Overview

Dataset statistics

Number of variables12
Number of observations109
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.1 KiB
Average record size in memory104.2 B

Variable types

Categorical7
Numeric5

Dataset

Description지방세 미환급 현황 및 연간 누적 현황 데이터로, 세목명, 미환급유형, 납세자유형(개인/법인/사업자/기타), 당해 미환급 건수, 당해 미환금 금액, 누적 미환급 건수, 누적 미환금 금액, 누적 미환금 금액 증감 항목으로 구성 ※ 누적 미환금 금액 증감: (누적미환급금액–전년도누적미환급금액) / 전년도누적미환급금액 ※ 전년도누적미환급금액: 누적미환급금액 – 당해미환급금액
URLhttps://www.data.go.kr/data/15080593/fileData.do

Alerts

시도명 has constant value ""Constant
미환급유형 has constant value ""Constant
시군구명 is highly overall correlated with 자치단체코드High correlation
자치단체코드 is highly overall correlated with 시군구명High 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 2 other fieldsHigh correlation
누적미환급금액 is highly overall correlated with 당해미환급건수 and 2 other fieldsHigh correlation
당해미환급금액 has unique valuesUnique
누적미환급금액증감 has 5 (4.6%) zerosZeros

Reproduction

Analysis started2023-12-12 01:42:25.055650
Analysis finished2023-12-12 01:42:28.916346
Duration3.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1004.0 B
경기도
109 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 109
100.0%

Length

2023-12-12T10:42:28.994577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:42:29.137993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 109
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1004.0 B
성남시분당구
44 
성남시수정구
37 
성남시중원구
28 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row성남시분당구
2nd row성남시분당구
3rd row성남시수정구
4th row성남시중원구
5th row성남시분당구

Common Values

ValueCountFrequency (%)
성남시분당구 44
40.4%
성남시수정구 37
33.9%
성남시중원구 28
25.7%

Length

2023-12-12T10:42:29.254061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:42:29.356979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성남시분당구 44
40.4%
성남시수정구 37
33.9%
성남시중원구 28
25.7%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1004.0 B
41135
44 
41131
37 
41133
28 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41135
2nd row41135
3rd row41131
4th row41133
5th row41135

Common Values

ValueCountFrequency (%)
41135 44
40.4%
41131 37
33.9%
41133 28
25.7%

Length

2023-12-12T10:42:29.497106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:42:29.646406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41135 44
40.4%
41131 37
33.9%
41133 28
25.7%

세목명
Categorical

Distinct6
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size1004.0 B
자동차세
30 
지방소득세
28 
주민세
19 
등록면허세
15 
재산세
14 

Length

Max length5
Median length4
Mean length4.0642202
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 30
27.5%
지방소득세 28
25.7%
주민세 19
17.4%
등록면허세 15
13.8%
재산세 14
12.8%
취득세 3
 
2.8%

Length

2023-12-12T10:42:29.803328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:42:29.927763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 30
27.5%
지방소득세 28
25.7%
주민세 19
17.4%
등록면허세 15
13.8%
재산세 14
12.8%
취득세 3
 
2.8%

과세년도
Categorical

Distinct5
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2022
27 
2021
24 
2018
20 
2017
19 
2019
19 

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 (%)
2022 27
24.8%
2021 24
22.0%
2018 20
18.3%
2017 19
17.4%
2019 19
17.4%

Length

2023-12-12T10:42:30.089285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:42:30.211052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 27
24.8%
2021 24
22.0%
2018 20
18.3%
2017 19
17.4%
2019 19
17.4%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1004.0 B
신규
109 

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 109
100.0%

Length

2023-12-12T10:42:30.352613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:42:30.473115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 109
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1004.0 B
개인
63 
법인
46 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 63
57.8%
법인 46
42.2%

Length

2023-12-12T10:42:30.594123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:42:30.700800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 63
57.8%
법인 46
42.2%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)46.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.16514
Minimum1
Maximum3548
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T10:42:30.835118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median9
Q345
95-th percentile423.6
Maximum3548
Range3547
Interquartile range (IQR)42

Descriptive statistics

Standard deviation416.06912
Coefficient of variation (CV)3.7094335
Kurtosis47.846905
Mean112.16514
Median Absolute Deviation (MAD)8
Skewness6.5439609
Sum12226
Variance173113.51
MonotonicityNot monotonic
2023-12-12T10:42:30.979800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 14
 
12.8%
2 10
 
9.2%
3 8
 
7.3%
4 7
 
6.4%
9 5
 
4.6%
5 5
 
4.6%
7 3
 
2.8%
33 3
 
2.8%
17 3
 
2.8%
56 2
 
1.8%
Other values (41) 49
45.0%
ValueCountFrequency (%)
1 14
12.8%
2 10
9.2%
3 8
7.3%
4 7
6.4%
5 5
 
4.6%
6 2
 
1.8%
7 3
 
2.8%
8 2
 
1.8%
9 5
 
4.6%
10 1
 
0.9%
ValueCountFrequency (%)
3548 1
0.9%
2029 1
0.9%
1430 1
0.9%
468 1
0.9%
447 1
0.9%
428 1
0.9%
417 1
0.9%
378 1
0.9%
258 1
0.9%
254 1
0.9%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2631718.6
Minimum10
Maximum98245790
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T10:42:31.169461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile2202
Q131300
median230190
Q31223290
95-th percentile7972724
Maximum98245790
Range98245780
Interquartile range (IQR)1191990

Descriptive statistics

Standard deviation10532799
Coefficient of variation (CV)4.002251
Kurtosis65.796983
Mean2631718.6
Median Absolute Deviation (MAD)224160
Skewness7.6944065
Sum2.8685733 × 108
Variance1.1093984 × 1014
MonotonicityNot monotonic
2023-12-12T10:42:31.383774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
144000 1
 
0.9%
1671010 1
 
0.9%
5610 1
 
0.9%
8553190 1
 
0.9%
2650390 1
 
0.9%
3204600 1
 
0.9%
537340 1
 
0.9%
230190 1
 
0.9%
25750 1
 
0.9%
71160 1
 
0.9%
Other values (99) 99
90.8%
ValueCountFrequency (%)
10 1
0.9%
150 1
0.9%
760 1
0.9%
810 1
0.9%
1290 1
0.9%
2010 1
0.9%
2490 1
0.9%
3450 1
0.9%
5150 1
0.9%
5610 1
0.9%
ValueCountFrequency (%)
98245790 1
0.9%
43448060 1
0.9%
24977850 1
0.9%
10282060 1
0.9%
8553190 1
0.9%
8273000 1
0.9%
7522310 1
0.9%
6802230 1
0.9%
6448180 1
0.9%
4918660 1
0.9%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean452.86239
Minimum1
Maximum7021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T10:42:31.559644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q121
median74
Q3235
95-th percentile1798.8
Maximum7021
Range7020
Interquartile range (IQR)214

Descriptive statistics

Standard deviation1204.3167
Coefficient of variation (CV)2.6593436
Kurtosis23.020468
Mean452.86239
Median Absolute Deviation (MAD)64
Skewness4.659231
Sum49362
Variance1450378.7
MonotonicityNot monotonic
2023-12-12T10:42:31.717598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
15 5
 
4.6%
1 4
 
3.7%
5 4
 
3.7%
9 3
 
2.8%
1374 3
 
2.8%
32 3
 
2.8%
1066 3
 
2.8%
154 3
 
2.8%
38 3
 
2.8%
76 3
 
2.8%
Other values (30) 75
68.8%
ValueCountFrequency (%)
1 4
3.7%
2 1
 
0.9%
5 4
3.7%
6 3
2.8%
9 3
2.8%
10 1
 
0.9%
11 1
 
0.9%
13 1
 
0.9%
14 2
 
1.8%
15 5
4.6%
ValueCountFrequency (%)
7021 3
2.8%
2054 3
2.8%
1416 3
2.8%
1374 3
2.8%
1066 3
2.8%
626 3
2.8%
519 3
2.8%
380 3
2.8%
326 3
2.8%
235 3
2.8%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10647693
Minimum810
Maximum1.684547 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T10:42:31.923661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum810
5-th percentile22636
Q1309500
median2984230
Q37072670
95-th percentile35106902
Maximum1.684547 × 108
Range1.6845389 × 108
Interquartile range (IQR)6763170

Descriptive statistics

Standard deviation28141985
Coefficient of variation (CV)2.6430123
Kurtosis26.001527
Mean10647693
Median Absolute Deviation (MAD)2734090
Skewness5.0085181
Sum1.1605986 × 109
Variance7.919713 × 1014
MonotonicityNot monotonic
2023-12-12T10:42:32.132681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
18581020 3
 
2.8%
12444240 3
 
2.8%
26907440 3
 
2.8%
458540 3
 
2.8%
24965500 3
 
2.8%
2984230 3
 
2.8%
4726470 3
 
2.8%
18442390 3
 
2.8%
6179140 3
 
2.8%
5097120 3
 
2.8%
Other values (38) 79
72.5%
ValueCountFrequency (%)
810 1
 
0.9%
9050 2
1.8%
12730 1
 
0.9%
19090 1
 
0.9%
20920 1
 
0.9%
25210 1
 
0.9%
42620 3
2.8%
89120 3
2.8%
171000 1
 
0.9%
193370 2
1.8%
ValueCountFrequency (%)
168454700 3
2.8%
40573210 3
2.8%
26907440 3
2.8%
24965500 3
2.8%
18581020 3
2.8%
18442390 3
2.8%
12444240 3
2.8%
9195450 3
2.8%
8406280 3
2.8%
7072670 3
2.8%

누적미환급금액증감
Real number (ℝ)

ZEROS 

Distinct105
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42647.049
Minimum0
Maximum3094900
Zeros5
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T10:42:32.341786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.2
Q1189.42
median529.22
Q31500
95-th percentile33009.564
Maximum3094900
Range3094900
Interquartile range (IQR)1310.58

Descriptive statistics

Standard deviation307523.36
Coefficient of variation (CV)7.2108943
Kurtosis92.29117
Mean42647.049
Median Absolute Deviation (MAD)451.17
Skewness9.3795303
Sum4648528.3
Variance9.4570619 × 1010
MonotonicityNot monotonic
2023-12-12T10:42:32.503989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5
 
4.6%
19.0 1
 
0.9%
7005.0 1
 
0.9%
556.0 1
 
0.9%
81122.0 1
 
0.9%
215.0 1
 
0.9%
915.0 1
 
0.9%
740.0 1
 
0.9%
434.0 1
 
0.9%
99.0 1
 
0.9%
Other values (95) 95
87.2%
ValueCountFrequency (%)
0.0 5
4.6%
1.0 1
 
0.9%
19.0 1
 
0.9%
34.0 1
 
0.9%
37.0 1
 
0.9%
40.0 1
 
0.9%
43.0 1
 
0.9%
45.0 1
 
0.9%
60.0 1
 
0.9%
61.0 1
 
0.9%
ValueCountFrequency (%)
3094900.0 1
0.9%
802470.0 1
0.9%
418123.0 1
0.9%
81122.0 1
0.9%
72492.0 1
0.9%
44228.0 1
0.9%
16181.91 1
0.9%
15162.0 1
0.9%
12093.23 1
0.9%
7005.0 1
0.9%

Interactions

2023-12-12T10:42:27.642288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:25.551088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:26.053499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:26.556416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:27.059236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:27.763407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:25.643288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:26.144211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:26.655086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:27.156770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:28.181641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:25.738293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:26.233864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:26.742683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:27.255940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:28.320777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:25.827118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:26.321950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:26.832773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:27.393865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:28.462396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:25.926517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:26.426797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:26.962509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:27.526274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:42:32.619812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드세목명과세년도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
시군구명1.0001.0000.0000.0000.0430.0000.0000.0000.0000.098
자치단체코드1.0001.0000.0000.0000.0430.0000.0000.0000.0000.098
세목명0.0000.0001.0000.0000.0000.2180.1410.3540.4310.000
과세년도0.0000.0000.0001.0000.0000.2330.0000.4190.2830.100
납세자유형0.0430.0430.0000.0001.0000.1210.0000.4490.5070.103
당해미환급건수0.0000.0000.2180.2330.1211.0000.9940.7570.7770.000
당해미환급금액0.0000.0000.1410.0000.0000.9941.0000.6700.7110.000
누적미환급건수0.0000.0000.3540.4190.4490.7570.6701.0000.9850.000
누적미환급금액0.0000.0000.4310.2830.5070.7770.7110.9851.0000.000
누적미환급금액증감0.0980.0980.0000.1000.1030.0000.0000.0000.0001.000
2023-12-12T10:42:32.752641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명시군구명납세자유형과세년도자치단체코드
세목명1.0000.0000.0000.0000.000
시군구명0.0001.0000.0700.0001.000
납세자유형0.0000.0701.0000.0000.070
과세년도0.0000.0000.0001.0000.000
자치단체코드0.0001.0000.0700.0001.000
2023-12-12T10:42:32.911854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감시군구명자치단체코드세목명과세년도납세자유형
당해미환급건수1.0000.8550.8790.758-0.1410.0000.0000.1470.0870.145
당해미환급금액0.8551.0000.6890.777-0.3390.0000.0000.0930.0000.000
누적미환급건수0.8790.6891.0000.8510.2300.0000.0000.2310.3520.299
누적미환급금액0.7580.7770.8511.0000.2250.0000.0000.2890.2340.343
누적미환급금액증감-0.141-0.3390.2300.2251.0000.0910.0910.0000.0790.065
시군구명0.0000.0000.0000.0000.0911.0001.0000.0000.0000.070
자치단체코드0.0000.0000.0000.0000.0911.0001.0000.0000.0000.070
세목명0.1470.0930.2310.2890.0000.0000.0001.0000.0000.000
과세년도0.0870.0000.3520.2340.0790.0000.0000.0001.0000.000
납세자유형0.1450.0000.2990.3430.0650.0700.0700.0000.0001.000

Missing values

2023-12-12T10:42:28.618075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:42:28.835107image/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
0경기도성남시분당구41135등록면허세2017신규개인8144000917100019.0
1경기도성남시분당구41135등록면허세2017신규법인11800022521040.0
2경기도성남시수정구41131자동차세2017신규개인332380701741968100727.0
3경기도성남시중원구41133자동차세2017신규개인352362701741968100733.0
4경기도성남시분당구41135자동차세2017신규개인336397501741968100208.0
5경기도성남시수정구41131자동차세2017신규법인231000338652802691.0
6경기도성남시중원구41133자동차세2017신규법인911491033865280653.0
7경기도성남시분당구41135자동차세2017신규법인136313303386528037.0
8경기도성남시수정구41131재산세2017신규개인176619026258820291.0
9경기도성남시분당구41135재산세2017신규개인91926302625882034.0
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
99경기도성남시분당구41135주민세2022신규개인33264970107722190172.56
100경기도성남시수정구41131주민세2022신규법인1350609309360782.37
101경기도성남시분당구41135주민세2022신규법인41357709309360127.86
102경기도성남시수정구41131지방소득세2022신규개인4686802230205440573210496.47
103경기도성남시중원구41133지방소득세2022신규개인4286448180205440573210529.22
104경기도성남시분당구41135지방소득세2022신규개인44710282060205440573210294.6
105경기도성남시수정구41131지방소득세2022신규법인83130087381648012093.23
106경기도성남시중원구41133지방소득세2022신규법인42344087381648016181.91
107경기도성남시분당구41135지방소득세2022신규법인24214347087381648078.05
108경기도성남시수정구41131취득세2022신규개인1127301127300.0