Overview

Dataset statistics

Number of variables12
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory112.3 B

Variable types

Categorical2
Numeric10

Dataset

Description- 2022년 12월말 기준 심사청구 유형별(개인, 법인), 청구세액 규모별 심사청구 처리 실적 - 심사청구는 국세청에서 처리함 - 각하 건수에 직권시정분 포함 - 세액을 부과한 과세관청을 지방국세청 기준으로 분류한 것임 - 감세액은 심사청구 처리 결과 감소하는 세액임 (단위 : 건, 백만원, %)
URLhttps://www.data.go.kr/data/15114194/fileData.do

Alerts

전년이월 건수 is highly overall correlated with 당년접수 건수 and 4 other fieldsHigh correlation
당년접수 건수 is highly overall correlated with 전년이월 건수 and 4 other fieldsHigh correlation
각하 건수 is highly overall correlated with 전년이월 건수 and 4 other fieldsHigh correlation
기각 건수 is highly overall correlated with 전년이월 건수 and 4 other fieldsHigh correlation
인용 건수 is highly overall correlated with 전년이월 건수 and 4 other fieldsHigh correlation
인용률 is highly overall correlated with 처리세액 and 2 other fieldsHigh correlation
처리세액 is highly overall correlated with 인용률 and 1 other fieldsHigh correlation
감세액 is highly overall correlated with 인용률 and 2 other fieldsHigh correlation
감세액 비율 is highly overall correlated with 인용률 and 1 other fieldsHigh correlation
이월건수 is highly overall correlated with 전년이월 건수 and 4 other fieldsHigh correlation
당년접수 건수 has unique valuesUnique
처리세액 has unique valuesUnique
전년이월 건수 has 1 (4.8%) zerosZeros
각하 건수 has 5 (23.8%) zerosZeros
인용 건수 has 1 (4.8%) zerosZeros
인용률 has 1 (4.8%) zerosZeros
감세액 has 1 (4.8%) zerosZeros
감세액 비율 has 1 (4.8%) zerosZeros

Reproduction

Analysis started2023-12-12 15:26:23.685543
Analysis finished2023-12-12 15:26:33.700147
Duration10.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분1
Categorical

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
청구세액 규모별
7 
개인
7 
법인
7 

Length

Max length8
Median length2
Mean length4
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row청구세액 규모별
2nd row청구세액 규모별
3rd row청구세액 규모별
4th row청구세액 규모별
5th row청구세액 규모별

Common Values

ValueCountFrequency (%)
청구세액 규모별 7
33.3%
개인 7
33.3%
법인 7
33.3%

Length

2023-12-13T00:26:33.765642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:26:33.873959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청구세액 7
25.0%
규모별 7
25.0%
개인 7
25.0%
법인 7
25.0%

구분2
Categorical

Distinct7
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
1천만 미만
3 
3천만 미만
3 
5천만 미만
3 
1억 미만
3 
5억 미만
3 
Other values (2)
6 

Length

Max length6
Median length6
Mean length5.7142857
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1천만 미만
2nd row3천만 미만
3rd row5천만 미만
4th row1억 미만
5th row5억 미만

Common Values

ValueCountFrequency (%)
1천만 미만 3
14.3%
3천만 미만 3
14.3%
5천만 미만 3
14.3%
1억 미만 3
14.3%
5억 미만 3
14.3%
10억 미만 3
14.3%
10억 이상 3
14.3%

Length

2023-12-13T00:26:34.000469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:26:34.153266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미만 18
42.9%
10억 6
 
14.3%
1천만 3
 
7.1%
3천만 3
 
7.1%
5천만 3
 
7.1%
1억 3
 
7.1%
5억 3
 
7.1%
이상 3
 
7.1%

전년이월 건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.285714
Minimum0
Maximum44
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:26:34.312188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median6
Q320
95-th percentile40
Maximum44
Range44
Interquartile range (IQR)16

Descriptive statistics

Standard deviation12.911789
Coefficient of variation (CV)1.0509595
Kurtosis0.9564686
Mean12.285714
Median Absolute Deviation (MAD)4
Skewness1.3620947
Sum258
Variance166.71429
MonotonicityNot monotonic
2023-12-13T00:26:34.430581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 3
14.3%
6 3
14.3%
4 2
 
9.5%
44 1
 
4.8%
5 1
 
4.8%
11 1
 
4.8%
7 1
 
4.8%
0 1
 
4.8%
1 1
 
4.8%
8 1
 
4.8%
Other values (6) 6
28.6%
ValueCountFrequency (%)
0 1
 
4.8%
1 1
 
4.8%
2 3
14.3%
4 2
9.5%
5 1
 
4.8%
6 3
14.3%
7 1
 
4.8%
8 1
 
4.8%
11 1
 
4.8%
15 1
 
4.8%
ValueCountFrequency (%)
44 1
4.8%
40 1
4.8%
31 1
4.8%
23 1
4.8%
21 1
4.8%
20 1
4.8%
15 1
4.8%
11 1
4.8%
8 1
4.8%
7 1
4.8%

당년접수 건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.571429
Minimum1
Maximum131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:26:34.562660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q111
median30
Q374
95-th percentile121
Maximum131
Range130
Interquartile range (IQR)63

Descriptive statistics

Standard deviation41.592753
Coefficient of variation (CV)0.89309593
Kurtosis-0.54584082
Mean46.571429
Median Absolute Deviation (MAD)24
Skewness0.8191626
Sum978
Variance1729.9571
MonotonicityNot monotonic
2023-12-13T00:26:35.034410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
131 1
 
4.8%
78 1
 
4.8%
1 1
 
4.8%
6 1
 
4.8%
30 1
 
4.8%
11 1
 
4.8%
13 1
 
4.8%
20 1
 
4.8%
10 1
 
4.8%
8 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
6 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
11 1
4.8%
13 1
4.8%
18 1
4.8%
20 1
4.8%
24 1
4.8%
ValueCountFrequency (%)
131 1
4.8%
121 1
4.8%
119 1
4.8%
89 1
4.8%
78 1
4.8%
74 1
4.8%
63 1
4.8%
58 1
4.8%
54 1
4.8%
41 1
4.8%

각하 건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.952381
Minimum0
Maximum24
Zeros5
Zeros (%)23.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:26:35.141986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q36
95-th percentile23
Maximum24
Range24
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.8005602
Coefficient of variation (CV)1.37319
Kurtosis4.1377666
Mean4.952381
Median Absolute Deviation (MAD)2
Skewness2.102068
Sum104
Variance46.247619
MonotonicityNot monotonic
2023-12-13T00:26:35.244299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 5
23.8%
1 4
19.0%
8 3
14.3%
5 2
 
9.5%
6 2
 
9.5%
2 2
 
9.5%
24 1
 
4.8%
23 1
 
4.8%
3 1
 
4.8%
ValueCountFrequency (%)
0 5
23.8%
1 4
19.0%
2 2
 
9.5%
3 1
 
4.8%
5 2
 
9.5%
6 2
 
9.5%
8 3
14.3%
23 1
 
4.8%
24 1
 
4.8%
ValueCountFrequency (%)
24 1
 
4.8%
23 1
 
4.8%
8 3
14.3%
6 2
 
9.5%
5 2
 
9.5%
3 1
 
4.8%
2 2
 
9.5%
1 4
19.0%
0 5
23.8%

기각 건수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.857143
Minimum2
Maximum107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:26:35.361273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q111
median20
Q352
95-th percentile96
Maximum107
Range105
Interquartile range (IQR)41

Descriptive statistics

Standard deviation31.219042
Coefficient of variation (CV)0.95014475
Kurtosis0.33560937
Mean32.857143
Median Absolute Deviation (MAD)15
Skewness1.1065447
Sum690
Variance974.62857
MonotonicityNot monotonic
2023-12-13T00:26:35.500939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
11 3
 
14.3%
52 2
 
9.5%
107 1
 
4.8%
8 1
 
4.8%
2 1
 
4.8%
3 1
 
4.8%
20 1
 
4.8%
12 1
 
4.8%
13 1
 
4.8%
5 1
 
4.8%
Other values (8) 8
38.1%
ValueCountFrequency (%)
2 1
 
4.8%
3 1
 
4.8%
5 1
 
4.8%
7 1
 
4.8%
8 1
 
4.8%
11 3
14.3%
12 1
 
4.8%
13 1
 
4.8%
20 1
 
4.8%
23 1
 
4.8%
ValueCountFrequency (%)
107 1
4.8%
96 1
4.8%
72 1
4.8%
65 1
4.8%
52 2
9.5%
49 1
4.8%
37 1
4.8%
34 1
4.8%
23 1
4.8%
20 1
4.8%

인용 건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.9047619
Minimum0
Maximum27
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:26:35.601936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q312
95-th percentile23
Maximum27
Range27
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.6544416
Coefficient of variation (CV)0.96833297
Kurtosis0.62002926
Mean7.9047619
Median Absolute Deviation (MAD)3
Skewness1.1041878
Sum166
Variance58.590476
MonotonicityNot monotonic
2023-12-13T00:26:35.701830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 4
19.0%
10 2
9.5%
3 2
9.5%
4 2
9.5%
2 2
9.5%
16 1
 
4.8%
13 1
 
4.8%
11 1
 
4.8%
27 1
 
4.8%
15 1
 
4.8%
Other values (4) 4
19.0%
ValueCountFrequency (%)
0 1
 
4.8%
1 4
19.0%
2 2
9.5%
3 2
9.5%
4 2
9.5%
7 1
 
4.8%
10 2
9.5%
11 1
 
4.8%
12 1
 
4.8%
13 1
 
4.8%
ValueCountFrequency (%)
27 1
4.8%
23 1
4.8%
16 1
4.8%
15 1
4.8%
13 1
4.8%
12 1
4.8%
11 1
4.8%
10 2
9.5%
7 1
4.8%
4 2
9.5%

인용률
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.080952
Minimum0
Maximum50
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:26:35.833758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.9
Q111.2
median16.7
Q325.2
95-th percentile33.3
Maximum50
Range50
Interquartile range (IQR)14

Descriptive statistics

Standard deviation11.003346
Coefficient of variation (CV)0.57666649
Kurtosis1.9061883
Mean19.080952
Median Absolute Deviation (MAD)5.8
Skewness0.94585284
Sum400.7
Variance121.07362
MonotonicityNot monotonic
2023-12-13T00:26:35.959456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20.0 2
 
9.5%
10.9 1
 
4.8%
11.1 1
 
4.8%
50.0 1
 
4.8%
33.3 1
 
4.8%
15.4 1
 
4.8%
25.0 1
 
4.8%
0.0 1
 
4.8%
5.9 1
 
4.8%
7.7 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
0.0 1
4.8%
5.9 1
4.8%
7.7 1
4.8%
10.9 1
4.8%
11.1 1
4.8%
11.2 1
4.8%
13.5 1
4.8%
15.4 1
4.8%
15.7 1
4.8%
16.2 1
4.8%
ValueCountFrequency (%)
50.0 1
4.8%
33.3 1
4.8%
30.0 1
4.8%
28.4 1
4.8%
26.3 1
4.8%
25.2 1
4.8%
25.0 1
4.8%
20.0 2
9.5%
18.2 1
4.8%
16.7 1
4.8%

처리세액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5927.0476
Minimum56
Maximum25505
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:26:36.077857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum56
5-th percentile307
Q11165
median3710
Q36818
95-th percentile18687
Maximum25505
Range25449
Interquartile range (IQR)5653

Descriptive statistics

Standard deviation7029.8544
Coefficient of variation (CV)1.1860634
Kurtosis1.9748925
Mean5927.0476
Median Absolute Deviation (MAD)3108
Skewness1.5837198
Sum124468
Variance49418852
MonotonicityNot monotonic
2023-12-13T00:26:36.204803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
495 1
 
4.8%
1488 1
 
4.8%
6292 1
 
4.8%
4418 1
 
4.8%
6818 1
 
4.8%
1165 1
 
4.8%
482 1
 
4.8%
307 1
 
4.8%
56 1
 
4.8%
11017 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
56 1
4.8%
307 1
4.8%
439 1
4.8%
482 1
4.8%
495 1
4.8%
1165 1
4.8%
1181 1
4.8%
1482 1
4.8%
1488 1
4.8%
1964 1
4.8%
ValueCountFrequency (%)
25505 1
4.8%
18687 1
4.8%
17309 1
4.8%
11017 1
4.8%
10598 1
4.8%
6818 1
4.8%
6292 1
4.8%
6180 1
4.8%
4875 1
4.8%
4418 1
4.8%

감세액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean834.66667
Minimum0
Maximum4567
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:26:36.304689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q158
median337
Q31394
95-th percentile3865
Maximum4567
Range4567
Interquartile range (IQR)1336

Descriptive statistics

Standard deviation1247.6652
Coefficient of variation (CV)1.4948065
Kurtosis4.3693166
Mean834.66667
Median Absolute Deviation (MAD)331
Skewness2.1608787
Sum17528
Variance1556668.4
MonotonicityNot monotonic
2023-12-13T00:26:36.398839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
337 2
 
9.5%
58 1
 
4.8%
100 1
 
4.8%
1454 1
 
4.8%
1394 1
 
4.8%
702 1
 
4.8%
180 1
 
4.8%
0 1
 
4.8%
2 1
 
4.8%
9 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
0 1
4.8%
2 1
4.8%
6 1
4.8%
9 1
4.8%
49 1
4.8%
58 1
4.8%
100 1
4.8%
160 1
4.8%
162 1
4.8%
180 1
4.8%
ValueCountFrequency (%)
4567 1
4.8%
3865 1
4.8%
1494 1
4.8%
1460 1
4.8%
1454 1
4.8%
1394 1
4.8%
702 1
4.8%
686 1
4.8%
506 1
4.8%
337 2
9.5%

감세액 비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.095238
Minimum0
Maximum31.6
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:26:36.493297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q110.3
median13.6
Q317.2
95-th percentile23.1
Maximum31.6
Range31.6
Interquartile range (IQR)6.9

Descriptive statistics

Standard deviation8.1121807
Coefficient of variation (CV)0.61947562
Kurtosis0.22890519
Mean13.095238
Median Absolute Deviation (MAD)3.6
Skewness0.09089535
Sum275
Variance65.807476
MonotonicityNot monotonic
2023-12-13T00:26:36.600765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
14.1 2
 
9.5%
11.7 1
 
4.8%
1.6 1
 
4.8%
23.1 1
 
4.8%
31.6 1
 
4.8%
10.3 1
 
4.8%
15.5 1
 
4.8%
0.0 1
 
4.8%
0.7 1
 
4.8%
16.1 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
0.0 1
4.8%
0.1 1
4.8%
0.7 1
4.8%
1.6 1
4.8%
8.4 1
4.8%
10.3 1
4.8%
10.9 1
4.8%
11.2 1
4.8%
11.7 1
4.8%
13.5 1
4.8%
ValueCountFrequency (%)
31.6 1
4.8%
23.1 1
4.8%
22.7 1
4.8%
20.7 1
4.8%
17.9 1
4.8%
17.2 1
4.8%
16.1 1
4.8%
15.5 1
4.8%
14.1 2
9.5%
13.6 1
4.8%

이월건수
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.142857
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:26:36.726383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median11
Q319
95-th percentile28
Maximum43
Range42
Interquartile range (IQR)16

Descriptive statistics

Standard deviation11.363475
Coefficient of variation (CV)0.86461225
Kurtosis0.72058803
Mean13.142857
Median Absolute Deviation (MAD)8
Skewness1.0046733
Sum276
Variance129.12857
MonotonicityNot monotonic
2023-12-13T00:26:36.852241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2 3
14.3%
28 2
 
9.5%
13 2
 
9.5%
5 2
 
9.5%
1 2
 
9.5%
18 1
 
4.8%
10 1
 
4.8%
21 1
 
4.8%
43 1
 
4.8%
27 1
 
4.8%
Other values (5) 5
23.8%
ValueCountFrequency (%)
1 2
9.5%
2 3
14.3%
3 1
 
4.8%
5 2
9.5%
9 1
 
4.8%
10 1
 
4.8%
11 1
 
4.8%
13 2
9.5%
15 1
 
4.8%
18 1
 
4.8%
ValueCountFrequency (%)
43 1
4.8%
28 2
9.5%
27 1
4.8%
21 1
4.8%
19 1
4.8%
18 1
4.8%
15 1
4.8%
13 2
9.5%
11 1
4.8%
10 1
4.8%

Interactions

2023-12-13T00:26:32.700385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.118701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.983707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.943237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:27.069251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:28.116622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:29.313153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:30.180399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:31.025509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:31.868817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:32.767620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.207510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.076896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.050953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:27.165916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:28.236314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:29.386623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:30.266304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:31.115972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:31.947948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:32.849430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.308985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.195533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.173406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:27.287688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:28.335758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:29.467662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:30.363736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:31.227857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:32.052510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:32.936348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.387036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.277359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.339079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:27.395154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:28.421427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:29.552267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:30.446090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:31.320979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:32.155137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:33.007653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.468838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.355772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.424035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:27.506706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:28.500356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:29.645571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:30.529223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:31.405818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:32.254400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:33.084138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.545234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.448031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.521499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:27.594165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:28.581669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:29.739844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:30.605688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:31.491312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:32.335852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:33.153162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.628088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.550018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.627670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:27.698841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:28.952997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:29.829610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:30.691352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:31.576470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:32.409953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:33.237838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.720163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.626289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.732016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:27.797169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:29.042067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:29.927020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:30.777206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:31.652886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:32.485636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:33.313373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.810329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.722487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.840177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:27.897369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:29.136424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:30.018629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:30.851131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:31.721751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:32.555301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:33.397635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.899676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.840464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.977504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:27.996470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:29.226964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:30.104939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:30.940197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:31.805714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:32.627847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:26:36.951890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분1구분2전년이월 건수당년접수 건수각하 건수기각 건수인용 건수인용률처리세액감세액감세액 비율이월건수
구분11.0000.0000.2860.5380.2570.6180.4820.4800.0000.0000.0000.567
구분20.0001.0000.6200.5250.6210.3730.6610.3290.7150.6090.4220.733
전년이월 건수0.2860.6201.0000.9340.7210.8880.9360.0000.5530.7470.6120.835
당년접수 건수0.5380.5250.9341.0000.6670.8460.9300.0000.3010.6740.7090.913
각하 건수0.2570.6210.7210.6671.0000.8440.8230.0000.3240.7100.0000.671
기각 건수0.6180.3730.8880.8460.8441.0000.8470.0000.0000.5860.0000.848
인용 건수0.4820.6610.9360.9300.8230.8471.0000.0000.7030.8340.8290.827
인용률0.4800.3290.0000.0000.0000.0000.0001.0000.0000.3130.5940.000
처리세액0.0000.7150.5530.3010.3240.0000.7030.0001.0000.8780.7430.716
감세액0.0000.6090.7470.6740.7100.5860.8340.3130.8781.0000.7070.731
감세액 비율0.0000.4220.6120.7090.0000.0000.8290.5940.7430.7071.0000.296
이월건수0.5670.7330.8350.9130.6710.8480.8270.0000.7160.7310.2961.000
2023-12-13T00:26:37.097707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분1구분2
구분11.0000.000
구분20.0001.000
2023-12-13T00:26:37.210921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전년이월 건수당년접수 건수각하 건수기각 건수인용 건수인용률처리세액감세액감세액 비율이월건수구분1구분2
전년이월 건수1.0000.8320.7170.8720.9370.0720.0220.2780.2000.8100.0890.352
당년접수 건수0.8321.0000.9050.9720.860-0.234-0.0690.0800.0250.9050.3200.266
각하 건수0.7170.9051.0000.8870.762-0.231-0.1770.0590.1650.7830.1600.416
기각 건수0.8720.9720.8871.0000.869-0.245-0.197-0.0060.0340.8230.0890.051
인용 건수0.9370.8600.7620.8691.0000.2460.1600.4050.3550.8460.2690.392
인용률0.072-0.234-0.231-0.2450.2461.0000.6220.7770.674-0.0310.3560.000
처리세액0.022-0.069-0.177-0.1970.1600.6221.0000.7660.1690.2980.0000.291
감세액0.2780.0800.059-0.0060.4050.7770.7661.0000.6080.3500.0000.404
감세액 비율0.2000.0250.1650.0340.3550.6740.1690.6081.0000.0470.0000.178
이월건수0.8100.9050.7830.8230.846-0.0310.2980.3500.0471.0000.3870.306
구분10.0890.3200.1600.0890.2690.3560.0000.0000.0000.3871.0000.000
구분20.3520.2660.4160.0510.3920.0000.2910.4040.1780.3060.0001.000

Missing values

2023-12-13T00:26:33.499989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:26:33.645811image/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

구분1구분2전년이월 건수당년접수 건수각하 건수기각 건수인용 건수인용률처리세액감세액감세액 비율이월건수
0청구세액 규모별1천만 미만44131241071610.94955811.728
1청구세액 규모별3천만 미만23785651315.7148816210.918
2청구세액 규모별5천만 미만6546341020.0196433717.210
3청구세액 규모별1억 미만15748491116.2487568614.121
4청구세액 규모별5억 미만311198722725.225505456717.943
5청구세액 규모별10억 미만424111320.010598149414.113
6청구세액 규모별10억 이상6907330.01730914608.45
7개인1천만 미만4012123961511.24394911.227
8개인3천만 미만21582521218.2118116013.513
9개인5천만 미만6415231026.3148233722.79
구분1구분2전년이월 건수당년접수 건수각하 건수기각 건수인용 건수인용률처리세액감세액감세액 비율이월건수
11개인5억 미만20896522328.418687386520.728
12개인10억 미만21808111.161801001.611
13개인10억 이상1805116.71101760.13
14법인1천만 미만41011117.756916.11
15법인3천만 미만22031315.930720.75
16법인5천만 미만01311100.048200.01
17법인1억 미만711012425.0116518015.52
18법인5억 미만1130220415.4681870210.315
19법인10억 미만2613233.34418139431.62
20법인10억 이상5102250.06292145423.12