Overview

Dataset statistics

Number of variables13
Number of observations68
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.5 KiB
Average record size in memory112.9 B

Variable types

Categorical6
Numeric6
DateTime1

Dataset

Description○ 미환급 유형별 미환급금 현황 및 연간 누적률 제공(세목명, 과세년도, 미환급유형, 납세자유형, 당해미환급건수, 누적미환급건수, 누적미환급금액, 누적미환급금액증감- 자치단체의 환급금 해소노력 확인 가능
Author세종특별자치시
URLhttps://www.data.go.kr/data/15080356/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터 기준일 has constant value ""Constant
당해미환급건수 is highly overall correlated with 당해미환급금액 High correlation
당해미환급금액 is highly overall correlated with 당해미환급건수 and 2 other fieldsHigh correlation
누적미환급건수 is highly overall correlated with 누적미환급금액 High correlation
누적미환급금액 is highly overall correlated with 당해미환급금액 and 1 other fieldsHigh correlation
누적미환급금액증감 is highly overall correlated with 당해미환급금액 High correlation
미환급유형 is highly imbalanced (58.0%)Imbalance
당해미환급금액 has unique valuesUnique
누적미환급금액증감 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:21:00.221504
Analysis finished2023-12-12 04:21:05.923434
Duration5.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
세종특별자치시
68 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세종특별자치시 68
100.0%

Length

2023-12-12T13:21:06.026504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:21:06.165484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세종특별자치시 68
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
세종특별자치시
68 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세종특별자치시 68
100.0%

Length

2023-12-12T13:21:06.314114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:21:06.448296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세종특별자치시 68
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
36110
68 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row36110
2nd row36110
3rd row36110
4th row36110
5th row36110

Common Values

ValueCountFrequency (%)
36110 68
100.0%

Length

2023-12-12T13:21:06.611767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:21:06.741206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
36110 68
100.0%

세목명
Categorical

Distinct6
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size676.0 B
자동차세
15 
지방소득세
15 
등록면허세
11 
재산세
11 
주민세
8 

Length

Max length5
Median length4
Mean length3.9852941
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 15
22.1%
지방소득세 15
22.1%
등록면허세 11
16.2%
재산세 11
16.2%
주민세 8
11.8%
취득세 8
11.8%

Length

2023-12-12T13:21:06.862302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:21:07.030567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 15
22.1%
지방소득세 15
22.1%
등록면허세 11
16.2%
재산세 11
16.2%
주민세 8
11.8%
취득세 8
11.8%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.4853
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-12T13:21:07.209443image/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 deviation1.6883503
Coefficient of variation (CV)0.00083603001
Kurtosis-1.1958609
Mean2019.4853
Median Absolute Deviation (MAD)1.5
Skewness0.016538646
Sum137325
Variance2.8505268
MonotonicityIncreasing
2023-12-12T13:21:07.369276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2020 13
19.1%
2019 12
17.6%
2017 11
16.2%
2018 11
16.2%
2022 11
16.2%
2021 10
14.7%
ValueCountFrequency (%)
2017 11
16.2%
2018 11
16.2%
2019 12
17.6%
2020 13
19.1%
2021 10
14.7%
2022 11
16.2%
ValueCountFrequency (%)
2022 11
16.2%
2021 10
14.7%
2020 13
19.1%
2019 12
17.6%
2018 11
16.2%
2017 11
16.2%

미환급유형
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
신규
59 
국외이주
7 
사망
 
2

Length

Max length4
Median length2
Mean length2.2058824
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신규 59
86.8%
국외이주 7
 
10.3%
사망 2
 
2.9%

Length

2023-12-12T13:21:07.559269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:21:07.702527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 59
86.8%
국외이주 7
 
10.3%
사망 2
 
2.9%

납세자유형
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
개인
44 
법인
24 

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 44
64.7%
법인 24
35.3%

Length

2023-12-12T13:21:07.833961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:21:07.947372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 44
64.7%
법인 24
35.3%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)63.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean226.63235
Minimum1
Maximum2548
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-12T13:21:08.086501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median13.5
Q3118.5
95-th percentile1543.8
Maximum2548
Range2547
Interquartile range (IQR)114.5

Descriptive statistics

Standard deviation516.95001
Coefficient of variation (CV)2.2810071
Kurtosis7.3492315
Mean226.63235
Median Absolute Deviation (MAD)12.5
Skewness2.7704283
Sum15411
Variance267237.31
MonotonicityNot monotonic
2023-12-12T13:21:08.267514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 11
 
16.2%
4 6
 
8.8%
3 4
 
5.9%
5 3
 
4.4%
133 2
 
2.9%
14 2
 
2.9%
9 2
 
2.9%
49 2
 
2.9%
13 2
 
2.9%
251 1
 
1.5%
Other values (33) 33
48.5%
ValueCountFrequency (%)
1 11
16.2%
2 1
 
1.5%
3 4
 
5.9%
4 6
8.8%
5 3
 
4.4%
6 1
 
1.5%
7 1
 
1.5%
8 1
 
1.5%
9 2
 
2.9%
10 1
 
1.5%
ValueCountFrequency (%)
2548 1
1.5%
1666 1
1.5%
1645 1
1.5%
1625 1
1.5%
1393 1
1.5%
1331 1
1.5%
1230 1
1.5%
910 1
1.5%
519 1
1.5%
435 1
1.5%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9666355.4
Minimum6790
Maximum1.0347935 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-12T13:21:08.461720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6790
5-th percentile21912
Q1101805
median862505
Q34127985
95-th percentile62299567
Maximum1.0347935 × 108
Range1.0347256 × 108
Interquartile range (IQR)4026180

Descriptive statistics

Standard deviation21213174
Coefficient of variation (CV)2.194537
Kurtosis6.9486504
Mean9666355.4
Median Absolute Deviation (MAD)827270
Skewness2.6844938
Sum6.5731216 × 108
Variance4.4999876 × 1014
MonotonicityNot monotonic
2023-12-12T13:21:08.686167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9270 1
 
1.5%
70062140 1
 
1.5%
2845920 1
 
1.5%
66079340 1
 
1.5%
1500160 1
 
1.5%
137770 1
 
1.5%
16700 1
 
1.5%
2696210 1
 
1.5%
44660 1
 
1.5%
29740 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
6790 1
1.5%
9270 1
1.5%
16700 1
1.5%
18020 1
1.5%
29140 1
1.5%
29740 1
1.5%
32220 1
1.5%
34390 1
1.5%
36080 1
1.5%
39420 1
1.5%
ValueCountFrequency (%)
103479350 1
1.5%
70519200 1
1.5%
70062140 1
1.5%
66079340 1
1.5%
55279990 1
1.5%
54567890 1
1.5%
38486180 1
1.5%
37990250 1
1.5%
34070254 1
1.5%
28088460 1
1.5%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean892.48529
Minimum2
Maximum6833
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-12T13:21:08.881294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8.35
Q137
median194
Q31006
95-th percentile4299.15
Maximum6833
Range6831
Interquartile range (IQR)969

Descriptive statistics

Standard deviation1486.4706
Coefficient of variation (CV)1.6655407
Kurtosis4.8925297
Mean892.48529
Median Absolute Deviation (MAD)182
Skewness2.2713705
Sum60689
Variance2209594.9
MonotonicityNot monotonic
2023-12-12T13:21:09.088130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38 3
 
4.4%
138 3
 
4.4%
2579 2
 
2.9%
1466 2
 
2.9%
3006 2
 
2.9%
34 2
 
2.9%
9 2
 
2.9%
334 2
 
2.9%
11 2
 
2.9%
1611 2
 
2.9%
Other values (42) 46
67.6%
ValueCountFrequency (%)
2 1
1.5%
4 1
1.5%
7 1
1.5%
8 1
1.5%
9 2
2.9%
11 2
2.9%
12 2
2.9%
16 1
1.5%
17 1
1.5%
19 2
2.9%
ValueCountFrequency (%)
6833 1
1.5%
5795 1
1.5%
4359 2
2.9%
4188 1
1.5%
4035 1
1.5%
3006 2
2.9%
2579 2
2.9%
1611 2
2.9%
1466 2
2.9%
1091 1
1.5%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26201762
Minimum41350
Maximum1.9531486 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-12T13:21:09.306969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41350
5-th percentile224478
Q11813335
median7161985
Q319226250
95-th percentile1.2932959 × 108
Maximum1.9531486 × 108
Range1.9527351 × 108
Interquartile range (IQR)17412915

Descriptive statistics

Standard deviation42500094
Coefficient of variation (CV)1.6220319
Kurtosis4.4092433
Mean26201762
Median Absolute Deviation (MAD)6796595
Skewness2.2141847
Sum1.7817198 × 109
Variance1.806258 × 1015
MonotonicityNot monotonic
2023-12-12T13:21:09.851813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14625650 3
 
4.4%
74884634 2
 
2.9%
47343850 2
 
2.9%
12298730 2
 
2.9%
19226250 2
 
2.9%
68834590 2
 
2.9%
129329590 2
 
2.9%
524240 1
 
1.5%
1880420 1
 
1.5%
14467860 1
 
1.5%
Other values (50) 50
73.5%
ValueCountFrequency (%)
41350 1
1.5%
56930 1
1.5%
106640 1
1.5%
223470 1
1.5%
226350 1
1.5%
332500 1
1.5%
350520 1
1.5%
380260 1
1.5%
386470 1
1.5%
406700 1
1.5%
ValueCountFrequency (%)
195314860 1
1.5%
144314650 1
1.5%
138002544 1
1.5%
129329590 2
2.9%
108569814 1
1.5%
104340590 1
1.5%
74884634 2
2.9%
68834590 2
2.9%
55549260 1
1.5%
47343850 2
2.9%

누적미환급금액증감
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27121.777
Minimum0.13
Maximum1102766.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-12T13:21:10.055076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.13
5-th percentile6.77
Q190.5
median264.9
Q31853.115
95-th percentile75779.478
Maximum1102766.5
Range1102766.4
Interquartile range (IQR)1762.615

Descriptive statistics

Standard deviation138709.57
Coefficient of variation (CV)5.1143246
Kurtosis56.116742
Mean27121.777
Median Absolute Deviation (MAD)234.795
Skewness7.2844745
Sum1844280.8
Variance1.9240345 × 1010
MonotonicityNot monotonic
2023-12-12T13:21:10.272064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
346.0 1
 
1.5%
84.59 1
 
1.5%
141.17 1
 
1.5%
108.84 1
 
1.5%
25.35 1
 
1.5%
280.52 1
 
1.5%
86533.89 1
 
1.5%
582.43 1
 
1.5%
289487.08 1
 
1.5%
1178.61 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
0.13 1
1.5%
0.49 1
1.5%
0.83 1
1.5%
1.8 1
1.5%
16.0 1
1.5%
22.0 1
1.5%
25.0 1
1.5%
25.35 1
1.5%
34.86 1
1.5%
62.0 1
1.5%
ValueCountFrequency (%)
1102766.48 1
1.5%
289487.08 1
1.5%
162370.0 1
1.5%
86533.89 1
1.5%
55807.0 1
1.5%
31038.0 1
1.5%
17656.0 1
1.5%
16408.0 1
1.5%
15536.0 1
1.5%
14436.59 1
1.5%

데이터 기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-12T13:21:10.424149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:10.563217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T13:21:04.788255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:00.716424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:01.451106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:02.471641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:03.210617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:04.000746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:04.901320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:00.833942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:01.564128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:02.589828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:03.328433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:04.127405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:05.017847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:00.940885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:01.668799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:02.707594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:03.466285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:04.266634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:05.134821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:01.063321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:01.787187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:02.811784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:03.607827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:04.396147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:05.268064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:01.207880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:02.248389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:02.953553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:03.733022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:04.535678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:05.409432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:01.335681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:02.376272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:03.109015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:03.869196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:21:04.670238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:21:10.655225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.6100.1770.0000.0000.6210.1000.000
과세년도0.0001.0000.0830.0000.0000.1500.3030.3770.000
미환급유형0.6100.0831.0000.1430.0000.0000.3430.0350.413
납세자유형0.1770.0000.1431.0000.0000.1280.3780.0000.000
당해미환급건수0.0000.0000.0000.0001.0000.7840.8710.8780.000
당해미환급금액0.0000.1500.0000.1280.7841.0000.7390.8050.000
누적미환급건수0.6210.3030.3430.3780.8710.7391.0000.8970.755
누적미환급금액0.1000.3770.0350.0000.8780.8050.8971.0000.850
누적미환급금액증감0.0000.0000.4130.0000.0000.0000.7550.8501.000
2023-12-12T13:21:10.825678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형세목명미환급유형
납세자유형1.0000.1190.233
세목명0.1191.0000.302
미환급유형0.2330.3021.000
2023-12-12T13:21:10.958109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명미환급유형납세자유형
과세년도1.0000.2430.2580.1190.188-0.1940.0000.0000.000
당해미환급건수0.2431.0000.8070.4970.412-0.4430.0000.0000.000
당해미환급금액0.2580.8071.0000.3300.531-0.6200.0000.0000.126
누적미환급건수0.1190.4970.3301.0000.7740.2960.3540.1470.355
누적미환급금액0.1880.4120.5310.7741.0000.1410.0610.0280.000
누적미환급금액증감-0.194-0.443-0.6200.2960.1411.0000.0000.4010.000
세목명0.0000.0000.0000.3540.0610.0001.0000.3020.119
미환급유형0.0000.0000.0000.1470.0280.4010.3021.0000.233
납세자유형0.0000.0000.1260.3550.0000.0000.1190.2331.000

Missing values

2023-12-12T13:21:05.582919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:21:05.823248image/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

시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감데이터 기준일
0세종특별자치시세종특별자치시36110등록면허세2017신규개인19270441350346.02022-12-31
1세종특별자치시세종특별자치시36110등록면허세2017신규법인3287500833250016.02022-12-31
2세종특별자치시세종특별자치시36110자동차세2017신규개인4355260350109112553790139.02022-12-31
3세종특별자치시세종특별자치시36110자동차세2017신규법인364740201263020060537.02022-12-31
4세종특별자치시세종특별자치시36110재산세2017신규개인134141603479082091.02022-12-31
5세종특별자치시세종특별자치시36110주민세2017신규개인336080985640638017656.02022-12-31
6세종특별자치시세종특별자치시36110지방소득세2017신규개인11822170203347963180259.02022-12-31
7세종특별자치시세종특별자치시36110지방소득세2017신규법인11903750386429200611.02022-12-31
8세종특별자치시세종특별자치시36110취득세2017국외이주개인1469701381462565031038.02022-12-31
9세종특별자치시세종특별자치시36110취득세2017사망개인4144255013814625650914.02022-12-31
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감데이터 기준일
58세종특별자치시세종특별자치시36110등록면허세2022신규법인14163290191454060790.482022-12-31
59세종특별자치시세종특별자치시36110자동차세2022신규개인1666384861805795108569814182.12022-12-31
60세종특별자치시세종특별자치시36110자동차세2022신규법인1704114240377739268079.692022-12-31
61세종특별자치시세종특별자치시36110재산세2022신규개인25127250204856961670155.472022-12-31
62세종특별자치시세종특별자치시36110재산세2022신규법인25103479350381043405900.832022-12-31
63세종특별자치시세종특별자치시36110주민세2022신규개인5475801009691651014436.592022-12-31
64세종특별자치시세종특별자치시36110주민세2022신규법인622319072234700.132022-12-31
65세종특별자치시세종특별자치시36110지방소득세2022신규개인1331379902504035144314650279.872022-12-31
66세종특별자치시세종특별자치시36110지방소득세2022신규법인75124917903341684605034.862022-12-31
67세종특별자치시세종특별자치시36110취득세2022신규개인1285101095977320109.662022-12-31