0%
342 1
3.0%
185 1
3.0%
180 1
3.0%
147 1
3.0%
142 1
3.0%
78 1
3.0%
71 1
3.0%
70 1
3.0%
61 1
3.0%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1305855.2
Minimum160
Maximum15172750
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-11T01:39:24.598053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum160
5-th percentile3942
Q176210
median206890
Q31158360
95-th percentile5243886
Maximum15172750
Range15172590
Interquartile range (IQR)1082150

Descriptive statistics

Standard deviation2862363.7
Coefficient of variation (CV)2.1919458
Kurtosis17.851773
Mean1305855.2
Median Absolute Deviation (MAD)193670
Skewness3.9469411
Sum43093220
Variance8.1931261 × 1012
MonotonicityNot monotonic
2023-12-11T01:39:24.797830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
613030 1
 
3.0%
4710670 1
 
3.0%
216370 1
 
3.0%
13220 1
 
3.0%
2476980 1
 
3.0%
39150 1
 
3.0%
76210 1
 
3.0%
138770 1
 
3.0%
1158360 1
 
3.0%
132380 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
160 1
3.0%
3690 1
3.0%
4110 1
3.0%
7580 1
3.0%
13220 1
3.0%
39150 1
3.0%
41310 1
3.0%
66340 1
3.0%
76210 1
3.0%
80260 1
3.0%
ValueCountFrequency (%)
15172750 1
3.0%
6043710 1
3.0%
4710670 1
3.0%
2811060 1
3.0%
2476980 1
3.0%
2276000 1
3.0%
2147520 1
3.0%
1283740 1
3.0%
1158360 1
3.0%
1006850 1
3.0%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean116.72727
Minimum1
Maximum746
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-11T01:39:24.972769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.6
Q16
median31
Q3117
95-th percentile484.2
Maximum746
Range745
Interquartile range (IQR)111

Descriptive statistics

Standard deviation190.39962
Coefficient of variation (CV)1.6311494
Kurtosis4.2946315
Mean116.72727
Median Absolute Deviation (MAD)28
Skewness2.1548505
Sum3852
Variance36252.017
MonotonicityNot monotonic
2023-12-11T01:39:25.153015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
3 4
 
12.1%
8 2
 
6.1%
1 2
 
6.1%
6 2
 
6.1%
117 1
 
3.0%
357 1
 
3.0%
42 1
 
3.0%
746 1
 
3.0%
2 1
 
3.0%
59 1
 
3.0%
Other values (17) 17
51.5%
ValueCountFrequency (%)
1 2
6.1%
2 1
 
3.0%
3 4
12.1%
4 1
 
3.0%
6 2
6.1%
8 2
6.1%
13 1
 
3.0%
20 1
 
3.0%
26 1
 
3.0%
30 1
 
3.0%
ValueCountFrequency (%)
746 1
3.0%
669 1
3.0%
361 1
3.0%
360 1
3.0%
357 1
3.0%
330 1
3.0%
188 1
3.0%
180 1
3.0%
117 1
3.0%
110 1
3.0%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2360088.8
Minimum7740
Maximum20371350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-11T01:39:25.333493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7740
5-th percentile29456
Q1220110
median435300
Q33291220
95-th percentile7342484
Maximum20371350
Range20363610
Interquartile range (IQR)3071110

Descriptive statistics

Standard deviation4042326.4
Coefficient of variation (CV)1.7127857
Kurtosis12.006123
Mean2360088.8
Median Absolute Deviation (MAD)386220
Skewness3.1097214
Sum77882930
Variance1.6340403 × 1013
MonotonicityNot monotonic
2023-12-11T01:39:25.562055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1033970 1
 
3.0%
9048650 1
 
3.0%
413410 1
 
3.0%
220110 1
 
3.0%
5759940 1
 
3.0%
435300 1
 
3.0%
83950 1
 
3.0%
760590 1
 
3.0%
1566960 1
 
3.0%
247240 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
7740 1
3.0%
26990 1
3.0%
31100 1
3.0%
49080 1
3.0%
66340 1
3.0%
83950 1
3.0%
97970 1
3.0%
216710 1
3.0%
220110 1
3.0%
247240 1
3.0%
ValueCountFrequency (%)
20371350 1
3.0%
9048650 1
3.0%
6205040 1
3.0%
6105490 1
3.0%
6102280 1
3.0%
5759940 1
3.0%
4665570 1
3.0%
4173120 1
3.0%
3291220 1
3.0%
2007480 1
3.0%

누적미환급금액증감
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)96.9%
Missing1
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean1304.3338
Minimum0
Maximum30575
Zeros2
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-11T01:39:25.756585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.561
Q135.0175
median117.165
Q3405.715
95-th percentile2546.52
Maximum30575
Range30575
Interquartile range (IQR)370.6975

Descriptive statistics

Standard deviation5388.1535
Coefficient of variation (CV)4.1309623
Kurtosis30.790297
Mean1304.3338
Median Absolute Deviation (MAD)108.115
Skewness5.5096949
Sum41738.68
Variance29032199
MonotonicityNot monotonic
2023-12-11T01:39:26.301032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 2
 
6.1%
68.67 1
 
3.0%
86.77 1
 
3.0%
391.59 1
 
3.0%
34.26 1
 
3.0%
3746.18 1
 
3.0%
175.19 1
 
3.0%
35.27 1
 
3.0%
92.09 1
 
3.0%
448.09 1
 
3.0%
Other values (21) 21
63.6%
ValueCountFrequency (%)
0.0 2
6.1%
1.02 1
3.0%
2.11 1
3.0%
4.75 1
3.0%
7.94 1
3.0%
10.16 1
3.0%
34.26 1
3.0%
35.27 1
3.0%
68.67 1
3.0%
83.35 1
3.0%
ValueCountFrequency (%)
30575.0 1
3.0%
3746.18 1
3.0%
1564.98 1
3.0%
1011.88 1
3.0%
792.79 1
3.0%
656.69 1
3.0%
631.44 1
3.0%
448.09 1
3.0%
391.59 1
3.0%
308.05 1
3.0%

Interactions

2023-12-11T01:39:21.332661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:18.664847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:19.325175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:19.991820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:20.659637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:21.452467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:18.779858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:19.452511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:20.118171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:20.794192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:21.576194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:18.913968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:19.600640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:20.273192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:20.939964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:21.706524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:19.044538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:19.732468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:20.401037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:21.067111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:21.863243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:19.185513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:19.870431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:20.531608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:21.206024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:39:26.427706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.0000.297
과세년도0.0001.0000.0000.0000.0000.4940.0000.000
납세자유형0.0000.0001.0000.8090.4760.7420.3670.014
당해미환급건수0.0000.0000.8091.0000.9740.9890.9630.000
당해미환급금액0.0000.0000.4760.9741.0000.9730.9620.000
누적미환급건수0.0000.4940.7420.9890.9731.0000.9760.000
누적미환급금액0.0000.0000.3670.9630.9620.9761.0000.911
누적미환급금액증감0.2970.0000.0140.0000.0000.0000.9111.000
2023-12-11T01:39:26.551560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도납세자유형세목명
과세년도1.0000.0000.000
납세자유형0.0001.0000.000
세목명0.0000.0001.000
2023-12-11T01:39:26.662963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도납세자유형
당해미환급건수1.0000.6380.9580.601-0.1110.0000.0000.570
당해미환급금액0.6381.0000.6020.882-0.3890.0000.0000.279
누적미환급건수0.9580.6021.0000.6160.0380.0000.3490.511
누적미환급금액0.6010.8820.6161.000-0.0290.0000.0000.201
누적미환급금액증감-0.111-0.3890.038-0.0291.0000.2180.0000.000
세목명0.0000.0000.0000.0000.2181.0000.0000.000
과세년도0.0000.0000.3490.0000.0000.0001.0000.000
납세자유형0.5700.2790.5110.2010.0000.0000.0001.000

Missing values

2023-12-11T01:39:22.021357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:39:22.224483image/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
0부산광역시해운대구26350자동차세2017신규개인78613030117103397068.67
1부산광역시해운대구26350자동차세2017신규법인171323802624724086.77
2부산광역시해운대구26350지방소득세2017신규개인611006850110200748099.38
3부산광역시해운대구26350지방소득세2017신규법인536901326990631.44
4부산광역시해운대구26350자동차세2018신규개인718631501881897120119.79
5부산광역시해운대구26350자동차세2018신규법인88026034327500308.05
6부산광역시해운대구26350재산세2018신규개인720689082167104.75
7부산광역시해운대구26350재산세2018신규법인16043710361054901.02
8부산광역시해운대구26350지방소득세2018신규개인7012837401803291220156.38
9부산광역시해운대구26350지방소득세2018신규법인741102031100656.69
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
23부산광역시해운대구26350등록면허세2021신규개인37621068395010.16
24부산광역시해운대구26350등록면허세2021신규법인21387706760590448.09
25부산광역시해운대구26350자동차세2021신규개인3424710670669904865092.09
26부산광역시해운대구26350자동차세2021신규법인29115836058156696035.27
27부산광역시해운대구26350재산세2021신규개인5112564059345750175.19
28부산광역시해운대구26350재산세2021신규법인2161330362050403746.18
29부산광역시해운대구26350주민세2021신규개인2663402663400.0
30부산광역시해운대구26350주민세2021신규법인1979701979700.0
31부산광역시해운대구26350지방소득세2021신규개인414151727507462037135034.26
32부산광역시해운대구26350지방소득세2021신규법인1410464042514400391.59