Overview

Dataset statistics

Number of variables9
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory87.0 B

Variable types

Numeric9

Dataset

Description공무원연금대출(회수액, 대출잔액, 대출수익 수익률) 현황에 대한 데이터입니다. 2001년부터 시작되며 연 단위로 구분됩니다.
URLhttps://www.data.go.kr/data/15054010/fileData.do

Alerts

구분 is highly overall correlated with 대출금액 and 5 other fieldsHigh correlation
대출건수 is highly overall correlated with 대출금액 and 1 other fieldsHigh correlation
대출금액 is highly overall correlated with 구분 and 6 other fieldsHigh correlation
회수건수 is highly overall correlated with 구분 and 6 other fieldsHigh correlation
회수금액 is highly overall correlated with 구분 and 5 other fieldsHigh correlation
대출잔액건수 is highly overall correlated with 구분 and 5 other fieldsHigh correlation
대출잔액금액 is highly overall correlated with 구분 and 5 other fieldsHigh correlation
수익률 is highly overall correlated with 구분 and 5 other fieldsHigh correlation
구분 has unique valuesUnique
대출건수 has unique valuesUnique
대출금액 has unique valuesUnique
회수건수 has unique valuesUnique
회수금액 has unique valuesUnique
대출잔액건수 has unique valuesUnique
대출잔액금액 has unique valuesUnique
수익액 has unique valuesUnique
수익률 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:36:56.898505
Analysis finished2023-12-12 08:37:06.450552
Duration9.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.5
Minimum2001
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T17:37:06.518998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2002.05
Q12006.25
median2011.5
Q32016.75
95-th percentile2020.95
Maximum2022
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.003228231
Kurtosis-1.2
Mean2011.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum44253
Variance42.166667
MonotonicityStrictly increasing
2023-12-12T17:37:06.671603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2001 1
 
4.5%
2013 1
 
4.5%
2022 1
 
4.5%
2021 1
 
4.5%
2020 1
 
4.5%
2019 1
 
4.5%
2018 1
 
4.5%
2017 1
 
4.5%
2016 1
 
4.5%
2015 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
2001 1
4.5%
2002 1
4.5%
2003 1
4.5%
2004 1
4.5%
2005 1
4.5%
2006 1
4.5%
2007 1
4.5%
2008 1
4.5%
2009 1
4.5%
2010 1
4.5%
ValueCountFrequency (%)
2022 1
4.5%
2021 1
4.5%
2020 1
4.5%
2019 1
4.5%
2018 1
4.5%
2017 1
4.5%
2016 1
4.5%
2015 1
4.5%
2014 1
4.5%
2013 1
4.5%

대출건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38656.636
Minimum30120
Maximum60144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T17:37:06.832598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30120
5-th percentile31266.55
Q133634.5
median37225
Q340926.25
95-th percentile51178.3
Maximum60144
Range30024
Interquartile range (IQR)7291.75

Descriptive statistics

Standard deviation7242.0974
Coefficient of variation (CV)0.18734422
Kurtosis2.5454781
Mean38656.636
Median Absolute Deviation (MAD)3961.5
Skewness1.4760865
Sum850446
Variance52447975
MonotonicityNot monotonic
2023-12-12T17:37:07.004521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
41317 1
 
4.5%
60144 1
 
4.5%
30120 1
 
4.5%
38385 1
 
4.5%
38761 1
 
4.5%
39754 1
 
4.5%
37419 1
 
4.5%
46130 1
 
4.5%
37031 1
 
4.5%
44301 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
30120 1
4.5%
31264 1
4.5%
31315 1
4.5%
32036 1
4.5%
33224 1
4.5%
33303 1
4.5%
34629 1
4.5%
34889 1
4.5%
35070 1
4.5%
36246 1
4.5%
ValueCountFrequency (%)
60144 1
4.5%
51444 1
4.5%
46130 1
4.5%
45241 1
4.5%
44301 1
4.5%
41317 1
4.5%
39754 1
4.5%
38761 1
4.5%
38423 1
4.5%
38385 1
4.5%

대출금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean642204.68
Minimum479342
Maximum948430
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T17:37:07.162142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum479342
5-th percentile494961.1
Q1499764.25
median566095
Q3784054.25
95-th percentile899462.3
Maximum948430
Range469088
Interquartile range (IQR)284290

Descriptive statistics

Standard deviation162210.84
Coefficient of variation (CV)0.25258433
Kurtosis-1.2977118
Mean642204.68
Median Absolute Deviation (MAD)79062
Skewness0.51191862
Sum14128503
Variance2.6312356 × 1010
MonotonicityNot monotonic
2023-12-12T17:37:07.323447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
501110 1
 
4.5%
889797 1
 
4.5%
749981 1
 
4.5%
948430 1
 
4.5%
899971 1
 
4.5%
799991 1
 
4.5%
795412 1
 
4.5%
799994 1
 
4.5%
629983 1
 
4.5%
699679 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
479342 1
4.5%
494724 1
4.5%
499466 1
4.5%
499618 1
4.5%
499625 1
4.5%
499739 1
4.5%
499840 1
4.5%
499920 1
4.5%
499965 1
4.5%
501110 1
4.5%
ValueCountFrequency (%)
948430 1
4.5%
899971 1
4.5%
889797 1
4.5%
799994 1
4.5%
799991 1
4.5%
795412 1
4.5%
749981 1
4.5%
739715 1
4.5%
699994 1
4.5%
699679 1
4.5%

회수건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33291.545
Minimum3459
Maximum46901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T17:37:07.466782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3459
5-th percentile13536.7
Q128518
median33699.5
Q342465
95-th percentile46099.25
Maximum46901
Range43442
Interquartile range (IQR)13947

Descriptive statistics

Standard deviation10889.1
Coefficient of variation (CV)0.32708305
Kurtosis1.4779366
Mean33291.545
Median Absolute Deviation (MAD)7908
Skewness-1.085856
Sum732414
Variance1.1857251 × 108
MonotonicityNot monotonic
2023-12-12T17:37:07.600723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3459 1
 
4.5%
46901 1
 
4.5%
28132 1
 
4.5%
33233 1
 
4.5%
42390 1
 
4.5%
34166 1
 
4.5%
38646 1
 
4.5%
42490 1
 
4.5%
42666 1
 
4.5%
46149 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
3459 1
4.5%
13047 1
4.5%
22841 1
4.5%
25159 1
4.5%
26424 1
4.5%
28132 1
4.5%
29676 1
4.5%
30244 1
4.5%
32492 1
4.5%
32982 1
4.5%
ValueCountFrequency (%)
46901 1
4.5%
46149 1
4.5%
45154 1
4.5%
44528 1
4.5%
42666 1
4.5%
42490 1
4.5%
42390 1
4.5%
38646 1
4.5%
37040 1
4.5%
34595 1
4.5%

회수금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean550256.59
Minimum72577
Maximum833209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T17:37:07.748837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum72577
5-th percentile282263.35
Q1476535.25
median542636
Q3674961.25
95-th percentile718812.8
Maximum833209
Range760632
Interquartile range (IQR)198426

Descriptive statistics

Standard deviation167763.38
Coefficient of variation (CV)0.30488209
Kurtosis1.9598109
Mean550256.59
Median Absolute Deviation (MAD)98595
Skewness-1.0085921
Sum12105645
Variance2.8144552 × 1010
MonotonicityNot monotonic
2023-12-12T17:37:07.895250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
72577 1
 
4.5%
622638 1
 
4.5%
633854 1
 
4.5%
680776 1
 
4.5%
833209 1
 
4.5%
704461 1
 
4.5%
719176 1
 
4.5%
657517 1
 
4.5%
638917 1
 
4.5%
705468 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
72577 1
4.5%
274452 1
4.5%
430679 1
4.5%
441727 1
4.5%
457165 1
4.5%
476049 1
4.5%
477994 1
4.5%
485310 1
4.5%
490582 1
4.5%
505910 1
4.5%
ValueCountFrequency (%)
833209 1
4.5%
719176 1
4.5%
711912 1
4.5%
705468 1
4.5%
704461 1
4.5%
680776 1
4.5%
657517 1
4.5%
638917 1
4.5%
633854 1
4.5%
622638 1
4.5%

대출잔액건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95701
Minimum37858
Maximum118032
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T17:37:08.068618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37858
5-th percentile61580.1
Q187411.75
median97062.5
Q3111839.25
95-th percentile115967.85
Maximum118032
Range80174
Interquartile range (IQR)24427.5

Descriptive statistics

Standard deviation20319.801
Coefficient of variation (CV)0.2123259
Kurtosis1.7505713
Mean95701
Median Absolute Deviation (MAD)13802.5
Skewness-1.2800065
Sum2105422
Variance4.128943 × 108
MonotonicityNot monotonic
2023-12-12T17:37:08.247727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
37858 1
 
4.5%
113290 1
 
4.5%
118032 1
 
4.5%
116044 1
 
4.5%
110892 1
 
4.5%
114521 1
 
4.5%
108933 1
 
4.5%
110160 1
 
4.5%
106520 1
 
4.5%
112155 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
37858 1
4.5%
61057 1
4.5%
71519 1
4.5%
78396 1
4.5%
83287 1
4.5%
87115 1
4.5%
88302 1
4.5%
91941 1
4.5%
93515 1
4.5%
93757 1
4.5%
ValueCountFrequency (%)
118032 1
4.5%
116044 1
4.5%
114521 1
4.5%
114003 1
4.5%
113290 1
4.5%
112155 1
4.5%
110892 1
4.5%
110160 1
4.5%
108933 1
4.5%
106520 1
4.5%

대출잔액금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1121100.1
Minimum428533
Maximum2050688
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T17:37:08.434483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum428533
5-th percentile659734.95
Q1825864
median940372.5
Q31371590
95-th percentile1921179.3
Maximum2050688
Range1622155
Interquartile range (IQR)545726

Descriptive statistics

Standard deviation433374.51
Coefficient of variation (CV)0.38656182
Kurtosis-0.38210862
Mean1121100.1
Median Absolute Deviation (MAD)300892
Skewness0.63915112
Sum24664203
Variance1.8781346 × 1011
MonotonicityNot monotonic
2023-12-12T17:37:08.607240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
428533 1
 
4.5%
1284713 1
 
4.5%
2050688 1
 
4.5%
1934562 1
 
4.5%
1666908 1
 
4.5%
1600146 1
 
4.5%
1504688 1
 
4.5%
1400549 1
 
4.5%
1258072 1
 
4.5%
1267006 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
428533 1
4.5%
656288 1
4.5%
725227 1
4.5%
767801 1
4.5%
771094 1
4.5%
824091 1
4.5%
831183 1
4.5%
839618 1
4.5%
845563 1
4.5%
853933 1
4.5%
ValueCountFrequency (%)
2050688 1
4.5%
1934562 1
4.5%
1666908 1
4.5%
1600146 1
4.5%
1504688 1
4.5%
1400549 1
4.5%
1284713 1
4.5%
1272795 1
4.5%
1267006 1
4.5%
1258072 1
4.5%

수익액
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52376.864
Minimum13017
Maximum70203
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T17:37:08.757350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13017
5-th percentile42327.45
Q148282
median52610
Q358274.25
95-th percentile65930
Maximum70203
Range57186
Interquartile range (IQR)9992.25

Descriptive statistics

Standard deviation11005.43
Coefficient of variation (CV)0.21012007
Kurtosis7.6082089
Mean52376.864
Median Absolute Deviation (MAD)4967
Skewness-2.0584208
Sum1152291
Variance1.2111949 × 108
MonotonicityNot monotonic
2023-12-12T17:37:09.198043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
13017 1
 
4.5%
58876 1
 
4.5%
70203 1
 
4.5%
47611 1
 
4.5%
50942 1
 
4.5%
51954 1
 
4.5%
56272 1
 
4.5%
47675 1
 
4.5%
46991 1
 
4.5%
50103 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
13017 1
4.5%
42082 1
4.5%
46991 1
4.5%
47053 1
4.5%
47611 1
4.5%
47675 1
4.5%
50103 1
4.5%
50942 1
4.5%
51954 1
4.5%
52252 1
4.5%
ValueCountFrequency (%)
70203 1
4.5%
66174 1
4.5%
61294 1
4.5%
60013 1
4.5%
59424 1
4.5%
58876 1
4.5%
56469 1
4.5%
56272 1
4.5%
55105 1
4.5%
53561 1
4.5%

수익률
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0486364
Minimum2.48
Maximum7.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T17:37:09.360468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.48
5-th percentile2.987
Q13.3675
median5.345
Q36.3175
95-th percentile7.5095
Maximum7.92
Range5.44
Interquartile range (IQR)2.95

Descriptive statistics

Standard deviation1.6837834
Coefficient of variation (CV)0.33351252
Kurtosis-1.3222824
Mean5.0486364
Median Absolute Deviation (MAD)1.555
Skewness0.10755481
Sum111.07
Variance2.8351266
MonotonicityNot monotonic
2023-12-12T17:37:09.537243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
7.92 1
 
4.5%
4.58 1
 
4.5%
3.42 1
 
4.5%
2.48 1
 
4.5%
2.98 1
 
4.5%
3.27 1
 
4.5%
3.64 1
 
4.5%
3.34 1
 
4.5%
3.12 1
 
4.5%
3.35 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
2.48 1
4.5%
2.98 1
4.5%
3.12 1
4.5%
3.27 1
4.5%
3.34 1
4.5%
3.35 1
4.5%
3.42 1
4.5%
3.64 1
4.5%
4.09 1
4.5%
4.58 1
4.5%
ValueCountFrequency (%)
7.92 1
4.5%
7.51 1
4.5%
7.5 1
4.5%
6.75 1
4.5%
6.51 1
4.5%
6.38 1
4.5%
6.13 1
4.5%
5.9 1
4.5%
5.84 1
4.5%
5.67 1
4.5%

Interactions

2023-12-12T17:37:05.339586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:57.158456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:58.203461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:59.057138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:00.067837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:00.942382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:02.052224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:03.374370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:04.416965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:05.427635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:57.248819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:58.292563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:59.143711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:00.165696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:01.038279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:02.164892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:03.491912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:04.532402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:05.519023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:57.365637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:58.386605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:59.255801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:00.293812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:01.138766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:02.610271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:03.600259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:04.640487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:05.602035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:57.536995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:58.466325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:59.383091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:00.380488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:01.238983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:02.711085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:03.707036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:04.734439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:05.690128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:57.647307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:58.545989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:59.483423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:00.458291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:01.349248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:02.805064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:03.804384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:04.820456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:05.785453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:57.782003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:58.643067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:59.599890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:00.560260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:01.482841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:02.921820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:03.914155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:04.935308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:05.905517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:57.917202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:58.762537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:59.731113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:00.663388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:01.606369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:03.022939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:04.014017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:05.034764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:06.011098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:58.023895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:58.864845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:59.863403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:00.771725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:01.798168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:03.148205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:04.193941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:05.140773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:06.095186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:58.116400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:58.955331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:59.962443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:00.865594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:01.918384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:03.263789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:04.303888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:37:05.243555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:37:09.666790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분대출건수대출금액회수건수회수금액대출잔액건수대출잔액금액수익액수익률
구분1.0000.6460.7370.5560.7440.8020.8430.4960.793
대출건수0.6461.0000.6740.0000.1490.3360.6290.0000.786
대출금액0.7370.6741.0000.6050.6960.0000.8660.0000.544
회수건수0.5560.0000.6051.0000.7380.8510.7930.4920.438
회수금액0.7440.1490.6960.7381.0000.8650.9000.0000.770
대출잔액건수0.8020.3360.0000.8510.8651.0000.8980.4440.553
대출잔액금액0.8430.6290.8660.7930.9000.8981.0000.0000.749
수익액0.4960.0000.0000.4920.0000.4440.0001.0000.286
수익률0.7930.7860.5440.4380.7700.5530.7490.2861.000
2023-12-12T17:37:09.800173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분대출건수대출금액회수건수회수금액대출잔액건수대출잔액금액수익액수익률
구분1.0000.2680.7900.5900.9100.9350.9760.130-0.951
대출건수0.2681.0000.5890.6430.4130.3690.316-0.138-0.370
대출금액0.7900.5891.0000.5160.7590.7820.802-0.073-0.750
회수건수0.5900.6430.5161.0000.7210.6320.5980.207-0.678
회수금액0.9100.4130.7590.7211.0000.8790.8890.115-0.897
대출잔액건수0.9350.3690.7820.6320.8791.0000.9450.258-0.872
대출잔액금액0.9760.3160.8020.5980.8890.9451.0000.212-0.910
수익액0.130-0.138-0.0730.2070.1150.2580.2121.0000.074
수익률-0.951-0.370-0.750-0.678-0.897-0.872-0.9100.0741.000

Missing values

2023-12-12T17:37:06.246478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:37:06.395340image/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

구분대출건수대출금액회수건수회수금액대출잔액건수대출잔액금액수익액수익률
020014131750111034597257737858428533130177.92
12002362465022071304727445261057656288420827.51
22003333034996182284143067971519725227551057.5
32004320364997392515945716578396767801522526.75
42005313154793422642447604983287771094470536.13
52006384234947243459544172787115824091535615.9
62007350704994663024447799491941845563612946.38
72008346294999653249250591094078839618661746.51
82009312644996253704048531088302853933564695.84
92010348894998402967649058293515863191525965.67
구분대출건수대출금액회수건수회수금액대출잔액건수대출잔액금액수익액수익률
12201360144889797469016226381132901284713588764.58
13201445241699994445287119121140031272795594244.09
14201544301699679461497054681121551267006501033.35
15201637031629983426666389171065201258072469913.12
16201746130799994424906575171101601400549476753.34
17201837419795412386467191761089331504688562723.64
18201939754799991341667044611145211600146519543.27
19202038761899971423908332091108921666908509422.98
20202138385948430332336807761160441934562476112.48
21202230120749981281326338541180322050688702033.42