Overview

Dataset statistics

Number of variables12
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory106.7 B

Variable types

Categorical6
Numeric6

Dataset

Description지방세미환급현황(세목명, 과세연도, 미환급유형, 납세자유형, 당해미환급건수, 당해미환급금액, 누적미환급건수, 누적미환급금액, 누적미환급금액증감 등) 정보공개
Author경기도 동두천시
URLhttps://www.data.go.kr/data/15079291/fileData.do

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 8 (22.2%) zerosZeros

Reproduction

Analysis started2024-03-16 04:13:37.663276
Analysis finished2024-03-16 04:13:42.802511
Duration5.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
경기도
36 

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 36
100.0%

Length

2024-03-16T13:13:42.917290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:13:43.080515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 36
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
동두천시
36 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동두천시 36
100.0%

Length

2024-03-16T13:13:43.329881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:13:43.617172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동두천시 36
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
41250
36 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41250
2nd row41250
3rd row41250
4th row41250
5th row41250

Common Values

ValueCountFrequency (%)
41250 36
100.0%

Length

2024-03-16T13:13:43.833635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:13:44.037461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41250 36
100.0%

세목명
Categorical

Distinct6
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size420.0 B
자동차세
12 
지방소득세
10 
재산세
6 
등록면허세
4 
주민세
3 

Length

Max length5
Median length4
Mean length4.1111111
Min length3

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 12
33.3%
지방소득세 10
27.8%
재산세 6
16.7%
등록면허세 4
 
11.1%
주민세 3
 
8.3%
취득세 1
 
2.8%

Length

2024-03-16T13:13:44.270410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:13:44.635236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 12
33.3%
지방소득세 10
27.8%
재산세 6
16.7%
등록면허세 4
 
11.1%
주민세 3
 
8.3%
취득세 1
 
2.8%

과세연도
Real number (ℝ)

Distinct6
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.8889
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-03-16T13:13:44.833203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12019
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5996031
Coefficient of variation (CV)0.0007919263
Kurtosis-0.8635499
Mean2019.8889
Median Absolute Deviation (MAD)1
Skewness-0.42942341
Sum72716
Variance2.5587302
MonotonicityIncreasing
2024-03-16T13:13:45.040914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2021 9
25.0%
2020 8
22.2%
2022 6
16.7%
2019 5
13.9%
2017 4
11.1%
2018 4
11.1%
ValueCountFrequency (%)
2017 4
11.1%
2018 4
11.1%
2019 5
13.9%
2020 8
22.2%
2021 9
25.0%
2022 6
16.7%
ValueCountFrequency (%)
2022 6
16.7%
2021 9
25.0%
2020 8
22.2%
2019 5
13.9%
2018 4
11.1%
2017 4
11.1%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
신규
36 

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 36
100.0%

Length

2024-03-16T13:13:45.293512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:13:45.478981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 36
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
개인
20 
법인
16 

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 20
55.6%
법인 16
44.4%

Length

2024-03-16T13:13:45.704529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:13:45.968355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 20
55.6%
법인 16
44.4%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.972222
Minimum1
Maximum393
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-03-16T13:13:46.171371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median7
Q329.25
95-th percentile241.5
Maximum393
Range392
Interquartile range (IQR)28.25

Descriptive statistics

Standard deviation93.124643
Coefficient of variation (CV)1.9412201
Kurtosis6.82067
Mean47.972222
Median Absolute Deviation (MAD)6
Skewness2.6490132
Sum1727
Variance8672.1992
MonotonicityNot monotonic
2024-03-16T13:13:46.406667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 10
27.8%
2 3
 
8.3%
25 2
 
5.6%
4 2
 
5.6%
148 1
 
2.8%
339 1
 
2.8%
61 1
 
2.8%
28 1
 
2.8%
393 1
 
2.8%
6 1
 
2.8%
Other values (13) 13
36.1%
ValueCountFrequency (%)
1 10
27.8%
2 3
 
8.3%
3 1
 
2.8%
4 2
 
5.6%
5 1
 
2.8%
6 1
 
2.8%
8 1
 
2.8%
14 1
 
2.8%
15 1
 
2.8%
16 1
 
2.8%
ValueCountFrequency (%)
393 1
2.8%
339 1
2.8%
209 1
2.8%
157 1
2.8%
148 1
2.8%
127 1
2.8%
61 1
2.8%
41 1
2.8%
33 1
2.8%
28 1
2.8%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean909864.44
Minimum240
Maximum5668470
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-03-16T13:13:46.600204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240
5-th percentile2720
Q124475
median165275
Q3614532.5
95-th percentile4258272.5
Maximum5668470
Range5668230
Interquartile range (IQR)590057.5

Descriptive statistics

Standard deviation1527237.4
Coefficient of variation (CV)1.6785329
Kurtosis2.3041976
Mean909864.44
Median Absolute Deviation (MAD)161145
Skewness1.821125
Sum32755120
Variance2.332454 × 1012
MonotonicityNot monotonic
2024-03-16T13:13:46.785873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
7240 1
 
2.8%
17410 1
 
2.8%
4320 1
 
2.8%
30900 1
 
2.8%
2853470 1
 
2.8%
360790 1
 
2.8%
233990 1
 
2.8%
46710 1
 
2.8%
3940 1
 
2.8%
3004550 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
240 1
2.8%
2120 1
2.8%
2920 1
2.8%
3940 1
2.8%
4320 1
2.8%
7240 1
2.8%
11000 1
2.8%
16280 1
2.8%
17410 1
2.8%
26830 1
2.8%
ValueCountFrequency (%)
5668470 1
2.8%
4530590 1
2.8%
4167500 1
2.8%
3528470 1
2.8%
3004550 1
2.8%
2853470 1
2.8%
2225770 1
2.8%
2145110 1
2.8%
1103540 1
2.8%
451530 1
2.8%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.611111
Minimum1
Maximum532
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-03-16T13:13:47.035448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median13
Q365.25
95-th percentile356
Maximum532
Range531
Interquartile range (IQR)62.25

Descriptive statistics

Standard deviation133.53593
Coefficient of variation (CV)1.7897593
Kurtosis5.2934483
Mean74.611111
Median Absolute Deviation (MAD)12
Skewness2.3862122
Sum2686
Variance17831.844
MonotonicityNot monotonic
2024-03-16T13:13:47.236207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 5
 
13.9%
3 3
 
8.3%
2 3
 
8.3%
8 2
 
5.6%
4 2
 
5.6%
208 1
 
2.8%
494 1
 
2.8%
82 1
 
2.8%
37 1
 
2.8%
532 1
 
2.8%
Other values (16) 16
44.4%
ValueCountFrequency (%)
1 5
13.9%
2 3
8.3%
3 3
8.3%
4 2
 
5.6%
5 1
 
2.8%
6 1
 
2.8%
8 2
 
5.6%
10 1
 
2.8%
16 1
 
2.8%
21 1
 
2.8%
ValueCountFrequency (%)
532 1
2.8%
494 1
2.8%
310 1
2.8%
253 1
2.8%
239 1
2.8%
208 1
2.8%
101 1
2.8%
82 1
2.8%
81 1
2.8%
60 1
2.8%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1356769.2
Minimum2840
Maximum7962420
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-03-16T13:13:47.479147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2840
5-th percentile3685
Q138760
median430765
Q31143205
95-th percentile6008750
Maximum7962420
Range7959580
Interquartile range (IQR)1104445

Descriptive statistics

Standard deviation2168623.9
Coefficient of variation (CV)1.5983735
Kurtosis2.9833638
Mean1356769.2
Median Absolute Deviation (MAD)405935
Skewness1.9410469
Sum48843690
Variance4.7029295 × 1012
MonotonicityNot monotonic
2024-03-16T13:13:47.715610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
7240 1
 
2.8%
20250 1
 
2.8%
4320 1
 
2.8%
30900 1
 
2.8%
3920900 1
 
2.8%
440340 1
 
2.8%
427250 1
 
2.8%
46710 1
 
2.8%
3940 1
 
2.8%
5455320 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
2840 1
2.8%
2920 1
2.8%
3940 1
2.8%
4320 1
2.8%
7240 1
2.8%
20250 1
2.8%
29410 1
2.8%
30900 1
2.8%
34200 1
2.8%
40280 1
2.8%
ValueCountFrequency (%)
7962420 1
2.8%
7669040 1
2.8%
5455320 1
2.8%
4773180 1
2.8%
4170420 1
2.8%
3920900 1
2.8%
3230900 1
2.8%
2429170 1
2.8%
1244710 1
2.8%
1109370 1
2.8%

누적미환급금액증감
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9693.3756
Minimum0
Maximum346508.33
Zeros8
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-03-16T13:13:47.972967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.415
median41.285
Q3128.1
95-th percentile244
Maximum346508.33
Range346508.33
Interquartile range (IQR)127.685

Descriptive statistics

Standard deviation57739.758
Coefficient of variation (CV)5.9566204
Kurtosis35.999859
Mean9693.3756
Median Absolute Deviation (MAD)41.285
Skewness5.9999829
Sum348961.52
Variance3.3338797 × 109
MonotonicityNot monotonic
2024-03-16T13:13:48.218390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 8
22.2%
47.0 1
 
2.8%
346508.33 1
 
2.8%
75.75 1
 
2.8%
210.91 1
 
2.8%
13.24 1
 
2.8%
54.24 1
 
2.8%
35.29 1
 
2.8%
0.53 1
 
2.8%
81.57 1
 
2.8%
Other values (19) 19
52.8%
ValueCountFrequency (%)
0.0 8
22.2%
0.07 1
 
2.8%
0.53 1
 
2.8%
13.24 1
 
2.8%
16.31 1
 
2.8%
16.73 1
 
2.8%
22.05 1
 
2.8%
34.0 1
 
2.8%
35.28 1
 
2.8%
35.29 1
 
2.8%
ValueCountFrequency (%)
346508.33 1
2.8%
247.0 1
2.8%
243.0 1
2.8%
220.0 1
2.8%
210.91 1
2.8%
185.0 1
2.8%
171.0 1
2.8%
150.0 1
2.8%
147.0 1
2.8%
121.8 1
2.8%

Interactions

2024-03-16T13:13:41.679969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:38.089690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:38.862062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:39.668141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:40.423654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:40.953647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:41.787620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:38.199531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:39.030304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:39.750579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:40.513914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:41.078652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:41.873172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:38.327673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:39.193765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:40.052550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:40.627950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:41.266009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:41.950171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:38.457314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:39.323983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:40.133909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:40.720084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:41.372516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:42.034530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:38.555740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:39.435830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:40.232612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:40.788784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:41.466051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:42.144778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:38.675065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:39.571945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:40.328966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:40.868042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:13:41.566031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:13:48.535998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세연도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.0000.000
과세연도0.0001.0000.0000.0000.0000.3860.2990.106
납세자유형0.0000.0001.0000.4480.2810.6780.2680.000
당해미환급건수0.0000.0000.4481.0000.8770.9800.8250.000
당해미환급금액0.0000.0000.2810.8771.0000.8860.951NaN
누적미환급건수0.0000.3860.6780.9800.8861.0000.8760.000
누적미환급금액0.0000.2990.2680.8250.9510.8761.0000.073
누적미환급금액증감0.0000.1060.0000.000NaN0.0000.0731.000
2024-03-16T13:13:49.084261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형
세목명1.0000.000
납세자유형0.0001.000
2024-03-16T13:13:49.221392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세연도당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명납세자유형
과세연도1.0000.2130.2350.1830.267-0.1410.0000.000
당해미환급건수0.2131.0000.9320.9620.8900.2350.0000.297
당해미환급금액0.2350.9321.0000.8680.9040.1030.0000.284
누적미환급건수0.1830.9620.8681.0000.9070.4480.0000.464
누적미환급금액0.2670.8900.9040.9071.0000.3680.0000.282
누적미환급금액증감-0.1410.2350.1030.4480.3681.0000.0000.000
세목명0.0000.0000.0000.0000.0000.0001.0000.000
납세자유형0.0000.2970.2840.4640.2820.0000.0001.000

Missing values

2024-03-16T13:13:42.333419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:13:42.664442image/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

시도명시군구명자치단체코드세목명과세연도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
0경기도동두천시41250등록면허세2017신규법인17240172400.0
1경기도동두천시41250자동차세2017신규개인263132203646194047.0
2경기도동두천시41250자동차세2017신규법인116280340280147.0
3경기도동두천시41250지방소득세2017신규개인1416033031434280171.0
4경기도동두천시41250자동차세2018신규개인2418993060651870243.0
5경기도동두천시41250자동차세2018신규법인226830567110150.0
6경기도동두천시41250재산세2018신규법인217022021702200.0
7경기도동두천시41250지방소득세2018신규개인254515305688581096.0
8경기도동두천시41250자동차세2019신규개인413532601011005130185.0
9경기도동두천시41250자동차세2019신규법인330450897560220.0
시도명시군구명자치단체코드세목명과세연도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
26경기도동두천시41250주민세2021신규개인4467104467100.0
27경기도동두천시41250주민세2021신규법인13940139400.0
28경기도동두천시41250지방소득세2021신규개인1573004550239545532081.57
29경기도동두천시41250지방소득세2021신규법인611035401011093700.53
30경기도동두천시41250자동차세2022신규개인3935668470532766904035.29
31경기도동두천시41250자동차세2022신규법인283708603757201054.24
32경기도동두천시41250재산세2022신규개인61214511082242917013.24
33경기도동두천시41250주민세2022신규개인111000334200210.91
34경기도동두천시41250지방소득세2022신규개인3394530590494796242075.75
35경기도동두천시41250지방소득세2022신규법인12404831860346508.33