Overview

Dataset statistics

Number of variables12
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory106.8 B

Variable types

Categorical6
Numeric6

Dataset

Description미환급 유형별 미환급금 현황 및 연간 누적률을 제공한다.2017년부터 2022년까지 재산세,자동차세, 지방소득세, 등록면허세 등납세자유형에 따른 당해미환급 건수, 당해미환급 금액, 누적미환급건수, 누적미환급금액, 누적미환급금액 증감에 대한 자료를 제공한다.
Author전라남도 장성군
URLhttps://www.data.go.kr/data/15080243/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
미환급유형 has constant value ""Constant
과세년도 is highly overall correlated with 누적미환급금액증감High 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
누적미환급금액증감 is highly overall correlated with 과세년도High correlation
당해미환급금액 has unique valuesUnique
누적미환급금액 has unique valuesUnique
누적미환급금액증감 has 5 (14.7%) zerosZeros

Reproduction

Analysis started2024-03-14 20:39:19.413915
Analysis finished2024-03-14 20:39:30.864773
Duration11.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size400.0 B
전라남도
34 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 34
100.0%

Length

2024-03-15T05:39:31.064714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:39:31.307116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 34
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size400.0 B
장성군
34 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장성군 34
100.0%

Length

2024-03-15T05:39:31.490478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:39:31.815728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장성군 34
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size400.0 B
46880
34 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46880
2nd row46880
3rd row46880
4th row46880
5th row46880

Common Values

ValueCountFrequency (%)
46880 34
100.0%

Length

2024-03-15T05:39:32.147568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:39:32.463178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46880 34
100.0%

세목명
Categorical

Distinct6
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size400.0 B
자동차세
12 
지방소득세
11 
재산세
6 
등록면허세
2 
주민세
2 

Length

Max length5
Median length4
Mean length4.1176471
Min length3

Unique

Unique1 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 12
35.3%
지방소득세 11
32.4%
재산세 6
17.6%
등록면허세 2
 
5.9%
주민세 2
 
5.9%
취득세 1
 
2.9%

Length

2024-03-15T05:39:32.841506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:39:33.219483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 12
35.3%
지방소득세 11
32.4%
재산세 6
17.6%
등록면허세 2
 
5.9%
주민세 2
 
5.9%
취득세 1
 
2.9%

과세년도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.6765
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-03-15T05:39:33.573272image/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 deviation1.7359058
Coefficient of variation (CV)0.00085949697
Kurtosis-1.2366749
Mean2019.6765
Median Absolute Deviation (MAD)1
Skewness-0.31595573
Sum68669
Variance3.013369
MonotonicityIncreasing
2024-03-15T05:39:33.868127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2021 9
26.5%
2017 6
17.6%
2020 6
17.6%
2022 5
14.7%
2018 4
11.8%
2019 4
11.8%
ValueCountFrequency (%)
2017 6
17.6%
2018 4
11.8%
2019 4
11.8%
2020 6
17.6%
2021 9
26.5%
2022 5
14.7%
ValueCountFrequency (%)
2022 5
14.7%
2021 9
26.5%
2020 6
17.6%
2019 4
11.8%
2018 4
11.8%
2017 6
17.6%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size400.0 B
신규
34 

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 34
100.0%

Length

2024-03-15T05:39:34.079724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:39:34.343658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 34
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size400.0 B
개인
20 
법인
14 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 20
58.8%
법인 14
41.2%

Length

2024-03-15T05:39:34.528930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:39:34.802512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 20
58.8%
법인 14
41.2%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)61.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47
Minimum1
Maximum406
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-03-15T05:39:34.976682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.25
median9
Q360
95-th percentile185.55
Maximum406
Range405
Interquartile range (IQR)58.75

Descriptive statistics

Standard deviation90.114405
Coefficient of variation (CV)1.9173278
Kurtosis10.558691
Mean47
Median Absolute Deviation (MAD)8
Skewness3.2067296
Sum1598
Variance8120.6061
MonotonicityNot monotonic
2024-03-15T05:39:35.198643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 9
26.5%
5 3
 
8.8%
7 2
 
5.9%
2 2
 
5.9%
64 2
 
5.9%
15 1
 
2.9%
85 1
 
2.9%
11 1
 
2.9%
96 1
 
2.9%
41 1
 
2.9%
Other values (11) 11
32.4%
ValueCountFrequency (%)
1 9
26.5%
2 2
 
5.9%
5 3
 
8.8%
7 2
 
5.9%
8 1
 
2.9%
10 1
 
2.9%
11 1
 
2.9%
15 1
 
2.9%
20 1
 
2.9%
35 1
 
2.9%
ValueCountFrequency (%)
406 1
2.9%
350 1
2.9%
97 1
2.9%
96 1
2.9%
93 1
2.9%
85 1
2.9%
70 1
2.9%
64 2
5.9%
48 1
2.9%
43 1
2.9%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean842347.06
Minimum60
Maximum6791510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-03-15T05:39:35.557542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile370.5
Q116995
median136740
Q3885475
95-th percentile4244891.5
Maximum6791510
Range6791450
Interquartile range (IQR)868480

Descriptive statistics

Standard deviation1609105.7
Coefficient of variation (CV)1.9102646
Kurtosis8.4189685
Mean842347.06
Median Absolute Deviation (MAD)133985
Skewness2.8984113
Sum28639800
Variance2.5892213 × 1012
MonotonicityNot monotonic
2024-03-15T05:39:35.986524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
40330 1
 
2.9%
1502160 1
 
2.9%
9450 1
 
2.9%
6791510 1
 
2.9%
1482980 1
 
2.9%
90100 1
 
2.9%
1166060 1
 
2.9%
11330 1
 
2.9%
9720 1
 
2.9%
1171300 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
60 1
2.9%
260 1
2.9%
430 1
2.9%
7200 1
2.9%
7590 1
2.9%
9020 1
2.9%
9450 1
2.9%
9720 1
2.9%
11330 1
2.9%
33990 1
2.9%
ValueCountFrequency (%)
6791510 1
2.9%
6271390 1
2.9%
3153700 1
2.9%
1998610 1
2.9%
1502160 1
2.9%
1482980 1
2.9%
1171300 1
2.9%
1166060 1
2.9%
912360 1
2.9%
804820 1
2.9%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.97059
Minimum1
Maximum699
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-03-15T05:39:36.381706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14.25
median36
Q3145.5
95-th percentile376.25
Maximum699
Range698
Interquartile range (IQR)141.25

Descriptive statistics

Standard deviation159.88338
Coefficient of variation (CV)1.5834649
Kurtosis7.6061946
Mean100.97059
Median Absolute Deviation (MAD)34
Skewness2.665537
Sum3433
Variance25562.696
MonotonicityNot monotonic
2024-03-15T05:39:36.924348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 3
 
8.8%
2 3
 
8.8%
3 2
 
5.9%
153 2
 
5.9%
41 1
 
2.9%
17 1
 
2.9%
12 1
 
2.9%
245 1
 
2.9%
64 1
 
2.9%
699 1
 
2.9%
Other values (18) 18
52.9%
ValueCountFrequency (%)
1 3
8.8%
2 3
8.8%
3 2
5.9%
4 1
 
2.9%
5 1
 
2.9%
12 1
 
2.9%
15 1
 
2.9%
17 1
 
2.9%
21 1
 
2.9%
23 1
 
2.9%
ValueCountFrequency (%)
699 1
2.9%
607 1
2.9%
252 1
2.9%
245 1
2.9%
201 1
2.9%
188 1
2.9%
182 1
2.9%
153 2
5.9%
123 1
2.9%
112 1
2.9%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1395837.1
Minimum490
Maximum9807080
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-03-15T05:39:37.342946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum490
5-th percentile8662.5
Q199050
median366660
Q31601177.5
95-th percentile6718389
Maximum9807080
Range9806590
Interquartile range (IQR)1502127.5

Descriptive statistics

Standard deviation2310037.2
Coefficient of variation (CV)1.6549476
Kurtosis6.7565376
Mean1395837.1
Median Absolute Deviation (MAD)358335
Skewness2.6066927
Sum47458460
Variance5.336272 × 1012
MonotonicityNot monotonic
2024-03-15T05:39:37.791873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
167050 1
 
2.9%
3336620 1
 
2.9%
9450 1
 
2.9%
8411470 1
 
2.9%
1586680 1
 
2.9%
187600 1
 
2.9%
1166060 1
 
2.9%
45320 1
 
2.9%
9780 1
 
2.9%
1834460 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
490 1
2.9%
7200 1
2.9%
9450 1
2.9%
9780 1
2.9%
33990 1
2.9%
45320 1
2.9%
55110 1
2.9%
72330 1
2.9%
97500 1
2.9%
103700 1
2.9%
ValueCountFrequency (%)
9807080 1
2.9%
8411470 1
2.9%
5806730 1
2.9%
3336620 1
2.9%
2655570 1
2.9%
2199690 1
2.9%
1834460 1
2.9%
1619960 1
2.9%
1606010 1
2.9%
1586680 1
2.9%

누적미환급금액증감
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9525.3771
Minimum0
Maximum256950
Zeros5
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-03-15T05:39:38.176384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115.0925
median90.56
Q3254.25
95-th percentile22851.25
Maximum256950
Range256950
Interquartile range (IQR)239.1575

Descriptive statistics

Standard deviation44875.404
Coefficient of variation (CV)4.711142
Kurtosis30.35722
Mean9525.3771
Median Absolute Deviation (MAD)90.52
Skewness5.4310175
Sum323862.82
Variance2.0138019 × 109
MonotonicityNot monotonic
2024-03-15T05:39:38.506537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.0 5
 
14.7%
314.0 1
 
2.9%
1185.0 1
 
2.9%
0.08 1
 
2.9%
84.12 1
 
2.9%
18.37 1
 
2.9%
32.87 1
 
2.9%
56.38 1
 
2.9%
1.0 1
 
2.9%
122.0 1
 
2.9%
Other values (20) 20
58.8%
ValueCountFrequency (%)
0.0 5
14.7%
0.08 1
 
2.9%
1.0 1
 
2.9%
7.0 1
 
2.9%
14.0 1
 
2.9%
18.37 1
 
2.9%
24.0 1
 
2.9%
32.87 1
 
2.9%
54.0 1
 
2.9%
56.38 1
 
2.9%
ValueCountFrequency (%)
256950.0 1
2.9%
59196.0 1
2.9%
3281.0 1
2.9%
1185.0 1
2.9%
353.0 1
2.9%
314.0 1
2.9%
300.0 1
2.9%
295.0 1
2.9%
255.0 1
2.9%
252.0 1
2.9%

Interactions

2024-03-15T05:39:28.686562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:19.846703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:21.353576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:23.293561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:25.417915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:27.340460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:28.832470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:20.080684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:21.612105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:23.677434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:25.860447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:27.575156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:28.992433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:20.340604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:21.877212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:24.021447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:26.257713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:27.844073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:29.194766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:20.598366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:22.242393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:24.331422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:26.616992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:28.108030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:29.353944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:20.851121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:22.665246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:24.729751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:26.875751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:28.375276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:29.819718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:21.112762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:22.998413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:25.058659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:27.139786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:39:28.541245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:39:38.701137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.0000.000
과세년도0.0001.0000.0000.2070.0000.0000.0000.249
납세자유형0.0000.0001.0000.2200.0750.1680.0000.109
당해미환급건수0.0000.2070.2201.0000.9180.8890.8940.000
당해미환급금액0.0000.0000.0750.9181.0000.7780.8810.000
누적미환급건수0.0000.0000.1680.8890.7781.0000.9150.000
누적미환급금액0.0000.0000.0000.8940.8810.9151.0000.000
누적미환급금액증감0.0000.2490.1090.0000.0000.0000.0001.000
2024-03-15T05:39:38.928342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형세목명
납세자유형1.0000.000
세목명0.0001.000
2024-03-15T05:39:39.187069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명납세자유형
과세년도1.0000.2880.4300.1250.202-0.5440.0000.000
당해미환급건수0.2881.0000.9130.9270.902-0.0290.0000.250
당해미환급금액0.4300.9131.0000.8290.905-0.2030.0000.063
누적미환급건수0.1250.9270.8291.0000.9310.2570.0000.091
누적미환급금액0.2020.9020.9050.9311.0000.1460.0000.000
누적미환급금액증감-0.544-0.029-0.2030.2570.1461.0000.0000.172
세목명0.0000.0000.0000.0000.0000.0001.0000.000
납세자유형0.0000.2500.0630.0910.0000.1720.0001.000

Missing values

2024-03-15T05:39:30.099227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:39:30.648813image/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
0전라남도장성군46880재산세2017신규개인154033041167050314.0
1전라남도장성군46880자동차세2017신규개인433188601531123210252.0
2전라남도장성군46880자동차세2017신규법인51501202129596097.0
3전라남도장성군46880지방소득세2017신규개인726840039629290134.0
4전라남도장성군46880지방소득세2017신규법인1260315417059196.0
5전라남도장성군46880등록면허세2017신규법인17200172000.0
6전라남도장성군46880자동차세2018신규개인354412301881564440255.0
7전라남도장성군46880자동차세2018신규법인29020233049803281.0
8전라남도장성군46880지방소득세2018신규개인2017840059807690353.0
9전라남도장성군46880지방소득세2018신규법인1604154230256950.0
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
24전라남도장성군46880재산세2021신규법인51166060511660600.0
25전라남도장성군46880주민세2021신규개인111330345320300.0
26전라남도장성군46880지방소득세2021신규개인7015021601823336620122.0
27전라남도장성군46880지방소득세2021신규법인19720297801.0
28전라남도장성군46880취득세2021신규법인1551101551100.0
29전라남도장성군46880자동차세2022신규개인3506271390699980708056.38
30전라남도장성군46880자동차세2022신규법인931998610153265557032.87
31전라남도장성군46880재산세2022신규개인418048206495267018.37
32전라남도장성군46880지방소득세2022신규개인963153700245580673084.12
33전라남도장성군46880지방소득세2022신규법인117227012723300.08