Overview

Dataset statistics

Number of variables12
Number of observations78
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.0 KiB
Average record size in memory104.6 B

Variable types

Numeric6
Categorical6

Dataset

Description미환급 유형별(미환급 사유) 미환급금 현황 및 연간 누적률 제공자치단체의 환급금 해소노력 확인 가능세목별, 납세자 유형별 미환급 유형 제공
Author경상북도 경산시
URLhttps://www.data.go.kr/data/15079720/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 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
미환급유형 is highly overall correlated with 납세자유형High correlation
납세자유형 is highly overall correlated with 미환급유형High correlation
구분 has unique valuesUnique

Reproduction

Analysis started2024-03-14 16:45:12.220464
Analysis finished2024-03-14 16:45:22.848960
Duration10.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.5
Minimum1
Maximum78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size830.0 B
2024-03-15T01:45:23.028857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.85
Q120.25
median39.5
Q358.75
95-th percentile74.15
Maximum78
Range77
Interquartile range (IQR)38.5

Descriptive statistics

Standard deviation22.660538
Coefficient of variation (CV)0.57368452
Kurtosis-1.2
Mean39.5
Median Absolute Deviation (MAD)19.5
Skewness0
Sum3081
Variance513.5
MonotonicityStrictly increasing
2024-03-15T01:45:23.370236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
51 1
 
1.3%
58 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
50 1
 
1.3%
Other values (68) 68
87.2%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
78 1
1.3%
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size752.0 B
경상북도
78 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 78
100.0%

Length

2024-03-15T01:45:23.610713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:45:23.773327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 78
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size752.0 B
경산시
78 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경산시 78
100.0%

Length

2024-03-15T01:45:24.050911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:45:24.312372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경산시 78
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size752.0 B
47290
78 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47290
2nd row47290
3rd row47290
4th row47290
5th row47290

Common Values

ValueCountFrequency (%)
47290 78
100.0%

Length

2024-03-15T01:45:24.499112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:45:24.663180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47290 78
100.0%

세목명
Categorical

Distinct6
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size752.0 B
자동차세
28 
지방소득세
26 
재산세
9 
주민세
7 
등록면허세
5 

Length

Max length5
Median length4
Mean length4.1538462
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 28
35.9%
지방소득세 26
33.3%
재산세 9
 
11.5%
주민세 7
 
9.0%
등록면허세 5
 
6.4%
취득세 3
 
3.8%

Length

2024-03-15T01:45:24.860096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:45:25.086746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 28
35.9%
지방소득세 26
33.3%
재산세 9
 
11.5%
주민세 7
 
9.0%
등록면허세 5
 
6.4%
취득세 3
 
3.8%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.5256
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size830.0 B
2024-03-15T01:45:25.307696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2019
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.8070882
Coefficient of variation (CV)0.00089480825
Kurtosis-1.3802844
Mean2019.5256
Median Absolute Deviation (MAD)1
Skewness0.13361479
Sum157523
Variance3.2655678
MonotonicityNot monotonic
2024-03-15T01:45:25.610882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2022 19
24.4%
2018 16
20.5%
2019 14
17.9%
2017 12
15.4%
2020 10
12.8%
2021 7
 
9.0%
ValueCountFrequency (%)
2017 12
15.4%
2018 16
20.5%
2019 14
17.9%
2020 10
12.8%
2021 7
 
9.0%
2022 19
24.4%
ValueCountFrequency (%)
2022 19
24.4%
2021 7
 
9.0%
2020 10
12.8%
2019 14
17.9%
2018 16
20.5%
2017 12
15.4%

미환급유형
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size752.0 B
신규
40 
사망
14 
폐업 또는 부도
8 
국외이주
7 
주소불명
6 
Other values (2)
 
3

Length

Max length8
Median length2
Mean length3.0769231
Min length2

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row신규
2nd row국외이주
3rd row기타
4th row사망
5th row신규

Common Values

ValueCountFrequency (%)
신규 40
51.3%
사망 14
 
17.9%
폐업 또는 부도 8
 
10.3%
국외이주 7
 
9.0%
주소불명 6
 
7.7%
송달분 미수령 2
 
2.6%
기타 1
 
1.3%

Length

2024-03-15T01:45:25.836722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:45:26.049540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 40
41.7%
사망 14
 
14.6%
폐업 8
 
8.3%
또는 8
 
8.3%
부도 8
 
8.3%
국외이주 7
 
7.3%
주소불명 6
 
6.2%
송달분 2
 
2.1%
미수령 2
 
2.1%
기타 1
 
1.0%

납세자유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size752.0 B
개인
53 
법인
25 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 53
67.9%
법인 25
32.1%

Length

2024-03-15T01:45:26.280187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:45:26.449157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 53
67.9%
법인 25
32.1%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.987179
Minimum1
Maximum666
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size830.0 B
2024-03-15T01:45:26.740733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2.5
Q313.25
95-th percentile149.05
Maximum666
Range665
Interquartile range (IQR)12.25

Descriptive statistics

Standard deviation110.76364
Coefficient of variation (CV)3.0778639
Kurtosis24.036132
Mean35.987179
Median Absolute Deviation (MAD)1.5
Skewness4.7942091
Sum2807
Variance12268.584
MonotonicityNot monotonic
2024-03-15T01:45:27.159079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 27
34.6%
2 12
15.4%
6 4
 
5.1%
9 3
 
3.8%
8 3
 
3.8%
3 3
 
3.8%
17 2
 
2.6%
5 2
 
2.6%
7 2
 
2.6%
62 1
 
1.3%
Other values (19) 19
24.4%
ValueCountFrequency (%)
1 27
34.6%
2 12
15.4%
3 3
 
3.8%
4 1
 
1.3%
5 2
 
2.6%
6 4
 
5.1%
7 2
 
2.6%
8 3
 
3.8%
9 3
 
3.8%
11 1
 
1.3%
ValueCountFrequency (%)
666 1
1.3%
631 1
1.3%
332 1
1.3%
172 1
1.3%
145 1
1.3%
99 1
1.3%
82 1
1.3%
73 1
1.3%
71 1
1.3%
62 1
1.3%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION 

Distinct77
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean615252.56
Minimum10
Maximum17609930
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size830.0 B
2024-03-15T01:45:27.581025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile125.5
Q17997.5
median36350
Q3217080
95-th percentile2022580
Maximum17609930
Range17609920
Interquartile range (IQR)209082.5

Descriptive statistics

Standard deviation2379547.5
Coefficient of variation (CV)3.8675946
Kurtosis39.124442
Mean615252.56
Median Absolute Deviation (MAD)36055
Skewness6.0744226
Sum47989700
Variance5.6622463 × 1012
MonotonicityNot monotonic
2024-03-15T01:45:28.250648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 2
 
2.6%
90630 1
 
1.3%
460 1
 
1.3%
8140 1
 
1.3%
107420 1
 
1.3%
22330 1
 
1.3%
29400 1
 
1.3%
44080 1
 
1.3%
1314990 1
 
1.3%
138510 1
 
1.3%
Other values (67) 67
85.9%
ValueCountFrequency (%)
10 1
1.3%
30 1
1.3%
100 2
2.6%
130 1
1.3%
460 1
1.3%
500 1
1.3%
550 1
1.3%
700 1
1.3%
730 1
1.3%
930 1
1.3%
ValueCountFrequency (%)
17609930 1
1.3%
11291430 1
1.3%
2941940 1
1.3%
2810870 1
1.3%
1883470 1
1.3%
1585080 1
1.3%
1314990 1
1.3%
891590 1
1.3%
737810 1
1.3%
657320 1
1.3%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)35.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean174.51282
Minimum1
Maximum1007
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size830.0 B
2024-03-15T01:45:29.214411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median35
Q3182.25
95-th percentile1007
Maximum1007
Range1006
Interquartile range (IQR)175.25

Descriptive statistics

Standard deviation292.95183
Coefficient of variation (CV)1.6786837
Kurtosis3.2173264
Mean174.51282
Median Absolute Deviation (MAD)34
Skewness2.1002752
Sum13612
Variance85820.773
MonotonicityNot monotonic
2024-03-15T01:45:29.594409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
7 7
 
9.0%
1 6
 
7.7%
3 6
 
7.7%
1007 5
 
6.4%
190 5
 
6.4%
159 4
 
5.1%
9 4
 
5.1%
25 3
 
3.8%
91 3
 
3.8%
36 3
 
3.8%
Other values (18) 32
41.0%
ValueCountFrequency (%)
1 6
7.7%
2 1
 
1.3%
3 6
7.7%
4 1
 
1.3%
5 1
 
1.3%
6 2
 
2.6%
7 7
9.0%
8 2
 
2.6%
9 4
5.1%
12 3
3.8%
ValueCountFrequency (%)
1007 5
6.4%
906 3
3.8%
581 1
 
1.3%
374 3
3.8%
321 1
 
1.3%
282 2
 
2.6%
190 5
6.4%
159 4
5.1%
157 3
3.8%
91 3
3.8%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)55.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2750870.9
Minimum100
Maximum21225090
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size830.0 B
2024-03-15T01:45:30.059890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile3430
Q163430
median589160
Q32817210
95-th percentile15025990
Maximum21225090
Range21224990
Interquartile range (IQR)2753780

Descriptive statistics

Standard deviation5215958.3
Coefficient of variation (CV)1.8961116
Kurtosis5.7006308
Mean2750870.9
Median Absolute Deviation (MAD)585750
Skewness2.5747844
Sum2.1456793 × 108
Variance2.7206221 × 1013
MonotonicityNot monotonic
2024-03-15T01:45:30.795412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1405410 5
 
6.4%
15025990 5
 
6.4%
3229840 4
 
5.1%
2044330 3
 
3.8%
3121320 3
 
3.8%
100890 3
 
3.8%
21225090 3
 
3.8%
2817210 3
 
3.8%
1341310 3
 
3.8%
3430 2
 
2.6%
Other values (33) 44
56.4%
ValueCountFrequency (%)
100 1
1.3%
130 1
1.3%
3390 1
1.3%
3430 2
2.6%
4630 1
1.3%
7660 1
1.3%
11830 1
1.3%
15170 1
1.3%
18210 2
2.6%
19140 1
1.3%
ValueCountFrequency (%)
21225090 3
3.8%
15025990 5
6.4%
5199780 1
 
1.3%
5022760 1
 
1.3%
3229840 4
5.1%
3121320 3
3.8%
2818530 1
 
1.3%
2817210 3
3.8%
2544820 2
 
2.6%
2044330 3
3.8%

Interactions

2024-03-15T01:45:20.938533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:12.848560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:14.414143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:15.675319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:17.319771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:19.065417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:21.239860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:13.200828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:14.680105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:16.194609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:17.520518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:19.379050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:21.493335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:13.460504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:14.870716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:16.441499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:17.775472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:19.635389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:21.758640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:13.678011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:15.117343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:16.688954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:18.143429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:19.926821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:22.002648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:13.914897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:15.385656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:16.954410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:18.477026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:20.243907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:22.147997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:14.165263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:15.533022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:17.180068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:18.776168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:20.545229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T01:45:31.160432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액
구분1.0000.5130.9700.0000.0000.1300.4620.7190.878
세목명0.5131.0000.0000.0000.1410.0000.0000.2170.160
과세년도0.9700.0001.0000.0000.0000.4760.3850.5330.798
미환급유형0.0000.0000.0001.0000.5050.0000.0000.3030.266
납세자유형0.0000.1410.0000.5051.0000.0850.0000.4040.321
당해미환급건수0.1300.0000.4760.0000.0851.0000.7570.7830.860
당해미환급금액0.4620.0000.3850.0000.0000.7571.0000.6360.672
누적미환급건수0.7190.2170.5330.3030.4040.7830.6361.0000.921
누적미환급금액0.8780.1600.7980.2660.3210.8600.6720.9211.000
2024-03-15T01:45:31.413926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미환급유형납세자유형세목명
미환급유형1.0000.5240.000
납세자유형0.5241.0000.094
세목명0.0000.0941.000
2024-03-15T01:45:31.617967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분과세년도당해미환급건수당해미환급금액누적미환급건수누적미환급금액세목명미환급유형납세자유형
구분1.000-0.1430.037-0.098-0.066-0.1000.2890.0000.000
과세년도-0.1431.0000.2170.2430.2570.3590.0000.0000.000
당해미환급건수0.0370.2171.0000.8410.5830.5740.0000.0000.099
당해미환급금액-0.0980.2430.8411.0000.5720.6820.0000.0000.000
누적미환급건수-0.0660.2570.5830.5721.0000.9240.1260.1050.417
누적미환급금액-0.1000.3590.5740.6820.9241.0000.1030.1680.384
세목명0.2890.0000.0000.0000.1260.1031.0000.0000.094
미환급유형0.0000.0000.0000.0000.1050.1680.0001.0000.524
납세자유형0.0000.0000.0990.0000.4170.3840.0940.5241.000

Missing values

2024-03-15T01:45:22.358672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:45:22.649880image/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

구분시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액
01경상북도경산시47290등록면허세2022신규개인690630795260
12경상북도경산시47290자동차세2022국외이주개인1550100715025990
23경상북도경산시47290자동차세2022기타개인2117100100715025990
34경상북도경산시47290자동차세2022사망개인17276230100715025990
45경상북도경산시47290자동차세2022신규개인63111291430100715025990
56경상북도경산시47290자동차세2022주소불명개인222290100715025990
67경상북도경산시47290자동차세2022신규법인4452153063670720
78경상북도경산시47290재산세2022사망개인233260891822360
89경상북도경산시47290재산세2022신규개인61737810891822360
910경상북도경산시47290재산세2022신규법인44239106530330
구분시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액
6869경상북도경산시47290지방소득세2020주소불명개인31244201593229840
6970경상북도경산시47290지방소득세2020신규법인2730964020
7071경상북도경산시47290지방소득세2020폐업 또는 부도법인1100964020
7172경상북도경산시47290등록면허세2021신규개인17200211830
7273경상북도경산시47290자동차세2021신규개인33229419405815199780
7374경상북도경산시47290자동차세2021신규법인99625034304170
7475경상북도경산시47290재산세2021신규개인822810870912818530
7576경상북도경산시47290주민세2021신규개인111330326050
7677경상북도경산시47290지방소득세2021신규개인17218834703215022760
7778경상북도경산시47290지방소득세2021신규법인679501571970