Overview

Dataset statistics

Number of variables12
Number of observations55
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory105.4 B

Variable types

Categorical6
Numeric6

Dataset

Description지방세 미환급 현황에 대한 데이터로 시도명, 시군구명, 지방자치단체코드, 세목명, 과세년도, 미환급유형, 납세자유형, 당해미환급건수, 당해미환급금액, 누적미환급건수, 누적미환급금액, 금액증감 등을 제공합니다.
Author경기도 의정부시
URLhttps://www.data.go.kr/data/15079454/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
당해미환급건수 has 1 (1.8%) missing valuesMissing
당해미환급금액 has unique valuesUnique
누적미환급금액 has unique valuesUnique
누적미환급금액증감 has 4 (7.3%) zerosZeros

Reproduction

Analysis started2023-12-12 02:00:12.177531
Analysis finished2023-12-12 02:00:16.982793
Duration4.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
경기도
55 

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 55
100.0%

Length

2023-12-12T11:00:17.061222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:00:17.185370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 55
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
의정부시
55 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
의정부시 55
100.0%

Length

2023-12-12T11:00:17.309242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:00:17.407332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의정부시 55
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
41150
55 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41150
2nd row41150
3rd row41150
4th row41150
5th row41150

Common Values

ValueCountFrequency (%)
41150 55
100.0%

Length

2023-12-12T11:00:17.508113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:00:17.609749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41150 55
100.0%

세목명
Categorical

Distinct7
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Memory size572.0 B
자동차세
12 
지방소득세
12 
재산세
10 
등록면허세
9 
주민세
9 
Other values (2)
3 

Length

Max length7
Median length5
Mean length4.0545455
Min length3

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 12
21.8%
지방소득세 12
21.8%
재산세 10
18.2%
등록면허세 9
16.4%
주민세 9
16.4%
취득세 2
 
3.6%
지역자원시설세 1
 
1.8%

Length

2023-12-12T11:00:17.741840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:00:17.871253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 12
21.8%
지방소득세 12
21.8%
재산세 10
18.2%
등록면허세 9
16.4%
주민세 9
16.4%
취득세 2
 
3.6%
지역자원시설세 1
 
1.8%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.5273
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T11:00:17.993613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6199514
Coefficient of variation (CV)0.00080214384
Kurtosis-1.122472
Mean2019.5273
Median Absolute Deviation (MAD)1
Skewness0.0035237538
Sum111074
Variance2.6242424
MonotonicityIncreasing
2023-12-12T11:00:18.115055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2020 11
20.0%
2018 10
18.2%
2019 10
18.2%
2021 9
16.4%
2022 8
14.5%
2017 7
12.7%
ValueCountFrequency (%)
2017 7
12.7%
2018 10
18.2%
2019 10
18.2%
2020 11
20.0%
2021 9
16.4%
2022 8
14.5%
ValueCountFrequency (%)
2022 8
14.5%
2021 9
16.4%
2020 11
20.0%
2019 10
18.2%
2018 10
18.2%
2017 7
12.7%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
신규
55 

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 55
100.0%

Length

2023-12-12T11:00:18.264027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:00:18.375661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 55
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
개인
30 
법인
25 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 30
54.5%
법인 25
45.5%

Length

2023-12-12T11:00:18.480597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:00:18.576778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 30
54.5%
법인 25
45.5%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct32
Distinct (%)59.3%
Missing1
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean186.14815
Minimum1
Maximum2550
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T11:00:18.673293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14.25
median12.5
Q348.5
95-th percentile926.2
Maximum2550
Range2549
Interquartile range (IQR)44.25

Descriptive statistics

Standard deviation456.95384
Coefficient of variation (CV)2.4547858
Kurtosis14.705067
Mean186.14815
Median Absolute Deviation (MAD)9.5
Skewness3.603298
Sum10052
Variance208806.81
MonotonicityNot monotonic
2023-12-12T11:00:18.796118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
4 5
 
9.1%
1 4
 
7.3%
10 4
 
7.3%
3 4
 
7.3%
16 3
 
5.5%
24 2
 
3.6%
12 2
 
3.6%
5 2
 
3.6%
7 2
 
3.6%
6 2
 
3.6%
Other values (22) 24
43.6%
ValueCountFrequency (%)
1 4
7.3%
2 1
 
1.8%
3 4
7.3%
4 5
9.1%
5 2
 
3.6%
6 2
 
3.6%
7 2
 
3.6%
8 1
 
1.8%
10 4
7.3%
12 2
 
3.6%
ValueCountFrequency (%)
2550 1
1.8%
1632 1
1.8%
1181 1
1.8%
789 1
1.8%
726 1
1.8%
637 1
1.8%
575 1
1.8%
435 1
1.8%
386 1
1.8%
319 1
1.8%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6138225.3
Minimum700
Maximum59189130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T11:00:18.928607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700
5-th percentile22715
Q1204650
median1028180
Q34550245
95-th percentile26811751
Maximum59189130
Range59188430
Interquartile range (IQR)4345595

Descriptive statistics

Standard deviation11994087
Coefficient of variation (CV)1.9539991
Kurtosis9.1279654
Mean6138225.3
Median Absolute Deviation (MAD)977910
Skewness2.8981623
Sum3.3760239 × 108
Variance1.4385812 × 1014
MonotonicityNot monotonic
2023-12-12T11:00:19.081381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
233510 1
 
1.8%
1553800 1
 
1.8%
1360860 1
 
1.8%
1246730 1
 
1.8%
3157110 1
 
1.8%
45330 1
 
1.8%
335900 1
 
1.8%
28804700 1
 
1.8%
5123360 1
 
1.8%
9980 1
 
1.8%
Other values (45) 45
81.8%
ValueCountFrequency (%)
700 1
1.8%
9980 1
1.8%
14420 1
1.8%
26270 1
1.8%
44110 1
1.8%
45330 1
1.8%
50270 1
1.8%
52560 1
1.8%
54340 1
1.8%
56720 1
1.8%
ValueCountFrequency (%)
59189130 1
1.8%
50130700 1
1.8%
28804700 1
1.8%
25957630 1
1.8%
22346340 1
1.8%
21634960 1
1.8%
18184210 1
1.8%
17981470 1
1.8%
16409690 1
1.8%
12596780 1
1.8%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean405.43636
Minimum1
Maximum4487
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T11:00:19.221944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q113
median30
Q3134
95-th percentile2282.4
Maximum4487
Range4486
Interquartile range (IQR)121

Descriptive statistics

Standard deviation908.49126
Coefficient of variation (CV)2.240774
Kurtosis9.0979536
Mean405.43636
Median Absolute Deviation (MAD)21
Skewness2.9546023
Sum22299
Variance825356.36
MonotonicityNot monotonic
2023-12-12T11:00:19.353711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
10 3
 
5.5%
30 3
 
5.5%
3 3
 
5.5%
13 2
 
3.6%
16 2
 
3.6%
145 1
 
1.8%
28 1
 
1.8%
9 1
 
1.8%
2205 1
 
1.8%
26 1
 
1.8%
Other values (37) 37
67.3%
ValueCountFrequency (%)
1 1
 
1.8%
3 3
5.5%
4 1
 
1.8%
6 1
 
1.8%
8 1
 
1.8%
9 1
 
1.8%
10 3
5.5%
11 1
 
1.8%
12 1
 
1.8%
13 2
3.6%
ValueCountFrequency (%)
4487 1
1.8%
3487 1
1.8%
2463 1
1.8%
2205 1
1.8%
1803 1
1.8%
1596 1
1.8%
1401 1
1.8%
959 1
1.8%
939 1
1.8%
573 1
1.8%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13250639
Minimum700
Maximum1.2006468 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T11:00:19.496995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700
5-th percentile98601
Q1494680
median2039670
Q311824710
95-th percentile63851031
Maximum1.2006468 × 108
Range1.2006398 × 108
Interquartile range (IQR)11330030

Descriptive statistics

Standard deviation26142212
Coefficient of variation (CV)1.9729021
Kurtosis8.5873385
Mean13250639
Median Absolute Deviation (MAD)1847200
Skewness2.8955609
Sum7.2878513 × 108
Variance6.8341527 × 1014
MonotonicityNot monotonic
2023-12-12T11:00:19.661653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
255110 1
 
1.8%
5521640 1
 
1.8%
2901850 1
 
1.8%
3089270 1
 
1.8%
19607210 1
 
1.8%
869400 1
 
1.8%
1411010 1
 
1.8%
77854300 1
 
1.8%
7796140 1
 
1.8%
9980 1
 
1.8%
Other values (45) 45
81.8%
ValueCountFrequency (%)
700 1
1.8%
9980 1
1.8%
26270 1
1.8%
129600 1
1.8%
142050 1
1.8%
151720 1
1.8%
192470 1
1.8%
213560 1
1.8%
221680 1
1.8%
250530 1
1.8%
ValueCountFrequency (%)
120064680 1
1.8%
115461670 1
1.8%
77854300 1
1.8%
57849630 1
1.8%
54644760 1
1.8%
41790300 1
1.8%
34676300 1
1.8%
32298420 1
1.8%
20957400 1
1.8%
19607210 1
1.8%

누적미환급금액증감
Real number (ℝ)

ZEROS 

Distinct52
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean225.786
Minimum0
Maximum1817.94
Zeros4
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T11:00:19.815682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q122.465
median110.34
Q3207.605
95-th percentile1146.164
Maximum1817.94
Range1817.94
Interquartile range (IQR)185.14

Descriptive statistics

Standard deviation392.64898
Coefficient of variation (CV)1.7390316
Kurtosis9.6705517
Mean225.786
Median Absolute Deviation (MAD)89.5
Skewness3.1217072
Sum12418.23
Variance154173.22
MonotonicityNot monotonic
2023-12-12T11:00:19.967710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4
 
7.3%
9.25 1
 
1.8%
489.71 1
 
1.8%
147.79 1
 
1.8%
521.05 1
 
1.8%
1817.94 1
 
1.8%
320.07 1
 
1.8%
170.28 1
 
1.8%
52.17 1
 
1.8%
108.39 1
 
1.8%
Other values (42) 42
76.4%
ValueCountFrequency (%)
0.0 4
7.3%
0.07 1
 
1.8%
2.06 1
 
1.8%
2.1 1
 
1.8%
4.67 1
 
1.8%
6.27 1
 
1.8%
9.25 1
 
1.8%
15.51 1
 
1.8%
16.55 1
 
1.8%
17.86 1
 
1.8%
ValueCountFrequency (%)
1817.94 1
1.8%
1793.15 1
1.8%
1381.0 1
1.8%
1045.52 1
1.8%
521.05 1
1.8%
489.71 1
1.8%
485.37 1
1.8%
320.07 1
1.8%
292.35 1
1.8%
255.36 1
1.8%

Interactions

2023-12-12T11:00:15.598141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:12.465528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:13.001105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:13.641934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:14.339985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:14.924361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:15.716054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:12.546480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:13.092777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:13.735770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:14.440418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:15.040083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:16.157667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:12.633705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:13.187149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:13.831675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:14.535779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:15.168540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:16.286479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:12.738286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:13.288840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:13.938766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:14.649386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:15.281297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:16.385374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:12.821557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:13.374386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:14.076162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:14.730711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:15.373491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:16.491230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:12.902214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:13.520679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:14.209162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:14.826272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:00:15.476540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:00:20.123448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.0000.189
과세년도0.0001.0000.0000.0000.0000.0000.0000.000
납세자유형0.0000.0001.0000.2890.2200.4050.1670.000
당해미환급건수0.0000.0000.2891.0000.9790.9660.9650.000
당해미환급금액0.0000.0000.2200.9791.0000.9180.9560.000
누적미환급건수0.0000.0000.4050.9660.9181.0000.8670.000
누적미환급금액0.0000.0000.1670.9650.9560.8671.0000.000
누적미환급금액증감0.1890.0000.0000.0000.0000.0000.0001.000
2023-12-12T11:00:20.240547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형
세목명1.0000.000
납세자유형0.0001.000
2023-12-12T11:00:20.347230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명납세자유형
과세년도1.0000.1210.2370.2330.3060.2600.0000.000
당해미환급건수0.1211.0000.7750.9110.7780.0320.0000.290
당해미환급금액0.2370.7751.0000.7430.954-0.0780.0000.231
누적미환급건수0.2330.9110.7431.0000.8200.3200.0000.283
누적미환급금액0.3060.7780.9540.8201.0000.1640.0000.178
누적미환급금액증감0.2600.032-0.0780.3200.1641.0000.1020.000
세목명0.0000.0000.0000.0000.0000.1021.0000.000
납세자유형0.0000.2900.2310.2830.1780.0000.0001.000

Missing values

2023-12-12T11:00:16.676667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:00:16.895092image/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
0경기도의정부시41150등록면허세2017신규법인7233510102551109.25
1경기도의정부시41150자동차세2017신규개인11515538003565521640255.36
2경기도의정부시41150자동차세2017신규법인1336118030797260120.74
3경기도의정부시41150재산세2017신규개인302125703525053017.86
4경기도의정부시41150재산세2017신규법인170017000.0
5경기도의정부시41150지방소득세2017신규개인319522644057310663460104.03
6경기도의정부시41150지방소득세2017신규법인650850065085000.0
7경기도의정부시41150등록면허세2018신규법인35256013307670485.37
8경기도의정부시41150자동차세2018신규개인14827725005048294140199.16
9경기도의정부시41150자동차세2018신규법인7272710371069970292.35
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
45경기도의정부시41150지방소득세2021신규법인2455962804612985960132.05
46경기도의정부시41150취득세2021신규개인147498044849602.1
47경기도의정부시41150등록면허세2022신규개인114420162135601381.0
48경기도의정부시41150자동차세2022신규개인118125957630246357849630122.86
49경기도의정부시41150자동차세2022신규법인523326650108579225074.12
50경기도의정부시41150재산세2022신규개인381588720142181990601045.52
51경기도의정부시41150주민세2022신규개인102438302538004055.86
52경기도의정부시41150주민세2022신규법인10908460162002070120.38
53경기도의정부시41150지방소득세2022신규개인255059189130448711546167095.07
54경기도의정부시41150지방소득세2022신규법인162961430306172580108.43