Overview

Dataset statistics

Number of variables11
Number of observations138
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.5 KiB
Average record size in memory100.0 B

Variable types

Numeric11

Dataset

Description한국주택금융공사에서 발행한 주택담보노후연금보증 보증잔액 현황에 대한 내용이 담긴 데이터 로 공공개방을 위해 등록된 데이터 입니다.
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15073688/fileData.do

Alerts

연도 is highly overall correlated with 보증공급건수 and 8 other fieldsHigh correlation
보증공급건수 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
보증공급연금지급액1 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
보증공급보증공급액2 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
보증해지건수 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
보증해지연금지급액1 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
보증해지보증공급액2 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
보증잔액건수 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
보증잔액연금지급액1 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
보증잔액보증공급액2 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
보증잔액건수 has unique valuesUnique
보증잔액연금지급액1 has unique valuesUnique
보증잔액보증공급액2 has unique valuesUnique
보증해지연금지급액1 has 7 (5.1%) zerosZeros

Reproduction

Analysis started2023-12-12 21:30:04.072084
Analysis finished2023-12-12 21:30:15.475631
Duration11.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.2609
Minimum2008
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:30:15.803168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2008
Q12010
median2013
Q32016
95-th percentile2018
Maximum2019
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.3381326
Coefficient of variation (CV)0.0016580726
Kurtosis-1.1908632
Mean2013.2609
Median Absolute Deviation (MAD)3
Skewness0.019675343
Sum277830
Variance11.143129
MonotonicityIncreasing
2023-12-13T06:30:15.898027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2008 12
8.7%
2009 12
8.7%
2010 12
8.7%
2011 12
8.7%
2012 12
8.7%
2013 12
8.7%
2014 12
8.7%
2015 12
8.7%
2016 12
8.7%
2017 12
8.7%
Other values (2) 18
13.0%
ValueCountFrequency (%)
2008 12
8.7%
2009 12
8.7%
2010 12
8.7%
2011 12
8.7%
2012 12
8.7%
2013 12
8.7%
2014 12
8.7%
2015 12
8.7%
2016 12
8.7%
2017 12
8.7%
ValueCountFrequency (%)
2019 6
4.3%
2018 12
8.7%
2017 12
8.7%
2016 12
8.7%
2015 12
8.7%
2014 12
8.7%
2013 12
8.7%
2012 12
8.7%
2011 12
8.7%
2010 12
8.7%

월
Real number (ℝ)

Distinct12
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3695652
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:30:15.995462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4621543
Coefficient of variation (CV)0.5435464
Kurtosis-1.2119284
Mean6.3695652
Median Absolute Deviation (MAD)3
Skewness0.057716983
Sum879
Variance11.986512
MonotonicityNot monotonic
2023-12-13T06:30:16.088535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 12
8.7%
2 12
8.7%
3 12
8.7%
4 12
8.7%
5 12
8.7%
6 12
8.7%
7 11
8.0%
8 11
8.0%
9 11
8.0%
10 11
8.0%
Other values (2) 22
15.9%
ValueCountFrequency (%)
1 12
8.7%
2 12
8.7%
3 12
8.7%
4 12
8.7%
5 12
8.7%
6 12
8.7%
7 11
8.0%
8 11
8.0%
9 11
8.0%
10 11
8.0%
ValueCountFrequency (%)
12 11
8.0%
11 11
8.0%
10 11
8.0%
9 11
8.0%
8 11
8.0%
7 11
8.0%
6 12
8.7%
5 12
8.7%
4 12
8.7%
3 12
8.7%

보증공급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct130
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean475.22464
Minimum22
Maximum1853
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:30:16.203481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile59.4
Q1193
median446
Q3705.25
95-th percentile1011.45
Maximum1853
Range1831
Interquartile range (IQR)512.25

Descriptive statistics

Standard deviation343.74728
Coefficient of variation (CV)0.7233364
Kurtosis1.7611687
Mean475.22464
Median Absolute Deviation (MAD)256
Skewness1.053474
Sum65581
Variance118162.19
MonotonicityNot monotonic
2023-12-13T06:30:16.347784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
488 2
 
1.4%
245 2
 
1.4%
477 2
 
1.4%
79 2
 
1.4%
284 2
 
1.4%
478 2
 
1.4%
157 2
 
1.4%
876 2
 
1.4%
791 1
 
0.7%
537 1
 
0.7%
Other values (120) 120
87.0%
ValueCountFrequency (%)
22 1
0.7%
39 1
0.7%
47 1
0.7%
49 1
0.7%
50 1
0.7%
55 1
0.7%
56 1
0.7%
60 1
0.7%
63 1
0.7%
64 1
0.7%
ValueCountFrequency (%)
1853 1
0.7%
1752 1
0.7%
1302 1
0.7%
1157 1
0.7%
1100 1
0.7%
1039 1
0.7%
1014 1
0.7%
1011 1
0.7%
1002 1
0.7%
1000 1
0.7%

보증공급연금지급액1
Real number (ℝ)

HIGH CORRELATION 

Distinct118
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean324.24638
Minimum7
Maximum1020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:30:16.495535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile21.85
Q189
median284.5
Q3540.25
95-th percentile803.55
Maximum1020
Range1013
Interquartile range (IQR)451.25

Descriptive statistics

Standard deviation263.28536
Coefficient of variation (CV)0.81199167
Kurtosis-0.48748651
Mean324.24638
Median Absolute Deviation (MAD)202
Skewness0.72408562
Sum44746
Variance69319.18
MonotonicityNot monotonic
2023-12-13T06:30:16.622718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
289 2
 
1.4%
333 2
 
1.4%
89 2
 
1.4%
281 2
 
1.4%
85 2
 
1.4%
717 2
 
1.4%
245 2
 
1.4%
108 2
 
1.4%
354 2
 
1.4%
283 2
 
1.4%
Other values (108) 118
85.5%
ValueCountFrequency (%)
7 1
0.7%
8 1
0.7%
9 1
0.7%
19 1
0.7%
20 2
1.4%
21 1
0.7%
22 2
1.4%
24 1
0.7%
25 2
1.4%
26 1
0.7%
ValueCountFrequency (%)
1020 1
0.7%
990 1
0.7%
917 1
0.7%
890 1
0.7%
864 1
0.7%
846 1
0.7%
818 1
0.7%
801 1
0.7%
799 1
0.7%
789 1
0.7%

보증공급보증공급액2
Real number (ℝ)

HIGH CORRELATION 

Distinct137
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5313.4058
Minimum255
Maximum22374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:30:16.745596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum255
5-th percentile688.4
Q12918.5
median4966
Q37596.25
95-th percentile10284.15
Maximum22374
Range22119
Interquartile range (IQR)4677.75

Descriptive statistics

Standard deviation3516.6778
Coefficient of variation (CV)0.66185003
Kurtosis4.0375438
Mean5313.4058
Median Absolute Deviation (MAD)2496.5
Skewness1.3338362
Sum733250
Variance12367023
MonotonicityNot monotonic
2023-12-13T06:30:16.880490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1002 2
 
1.4%
401 1
 
0.7%
8737 1
 
0.7%
5370 1
 
0.7%
5504 1
 
0.7%
4875 1
 
0.7%
5889 1
 
0.7%
6394 1
 
0.7%
9968 1
 
0.7%
9451 1
 
0.7%
Other values (127) 127
92.0%
ValueCountFrequency (%)
255 1
0.7%
401 1
0.7%
478 1
0.7%
577 1
0.7%
590 1
0.7%
617 1
0.7%
685 1
0.7%
689 1
0.7%
841 1
0.7%
854 1
0.7%
ValueCountFrequency (%)
22374 1
0.7%
18687 1
0.7%
13945 1
0.7%
12097 1
0.7%
10803 1
0.7%
10779 1
0.7%
10438 1
0.7%
10257 1
0.7%
10127 1
0.7%
10010 1
0.7%

보증해지건수
Real number (ℝ)

HIGH CORRELATION 

Distinct88
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.376812
Minimum2
Maximum246
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:30:17.008455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q115
median48.5
Q3126.75
95-th percentile189.45
Maximum246
Range244
Interquartile range (IQR)111.75

Descriptive statistics

Standard deviation64.414171
Coefficient of variation (CV)0.88998354
Kurtosis-0.69164049
Mean72.376812
Median Absolute Deviation (MAD)41
Skewness0.6893457
Sum9988
Variance4149.1854
MonotonicityNot monotonic
2023-12-13T06:30:17.145421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 4
 
2.9%
8 4
 
2.9%
12 4
 
2.9%
2 4
 
2.9%
13 3
 
2.2%
22 3
 
2.2%
4 3
 
2.2%
7 3
 
2.2%
5 3
 
2.2%
6 3
 
2.2%
Other values (78) 104
75.4%
ValueCountFrequency (%)
2 4
2.9%
3 2
1.4%
4 3
2.2%
5 3
2.2%
6 3
2.2%
7 3
2.2%
8 4
2.9%
9 4
2.9%
12 4
2.9%
13 3
2.2%
ValueCountFrequency (%)
246 1
0.7%
226 1
0.7%
224 1
0.7%
206 1
0.7%
205 1
0.7%
197 1
0.7%
192 1
0.7%
189 1
0.7%
183 1
0.7%
181 1
0.7%

보증해지연금지급액1
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct73
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.992754
Minimum0
Maximum208
Zeros7
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:30:17.295345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.85
Q15
median21
Q371.75
95-th percentile133.3
Maximum208
Range208
Interquartile range (IQR)66.75

Descriptive statistics

Standard deviation46.493622
Coefficient of variation (CV)1.107182
Kurtosis0.99716221
Mean41.992754
Median Absolute Deviation (MAD)20
Skewness1.2626029
Sum5795
Variance2161.6569
MonotonicityNot monotonic
2023-12-13T06:30:17.427155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 10
 
7.2%
0 7
 
5.1%
2 7
 
5.1%
5 6
 
4.3%
7 5
 
3.6%
14 5
 
3.6%
11 4
 
2.9%
3 4
 
2.9%
13 3
 
2.2%
78 3
 
2.2%
Other values (63) 84
60.9%
ValueCountFrequency (%)
0 7
5.1%
1 10
7.2%
2 7
5.1%
3 4
 
2.9%
4 2
 
1.4%
5 6
4.3%
6 3
 
2.2%
7 5
3.6%
8 1
 
0.7%
9 2
 
1.4%
ValueCountFrequency (%)
208 1
0.7%
189 1
0.7%
162 1
0.7%
158 1
0.7%
149 1
0.7%
136 1
0.7%
135 1
0.7%
133 1
0.7%
130 1
0.7%
124 2
1.4%

보증해지보증공급액2
Real number (ℝ)

HIGH CORRELATION 

Distinct129
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean789.94203
Minimum11
Maximum2979
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:30:17.567176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile30.55
Q1166
median489
Q31308.25
95-th percentile2125.4
Maximum2979
Range2968
Interquartile range (IQR)1142.25

Descriptive statistics

Standard deviation737.23792
Coefficient of variation (CV)0.93328104
Kurtosis-0.086567159
Mean789.94203
Median Absolute Deviation (MAD)425.5
Skewness0.8699529
Sum109012
Variance543519.75
MonotonicityNot monotonic
2023-12-13T06:30:17.727501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
307 3
 
2.2%
243 2
 
1.4%
360 2
 
1.4%
240 2
 
1.4%
67 2
 
1.4%
24 2
 
1.4%
185 2
 
1.4%
1197 2
 
1.4%
998 1
 
0.7%
995 1
 
0.7%
Other values (119) 119
86.2%
ValueCountFrequency (%)
11 1
0.7%
12 1
0.7%
13 1
0.7%
24 2
1.4%
26 1
0.7%
28 1
0.7%
31 1
0.7%
32 1
0.7%
33 1
0.7%
39 1
0.7%
ValueCountFrequency (%)
2979 1
0.7%
2799 1
0.7%
2756 1
0.7%
2747 1
0.7%
2274 1
0.7%
2242 1
0.7%
2241 1
0.7%
2105 1
0.7%
2020 1
0.7%
1899 1
0.7%

보증잔액건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct138
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19138.275
Minimum547
Maximum56105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:30:17.867376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum547
5-th percentile903.25
Q13957.75
median15198.5
Q331796.5
95-th percentile50388.1
Maximum56105
Range55558
Interquartile range (IQR)27838.75

Descriptive statistics

Standard deviation16742.812
Coefficient of variation (CV)0.87483387
Kurtosis-0.81689389
Mean19138.275
Median Absolute Deviation (MAD)12318.5
Skewness0.67099745
Sum2641082
Variance2.8032174 × 108
MonotonicityNot monotonic
2023-12-13T06:30:18.009776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
547 1
 
0.7%
25611 1
 
0.7%
22802 1
 
0.7%
23183 1
 
0.7%
23583 1
 
0.7%
23937 1
 
0.7%
24339 1
 
0.7%
24823 1
 
0.7%
26226 1
 
0.7%
32563 1
 
0.7%
Other values (128) 128
92.8%
ValueCountFrequency (%)
547 1
0.7%
567 1
0.7%
614 1
0.7%
661 1
0.7%
724 1
0.7%
794 1
0.7%
865 1
0.7%
910 1
0.7%
965 1
0.7%
1043 1
0.7%
ValueCountFrequency (%)
56105 1
0.7%
55495 1
0.7%
54811 1
0.7%
53983 1
0.7%
52383 1
0.7%
51609 1
0.7%
51080 1
0.7%
50266 1
0.7%
49490 1
0.7%
48722 1
0.7%

보증잔액연금지급액1
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct138
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11312.87
Minimum53
Maximum38995
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:30:18.144536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53
5-th percentile168.15
Q11570.75
median7673
Q318611.25
95-th percentile33716.5
Maximum38995
Range38942
Interquartile range (IQR)17040.5

Descriptive statistics

Standard deviation11215.535
Coefficient of variation (CV)0.9913961
Kurtosis-0.41159978
Mean11312.87
Median Absolute Deviation (MAD)6863
Skewness0.87357537
Sum1561176
Variance1.2578822 × 108
MonotonicityStrictly increasing
2023-12-13T06:30:18.297846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53 1
 
0.7%
15187 1
 
0.7%
13372 1
 
0.7%
13686 1
 
0.7%
13942 1
 
0.7%
14237 1
 
0.7%
14536 1
 
0.7%
14811 1
 
0.7%
15510 1
 
0.7%
19212 1
 
0.7%
Other values (128) 128
92.8%
ValueCountFrequency (%)
53 1
0.7%
60 1
0.7%
67 1
0.7%
86 1
0.7%
106 1
0.7%
130 1
0.7%
152 1
0.7%
171 1
0.7%
190 1
0.7%
214 1
0.7%
ValueCountFrequency (%)
38995 1
0.7%
38264 1
0.7%
37495 1
0.7%
36640 1
0.7%
35712 1
0.7%
34952 1
0.7%
34286 1
0.7%
33616 1
0.7%
32934 1
0.7%
32305 1
0.7%

보증잔액보증공급액2
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct138
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean236598.13
Minimum6348
Maximum630225
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:30:18.443634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6348
5-th percentile10672.5
Q158086.75
median209626.5
Q3389136.5
95-th percentile569938.1
Maximum630225
Range623877
Interquartile range (IQR)331049.75

Descriptive statistics

Standard deviation190736.46
Coefficient of variation (CV)0.80616218
Kurtosis-1.0440387
Mean236598.13
Median Absolute Deviation (MAD)159327.5
Skewness0.48268922
Sum32650542
Variance3.6380399 × 1010
MonotonicityStrictly increasing
2023-12-13T06:30:18.615819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6348 1
 
0.7%
324659 1
 
0.7%
293569 1
 
0.7%
297742 1
 
0.7%
302189 1
 
0.7%
306015 1
 
0.7%
310308 1
 
0.7%
315586 1
 
0.7%
332399 1
 
0.7%
396791 1
 
0.7%
Other values (128) 128
92.8%
ValueCountFrequency (%)
6348 1
0.7%
6592 1
0.7%
7038 1
0.7%
7546 1
0.7%
8333 1
0.7%
9211 1
0.7%
10188 1
0.7%
10758 1
0.7%
11447 1
0.7%
12499 1
0.7%
ValueCountFrequency (%)
630225 1
0.7%
624341 1
0.7%
617494 1
0.7%
608874 1
0.7%
591633 1
0.7%
582754 1
0.7%
576818 1
0.7%
568724 1
0.7%
561461 1
0.7%
554606 1
0.7%

Interactions

2023-12-13T06:30:14.225047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:04.666337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:05.599196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:06.539555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.427544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:08.281987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:09.223803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:10.346878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:11.242948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:12.202928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:13.122719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:14.310036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:04.738288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:05.692180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:06.620162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.510999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:08.359315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:09.291241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:10.421033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:11.326617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:12.281188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:13.229581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:14.405362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:04.822756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:05.770749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:06.696336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.583570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:08.439092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:09.360675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:10.496616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:11.425134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:12.351961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:13.334765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:14.515853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:04.919684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:05.869554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:06.775812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.682411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:08.534761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:09.443391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:10.582421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:11.536912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:12.424036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:13.445477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:14.598492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:04.997113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:05.955682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:06.865530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.749098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:08.629344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:09.519910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:10.654390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:11.620663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:12.500536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:13.531730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:14.677551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:05.092214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:06.025249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:06.945256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.816250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:08.710177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:09.585731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:10.726614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:11.689600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:12.568603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:13.615499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:14.767219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:05.173208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:06.115498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.026400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.892240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:08.775479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:09.652619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:10.806143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:11.769759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:12.645052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:13.743102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:14.862026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:05.242731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:06.185873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.100075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.962947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:08.846266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:09.738755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:10.878359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:11.841413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:12.718303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:13.867964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:14.964235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:05.328250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:06.276983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.180730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:08.046103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:08.926393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:09.823582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:10.959914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:11.920771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:12.816726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:13.960051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:15.042140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:05.414870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:06.371100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.265103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:08.121804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:09.006725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:09.906793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:11.036352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:12.008297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:12.930555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:14.045428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:15.133958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:05.505685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:06.466120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:07.353538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:08.204746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:09.117440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:10.272034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:11.133484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:12.111562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:13.044561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:14.139648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:30:18.718215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도월보증공급건수보증공급연금지급액1보증공급보증공급액2보증해지건수보증해지연금지급액1보증해지보증공급액2보증잔액건수보증잔액연금지급액1보증잔액보증공급액2
연도1.0000.0000.7680.9360.7120.9150.7840.7790.9730.9750.979
월0.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
보증공급건수0.7680.0001.0000.8270.9170.7270.6750.7110.7740.7490.810
보증공급연금지급액10.9360.0000.8271.0000.7960.8890.7890.7590.9540.9510.971
보증공급보증공급액20.7120.0000.9170.7961.0000.6590.7450.7500.7110.7080.761
보증해지건수0.9150.0000.7270.8890.6591.0000.8730.8970.9200.9360.915
보증해지연금지급액10.7840.0000.6750.7890.7450.8731.0000.9450.8270.8560.797
보증해지보증공급액20.7790.0000.7110.7590.7500.8970.9451.0000.8590.8530.780
보증잔액건수0.9730.0000.7740.9540.7110.9200.8270.8591.0000.9810.975
보증잔액연금지급액10.9750.0000.7490.9510.7080.9360.8560.8530.9811.0000.982
보증잔액보증공급액20.9790.0000.8100.9710.7610.9150.7970.7800.9750.9821.000
2023-12-13T06:30:18.889546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도월보증공급건수보증공급연금지급액1보증공급보증공급액2보증해지건수보증해지연금지급액1보증해지보증공급액2보증잔액건수보증잔액연금지급액1보증잔액보증공급액2
연도1.000-0.0630.9340.9840.8750.9660.9770.9590.9960.9960.996
월-0.0631.0000.0070.0310.0180.0320.0400.0320.0210.0210.021
보증공급건수0.9340.0071.0000.9550.9810.9070.9160.8980.9360.9360.936
보증공급연금지급액10.9840.0310.9551.0000.9050.9630.9720.9560.9880.9880.988
보증공급보증공급액20.8750.0180.9810.9051.0000.8370.8490.8260.8770.8770.877
보증해지건수0.9660.0320.9070.9630.8371.0000.9850.9940.9700.9700.970
보증해지연금지급액10.9770.0400.9160.9720.8490.9851.0000.9840.9820.9820.982
보증해지보증공급액20.9590.0320.8980.9560.8260.9940.9841.0000.9620.9620.962
보증잔액건수0.9960.0210.9360.9880.8770.9700.9820.9621.0001.0001.000
보증잔액연금지급액10.9960.0210.9360.9880.8770.9700.9820.9621.0001.0001.000
보증잔액보증공급액20.9960.0210.9360.9880.8770.9700.9820.9621.0001.0001.000

Missing values

2023-12-13T06:30:15.257829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:30:15.423368image/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

연도월보증공급건수보증공급연금지급액1보증공급보증공급액2보증해지건수보증해지연금지급액1보증해지보증공급액2보증잔액건수보증잔액연금지급액1보증잔액보증공급액2
0200813994013026547536348
1200822272552012567606592
2200834984782032614677038
32008456205779169661867546
420085712185481677241068333
5200867925984911067941309211
62008775221002402486515210188
7200884720590714391017110758
8200895519689502896519011447
9200810782610518276104321412499
연도월보증공급건수보증공급연금지급액1보증공급보증공급액2보증해지건수보증해지연금지급액1보증해지보증공급액2보증잔액건수보증잔액연금지급액1보증잔액보증공급액2
12820189584687557220616227994872232305554606
1292018101014818983424618929794949032934561461
13020181110028901001022620827475026633616568724
131201812972789969415811916005108034286576818
13220191726801804119713521055160934952582754
13320192906846101271338612525238335712591633
1342019317521020186871519214415398336640608874
1352019410119901043818313618185481137495617494
13620195876917869819214918515549538264624341
13720196773864746416313315805610538995630225