Overview

Dataset statistics

Number of variables12
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory106.1 B

Variable types

Categorical6
Numeric6

Dataset

Description부산광역시 동래구 지방세 미환급 현황(2017년~2022년)으로 자치단체코드, 세목명, 과세년도, 미환급유형, 납세자 유형, 당해 미환급건수, 미환급금액, 누적미환급건수, 누적미환급금액, 누적미환급금액증감 등에 대한 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15087056/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 3 other fieldsHigh correlation
누적미환급금액 is highly overall correlated with 당해미환급건수 and 2 other fieldsHigh correlation
누적미환급금액증감 is highly overall correlated with 누적미환급건수High correlation
당해미환급금액 has unique valuesUnique
누적미환급금액 has unique valuesUnique
누적미환급금액증감 has 8 (19.0%) zerosZeros

Reproduction

Analysis started2023-12-12 18:05:21.448800
Analysis finished2023-12-12 18:05:26.308753
Duration4.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
부산광역시
42 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 42
100.0%

Length

2023-12-13T03:05:26.373634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:26.481979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 42
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
동래구
42 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동래구 42
100.0%

Length

2023-12-13T03:05:26.586899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:26.684682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동래구 42
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
26260
42 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26260
2nd row26260
3rd row26260
4th row26260
5th row26260

Common Values

ValueCountFrequency (%)
26260 42
100.0%

Length

2023-12-13T03:05:26.805853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:26.938588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26260 42
100.0%

세목명
Categorical

Distinct6
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size468.0 B
자동차세
12 
지방소득세
12 
주민세
6 
등록면허세
5 
재산세
5 

Length

Max length5
Median length4
Mean length4.0952381
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 12
28.6%
지방소득세 12
28.6%
주민세 6
14.3%
등록면허세 5
11.9%
재산세 5
11.9%
취득세 2
 
4.8%

Length

2023-12-13T03:05:27.073875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:27.208803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 12
28.6%
지방소득세 12
28.6%
주민세 6
14.3%
등록면허세 5
11.9%
재산세 5
11.9%
취득세 2
 
4.8%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.6905
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-13T03:05:27.312990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018.25
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation1.6452162
Coefficient of variation (CV)0.00081458829
Kurtosis-1.1564736
Mean2019.6905
Median Absolute Deviation (MAD)1
Skewness-0.13057563
Sum84827
Variance2.7067364
MonotonicityIncreasing
2023-12-13T03:05:27.419527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2019 9
21.4%
2021 9
21.4%
2022 7
16.7%
2018 6
14.3%
2020 6
14.3%
2017 5
11.9%
ValueCountFrequency (%)
2017 5
11.9%
2018 6
14.3%
2019 9
21.4%
2020 6
14.3%
2021 9
21.4%
2022 7
16.7%
ValueCountFrequency (%)
2022 7
16.7%
2021 9
21.4%
2020 6
14.3%
2019 9
21.4%
2018 6
14.3%
2017 5
11.9%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
신규
42 

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 42
100.0%

Length

2023-12-13T03:05:27.540600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:27.650028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 42
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
개인
26 
법인
16 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 26
61.9%
법인 16
38.1%

Length

2023-12-13T03:05:27.755386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:27.859794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 26
61.9%
법인 16
38.1%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)59.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79.619048
Minimum1
Maximum836
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-13T03:05:27.969689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median8
Q337.5
95-th percentile573.15
Maximum836
Range835
Interquartile range (IQR)35.5

Descriptive statistics

Standard deviation184.81764
Coefficient of variation (CV)2.3212741
Kurtosis8.539356
Mean79.619048
Median Absolute Deviation (MAD)7
Skewness3.0002949
Sum3344
Variance34157.559
MonotonicityNot monotonic
2023-12-13T03:05:28.097233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 9
21.4%
8 3
 
7.1%
2 3
 
7.1%
7 2
 
4.8%
4 2
 
4.8%
10 2
 
4.8%
3 2
 
4.8%
26 2
 
4.8%
581 1
 
2.4%
9 1
 
2.4%
Other values (15) 15
35.7%
ValueCountFrequency (%)
1 9
21.4%
2 3
 
7.1%
3 2
 
4.8%
4 2
 
4.8%
5 1
 
2.4%
7 2
 
4.8%
8 3
 
7.1%
9 1
 
2.4%
10 2
 
4.8%
14 1
 
2.4%
ValueCountFrequency (%)
836 1
2.4%
613 1
2.4%
581 1
2.4%
424 1
2.4%
134 1
2.4%
125 1
2.4%
120 1
2.4%
116 1
2.4%
74 1
2.4%
50 1
2.4%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1248942.6
Minimum10
Maximum11974120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-13T03:05:28.227122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile407.5
Q139047.5
median128665
Q3718197.5
95-th percentile7517462.5
Maximum11974120
Range11974110
Interquartile range (IQR)679150

Descriptive statistics

Standard deviation2641361.6
Coefficient of variation (CV)2.1148783
Kurtosis7.5944985
Mean1248942.6
Median Absolute Deviation (MAD)127150
Skewness2.8037946
Sum52455590
Variance6.9767911 × 1012
MonotonicityNot monotonic
2023-12-13T03:05:28.371131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
343860 1
 
2.4%
7327700 1
 
2.4%
2624620 1
 
2.4%
665970 1
 
2.4%
21710 1
 
2.4%
8284380 1
 
2.4%
233880 1
 
2.4%
2706260 1
 
2.4%
103680 1
 
2.4%
38610 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
10 1
2.4%
20 1
2.4%
370 1
2.4%
1120 1
2.4%
1910 1
2.4%
2890 1
2.4%
5780 1
2.4%
18540 1
2.4%
21710 1
2.4%
36320 1
2.4%
ValueCountFrequency (%)
11974120 1
2.4%
8284380 1
2.4%
7527450 1
2.4%
7327700 1
2.4%
2706260 1
2.4%
2624620 1
2.4%
2551020 1
2.4%
1937540 1
2.4%
1273540 1
2.4%
764690 1
2.4%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.52381
Minimum1
Maximum1233
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-13T03:05:28.509116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14.25
median14.5
Q377.5
95-th percentile823.1
Maximum1233
Range1232
Interquartile range (IQR)73.25

Descriptive statistics

Standard deviation282.70033
Coefficient of variation (CV)2.1826128
Kurtosis7.9048494
Mean129.52381
Median Absolute Deviation (MAD)13.5
Skewness2.894467
Sum5440
Variance79919.475
MonotonicityNot monotonic
2023-12-13T03:05:28.670644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 6
 
14.3%
6 2
 
4.8%
5 2
 
4.8%
8 2
 
4.8%
3 2
 
4.8%
4 2
 
4.8%
80 1
 
2.4%
616 1
 
2.4%
44 1
 
2.4%
82 1
 
2.4%
Other values (22) 22
52.4%
ValueCountFrequency (%)
1 6
14.3%
2 1
 
2.4%
3 2
 
4.8%
4 2
 
4.8%
5 2
 
4.8%
6 2
 
4.8%
8 2
 
4.8%
9 1
 
2.4%
10 1
 
2.4%
11 1
 
2.4%
ValueCountFrequency (%)
1233 1
2.4%
1053 1
2.4%
834 1
2.4%
616 1
2.4%
298 1
2.4%
246 1
2.4%
220 1
2.4%
186 1
2.4%
121 1
2.4%
82 1
2.4%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1972972.9
Minimum10
Maximum18933740
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-13T03:05:28.871926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile1947.5
Q141460
median430230
Q31180725
95-th percentile11278898
Maximum18933740
Range18933730
Interquartile range (IQR)1139265

Descriptive statistics

Standard deviation4137048.6
Coefficient of variation (CV)2.0968604
Kurtosis7.9166277
Mean1972972.9
Median Absolute Deviation (MAD)394500
Skewness2.8467037
Sum82864860
Variance1.7115171 × 1013
MonotonicityNot monotonic
2023-12-13T03:05:29.033402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
503660 1
 
2.4%
11122690 1
 
2.4%
4890860 1
 
2.4%
711650 1
 
2.4%
40260 1
 
2.4%
11287120 1
 
2.4%
394120 1
 
2.4%
2751320 1
 
2.4%
155290 1
 
2.4%
40170 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
10 1
2.4%
370 1
2.4%
1930 1
2.4%
2280 1
2.4%
3360 1
2.4%
4480 1
2.4%
5780 1
2.4%
18550 1
2.4%
36320 1
2.4%
40170 1
2.4%
ValueCountFrequency (%)
18933740 1
2.4%
13551990 1
2.4%
11287120 1
2.4%
11122690 1
2.4%
4890860 1
2.4%
3820660 1
2.4%
3496670 1
2.4%
2751320 1
2.4%
2187520 1
2.4%
1606150 1
2.4%

누적미환급금액증감
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean312.58119
Minimum0
Maximum9550
Zeros8
Zeros (%)19.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-13T03:05:29.188284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.745
median48.12
Q384.1975
95-th percentile565.582
Maximum9550
Range9550
Interquartile range (IQR)79.4525

Descriptive statistics

Standard deviation1467.6792
Coefficient of variation (CV)4.6953536
Kurtosis41.077413
Mean312.58119
Median Absolute Deviation (MAD)40.805
Skewness6.3795837
Sum13128.41
Variance2154082.3
MonotonicityNot monotonic
2023-12-13T03:05:29.341043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0.0 8
 
19.0%
46.47 1
 
2.4%
36.25 1
 
2.4%
68.51 1
 
2.4%
1.67 1
 
2.4%
49.78 1
 
2.4%
4.04 1
 
2.4%
51.79 1
 
2.4%
282.97 1
 
2.4%
7.77 1
 
2.4%
Other values (25) 25
59.5%
ValueCountFrequency (%)
0.0 8
19.0%
0.05 1
 
2.4%
1.67 1
 
2.4%
4.04 1
 
2.4%
6.86 1
 
2.4%
7.77 1
 
2.4%
8.98 1
 
2.4%
9.14 1
 
2.4%
16.26 1
 
2.4%
19.37 1
 
2.4%
ValueCountFrequency (%)
9550.0 1
2.4%
741.22 1
2.4%
579.56 1
2.4%
300.0 1
2.4%
282.97 1
2.4%
181.13 1
2.4%
178.64 1
2.4%
132.15 1
2.4%
122.75 1
2.4%
86.35 1
2.4%

Interactions

2023-12-13T03:05:25.277851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:21.799958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:22.415634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:22.945078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:23.514977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:24.096902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:25.399636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:21.896792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:22.513421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:23.036365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:23.602367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:24.235796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:25.518793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:21.985391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:22.589247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:23.112720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:23.697670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:24.353717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:25.628774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:22.089312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:22.678385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:23.196733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:23.795842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:24.473385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:25.740670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:22.196301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:22.755807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:23.312171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:23.890242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:24.596550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:25.885565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:22.311327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:22.853708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:23.425056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:23.991870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:25.165427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:05:29.509848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.0000.245
과세년도0.0001.0000.0000.1640.0000.1410.0810.163
납세자유형0.0000.0001.0000.2380.2320.0440.3270.000
당해미환급건수0.0000.1640.2381.0000.8841.0000.9910.000
당해미환급금액0.0000.0000.2320.8841.0000.9060.9410.000
누적미환급건수0.0000.1410.0441.0000.9061.0000.9440.000
누적미환급금액0.0000.0810.3270.9910.9410.9441.0000.000
누적미환급금액증감0.2450.1630.0000.0000.0000.0000.0001.000
2023-12-13T03:05:29.686549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형세목명
납세자유형1.0000.000
세목명0.0001.000
2023-12-13T03:05:29.793631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명납세자유형
과세년도1.0000.3050.3590.3460.4170.2920.0000.000
당해미환급건수0.3051.0000.8520.9760.8800.3780.0000.153
당해미환급금액0.3590.8521.0000.8070.9730.1260.0000.268
누적미환급건수0.3460.9760.8071.0000.8640.5010.0000.000
누적미환급금액0.4170.8800.9730.8641.0000.2850.0000.217
누적미환급금액증감0.2920.3780.1260.5010.2851.0000.1580.000
세목명0.0000.0000.0000.0000.0000.1581.0000.000
납세자유형0.0000.1530.2680.0000.2170.0000.0001.000

Missing values

2023-12-13T03:05:26.043144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:05:26.238978image/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
0부산광역시동래구26260자동차세2017신규개인503438608050366046.47
1부산광역시동래구26260자동차세2017신규법인15780157800.0
2부산광역시동래구26260주민세2017신규개인137013700.0
3부산광역시동래구26260지방소득세2017신규개인2119233043540690181.13
4부산광역시동래구26260지방소득세2017신규법인428906336016.26
5부산광역시동래구26260등록면허세2018신규개인1101100.0
6부산광역시동래구26260자동차세2018신규개인41410320121913980122.75
7부산광역시동래구26260자동차세2018신규법인8643509701308.98
8부산광역시동래구26260지방소득세2018신규개인2772895070126964074.17
9부산광역시동래구26260지방소득세2018신규법인2112084480300.0
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
32부산광역시동래구26260지방소득세2021신규개인42473277006161112269051.79
33부산광역시동래구26260지방소득세2021신규법인1012177026466340282.97
34부산광역시동래구26260취득세2021신규개인546751065038307.77
35부산광역시동래구26260등록면허세2022신규개인14036046611063.8
36부산광역시동래구26260자동차세2022신규개인613752745010531355199080.03
37부산광역시동래구26260자동차세2022신규법인265968604982532038.28
38부산광역시동래구26260재산세2022신규개인15190930511606150741.22
39부산광역시동래구26260주민세2022신규개인7895701212974044.85
40부산광역시동래구26260지방소득세2022신규개인8361197412012331893374058.12
41부산광역시동래구26260지방소득세2022신규법인97974032541880579.56