Overview

Dataset statistics

Number of variables16
Number of observations85
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory145.6 B

Variable types

Numeric15
Categorical1

Dataset

Description한국주택금융공사에서 발행한 주택담보노후연금보증 현황에 대한 데이터 입니다. 공공데이터 개방 정책에 따라 등록되었습니다. 기준년","기준월","합계","국민은행","기업은행","농협은행","신한은행","우리은행","하나은행","광주은행","대구은행","부산은행","전북은행","경남은행","외환은행 과 같은 은행값이 포함되어있습니다.
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15073665/fileData.do

Alerts

기준년 is highly overall correlated with 합계 and 12 other fieldsHigh correlation
합계 is highly overall correlated with 기준년 and 12 other fieldsHigh correlation
국민은행 is highly overall correlated with 기준년 and 11 other fieldsHigh correlation
기업은행 is highly overall correlated with 기준년 and 10 other fieldsHigh correlation
농협은행 is highly overall correlated with 기준년 and 12 other fieldsHigh correlation
신한은행 is highly overall correlated with 기준년 and 11 other fieldsHigh correlation
우리은행 is highly overall correlated with 기준년 and 12 other fieldsHigh correlation
하나은행 is highly overall correlated with 기준년 and 11 other fieldsHigh correlation
광주은행 is highly overall correlated with 기준년 and 9 other fieldsHigh correlation
대구은행 is highly overall correlated with 기준년 and 12 other fieldsHigh correlation
부산은행 is highly overall correlated with 기준년 and 13 other fieldsHigh correlation
전북은행 is highly overall correlated with 기준년 and 13 other fieldsHigh correlation
경남은행 is highly overall correlated with 기준년 and 11 other fieldsHigh correlation
외환은행 is highly overall correlated with 기준년 and 7 other fieldsHigh correlation
기타 is highly overall correlated with 부산은행 and 1 other fieldsHigh correlation
기타 is highly imbalanced (88.4%)Imbalance
국민은행 has unique valuesUnique
광주은행 has 22 (25.9%) zerosZeros
대구은행 has 17 (20.0%) zerosZeros
부산은행 has 23 (27.1%) zerosZeros
전북은행 has 36 (42.4%) zerosZeros
경남은행 has 48 (56.5%) zerosZeros
외환은행 has 61 (71.8%) zerosZeros

Reproduction

Analysis started2023-12-11 23:37:23.172917
Analysis finished2023-12-11 23:37:46.472069
Duration23.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.0471
Minimum2008
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:46.520379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2008
Q12009
median2011
Q32013
95-th percentile2014
Maximum2015
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0465178
Coefficient of variation (CV)0.001017638
Kurtosis-1.2145285
Mean2011.0471
Median Absolute Deviation (MAD)2
Skewness0.020373567
Sum170939
Variance4.1882353
MonotonicityIncreasing
2023-12-12T08:37:46.636040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2008 12
14.1%
2009 12
14.1%
2010 12
14.1%
2011 12
14.1%
2012 12
14.1%
2013 12
14.1%
2014 12
14.1%
2015 1
 
1.2%
ValueCountFrequency (%)
2008 12
14.1%
2009 12
14.1%
2010 12
14.1%
2011 12
14.1%
2012 12
14.1%
2013 12
14.1%
2014 12
14.1%
2015 1
 
1.2%
ValueCountFrequency (%)
2015 1
 
1.2%
2014 12
14.1%
2013 12
14.1%
2012 12
14.1%
2011 12
14.1%
2010 12
14.1%
2009 12
14.1%
2008 12
14.1%

기준월
Real number (ℝ)

Distinct12
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4352941
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:46.789274image/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 deviation3.5032198
Coefficient of variation (CV)0.54437602
Kurtosis-1.2281706
Mean6.4352941
Median Absolute Deviation (MAD)3
Skewness0.0095740883
Sum547
Variance12.272549
MonotonicityNot monotonic
2023-12-12T08:37:46.902752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 8
9.4%
2 7
8.2%
3 7
8.2%
4 7
8.2%
5 7
8.2%
6 7
8.2%
7 7
8.2%
8 7
8.2%
9 7
8.2%
10 7
8.2%
Other values (2) 14
16.5%
ValueCountFrequency (%)
1 8
9.4%
2 7
8.2%
3 7
8.2%
4 7
8.2%
5 7
8.2%
6 7
8.2%
7 7
8.2%
8 7
8.2%
9 7
8.2%
10 7
8.2%
ValueCountFrequency (%)
12 7
8.2%
11 7
8.2%
10 7
8.2%
9 7
8.2%
8 7
8.2%
7 7
8.2%
6 7
8.2%
5 7
8.2%
4 7
8.2%
3 7
8.2%

합계
Real number (ℝ)

HIGH CORRELATION 

Distinct84
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3414.4
Minimum261
Maximum10779
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:47.064329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum261
5-th percentile595.4
Q11604
median3452
Q34615
95-th percentile6751.2
Maximum10779
Range10518
Interquartile range (IQR)3011

Descriptive statistics

Standard deviation2121.4713
Coefficient of variation (CV)0.62133064
Kurtosis0.83773872
Mean3414.4
Median Absolute Deviation (MAD)1481
Skewness0.75230218
Sum290224
Variance4500640.7
MonotonicityNot monotonic
2023-12-12T08:37:47.243953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1002 2
 
2.4%
401 1
 
1.2%
5738 1
 
1.2%
3188 1
 
1.2%
4225 1
 
1.2%
8126 1
 
1.2%
8997 1
 
1.2%
6067 1
 
1.2%
6907 1
 
1.2%
6014 1
 
1.2%
Other values (74) 74
87.1%
ValueCountFrequency (%)
261 1
1.2%
401 1
1.2%
476 1
1.2%
568 1
1.2%
590 1
1.2%
617 1
1.2%
685 1
1.2%
689 1
1.2%
841 1
1.2%
860 1
1.2%
ValueCountFrequency (%)
10779 1
1.2%
8997 1
1.2%
8126 1
1.2%
7591 1
1.2%
6907 1
1.2%
6128 1
1.2%
6119 1
1.2%
6067 1
1.2%
6014 1
1.2%
5924 1
1.2%

국민은행
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1343.0824
Minimum173
Maximum4594
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:47.397874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173
5-th percentile290
Q1615
median1273
Q31819
95-th percentile2535.8
Maximum4594
Range4421
Interquartile range (IQR)1204

Descriptive statistics

Standard deviation809.40544
Coefficient of variation (CV)0.60264766
Kurtosis2.2862145
Mean1343.0824
Median Absolute Deviation (MAD)603
Skewness1.0727507
Sum114162
Variance655137.17
MonotonicityNot monotonic
2023-12-12T08:37:47.559070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201 1
 
1.2%
1448 1
 
1.2%
1408 1
 
1.2%
3041 1
 
1.2%
3636 1
 
1.2%
2451 1
 
1.2%
2541 1
 
1.2%
2515 1
 
1.2%
2861 1
 
1.2%
2253 1
 
1.2%
Other values (75) 75
88.2%
ValueCountFrequency (%)
173 1
1.2%
190 1
1.2%
201 1
1.2%
275 1
1.2%
288 1
1.2%
298 1
1.2%
349 1
1.2%
404 1
1.2%
410 1
1.2%
429 1
1.2%
ValueCountFrequency (%)
4594 1
1.2%
3636 1
1.2%
3041 1
1.2%
2861 1
1.2%
2541 1
1.2%
2515 1
1.2%
2451 1
1.2%
2395 1
1.2%
2253 1
1.2%
2190 1
1.2%

기업은행
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean140.32941
Minimum7
Maximum388
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:47.734411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile25.4
Q170
median138
Q3201
95-th percentile267
Maximum388
Range381
Interquartile range (IQR)131

Descriptive statistics

Standard deviation81.620695
Coefficient of variation (CV)0.58163641
Kurtosis-0.32561381
Mean140.32941
Median Absolute Deviation (MAD)68
Skewness0.37248954
Sum11928
Variance6661.9378
MonotonicityNot monotonic
2023-12-12T08:37:47.898016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
261 2
 
2.4%
70 2
 
2.4%
72 2
 
2.4%
267 2
 
2.4%
125 2
 
2.4%
176 2
 
2.4%
45 2
 
2.4%
47 2
 
2.4%
62 2
 
2.4%
7 2
 
2.4%
Other values (64) 65
76.5%
ValueCountFrequency (%)
7 2
2.4%
11 1
1.2%
23 1
1.2%
24 1
1.2%
31 1
1.2%
36 2
2.4%
37 1
1.2%
38 1
1.2%
42 1
1.2%
45 2
2.4%
ValueCountFrequency (%)
388 1
1.2%
292 1
1.2%
280 1
1.2%
277 1
1.2%
267 2
2.4%
265 1
1.2%
261 2
2.4%
249 1
1.2%
244 1
1.2%
237 1
1.2%

농협은행
Real number (ℝ)

HIGH CORRELATION 

Distinct83
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean365.31765
Minimum13
Maximum897
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:48.056808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile37
Q1131
median357
Q3530
95-th percentile798.6
Maximum897
Range884
Interquartile range (IQR)399

Descriptive statistics

Standard deviation244.80703
Coefficient of variation (CV)0.670121
Kurtosis-0.88034542
Mean365.31765
Median Absolute Deviation (MAD)201
Skewness0.35061256
Sum31052
Variance59930.481
MonotonicityNot monotonic
2023-12-12T08:37:48.232245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
399 2
 
2.4%
528 2
 
2.4%
261 1
 
1.2%
897 1
 
1.2%
840 1
 
1.2%
845 1
 
1.2%
558 1
 
1.2%
706 1
 
1.2%
463 1
 
1.2%
376 1
 
1.2%
Other values (73) 73
85.9%
ValueCountFrequency (%)
13 1
1.2%
14 1
1.2%
30 1
1.2%
31 1
1.2%
34 1
1.2%
49 1
1.2%
50 1
1.2%
54 1
1.2%
62 1
1.2%
67 1
1.2%
ValueCountFrequency (%)
897 1
1.2%
866 1
1.2%
845 1
1.2%
840 1
1.2%
808 1
1.2%
761 1
1.2%
760 1
1.2%
753 1
1.2%
737 1
1.2%
706 1
1.2%

신한은행
Real number (ℝ)

HIGH CORRELATION 

Distinct81
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean600.68235
Minimum6
Maximum2322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:48.400799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile43.8
Q1257
median541
Q3838
95-th percentile1304.2
Maximum2322
Range2316
Interquartile range (IQR)581

Descriptive statistics

Standard deviation426.09241
Coefficient of variation (CV)0.70934731
Kurtosis2.0132511
Mean600.68235
Median Absolute Deviation (MAD)284
Skewness1.0511726
Sum51058
Variance181554.74
MonotonicityNot monotonic
2023-12-12T08:37:48.531888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1221 2
 
2.4%
29 2
 
2.4%
257 2
 
2.4%
209 2
 
2.4%
1183 1
 
1.2%
489 1
 
1.2%
744 1
 
1.2%
1558 1
 
1.2%
1548 1
 
1.2%
1179 1
 
1.2%
Other values (71) 71
83.5%
ValueCountFrequency (%)
6 1
1.2%
9 1
1.2%
29 2
2.4%
42 1
1.2%
51 1
1.2%
52 1
1.2%
89 1
1.2%
115 1
1.2%
126 1
1.2%
138 1
1.2%
ValueCountFrequency (%)
2322 1
1.2%
1558 1
1.2%
1548 1
1.2%
1371 1
1.2%
1325 1
1.2%
1221 2
2.4%
1183 1
1.2%
1179 1
1.2%
1075 1
1.2%
1060 1
1.2%

우리은행
Real number (ℝ)

HIGH CORRELATION 

Distinct80
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean465.83529
Minimum27
Maximum1443
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:48.675429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile73.4
Q1199
median439
Q3651
95-th percentile1013.2
Maximum1443
Range1416
Interquartile range (IQR)452

Descriptive statistics

Standard deviation303.97176
Coefficient of variation (CV)0.65253054
Kurtosis0.93961929
Mean465.83529
Median Absolute Deviation (MAD)219
Skewness0.8506791
Sum39596
Variance92398.83
MonotonicityNot monotonic
2023-12-12T08:37:48.841195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
663 2
 
2.4%
85 2
 
2.4%
439 2
 
2.4%
349 2
 
2.4%
180 2
 
2.4%
1236 1
 
1.2%
669 1
 
1.2%
1111 1
 
1.2%
1443 1
 
1.2%
930 1
 
1.2%
Other values (70) 70
82.4%
ValueCountFrequency (%)
27 1
1.2%
39 1
1.2%
61 1
1.2%
64 1
1.2%
71 1
1.2%
83 1
1.2%
85 2
2.4%
90 1
1.2%
99 1
1.2%
106 1
1.2%
ValueCountFrequency (%)
1443 1
1.2%
1347 1
1.2%
1236 1
1.2%
1111 1
1.2%
1034 1
1.2%
930 1
1.2%
888 1
1.2%
868 1
1.2%
811 1
1.2%
780 1
1.2%

하나은행
Real number (ℝ)

HIGH CORRELATION 

Distinct79
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean313.35294
Minimum7
Maximum979
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:49.066716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile25.8
Q1152
median309
Q3433
95-th percentile697.2
Maximum979
Range972
Interquartile range (IQR)281

Descriptive statistics

Standard deviation215.44034
Coefficient of variation (CV)0.68753253
Kurtosis1.0197608
Mean313.35294
Median Absolute Deviation (MAD)137
Skewness0.90550026
Sum26635
Variance46414.541
MonotonicityNot monotonic
2023-12-12T08:37:49.225378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
433 3
 
3.5%
11 2
 
2.4%
360 2
 
2.4%
333 2
 
2.4%
355 2
 
2.4%
709 1
 
1.2%
468 1
 
1.2%
979 1
 
1.2%
560 1
 
1.2%
319 1
 
1.2%
Other values (69) 69
81.2%
ValueCountFrequency (%)
7 1
1.2%
11 2
2.4%
20 1
1.2%
25 1
1.2%
29 1
1.2%
31 1
1.2%
32 1
1.2%
48 1
1.2%
58 1
1.2%
78 1
1.2%
ValueCountFrequency (%)
979 1
1.2%
959 1
1.2%
913 1
1.2%
717 1
1.2%
709 1
1.2%
650 1
1.2%
644 1
1.2%
586 1
1.2%
585 1
1.2%
560 1
1.2%

광주은행
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.647059
Minimum-5
Maximum48
Zeros22
Zeros (%)25.9%
Negative1
Negative (%)1.2%
Memory size897.0 B
2023-12-12T08:37:49.403749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-5
5-th percentile0
Q10
median8
Q321
95-th percentile40.2
Maximum48
Range53
Interquartile range (IQR)21

Descriptive statistics

Standard deviation13.08553
Coefficient of variation (CV)1.0346698
Kurtosis0.18435819
Mean12.647059
Median Absolute Deviation (MAD)8
Skewness0.99976737
Sum1075
Variance171.23109
MonotonicityNot monotonic
2023-12-12T08:37:49.536246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 22
25.9%
5 5
 
5.9%
7 4
 
4.7%
12 4
 
4.7%
6 4
 
4.7%
8 3
 
3.5%
24 3
 
3.5%
14 3
 
3.5%
18 3
 
3.5%
11 3
 
3.5%
Other values (26) 31
36.5%
ValueCountFrequency (%)
-5 1
 
1.2%
0 22
25.9%
2 1
 
1.2%
3 2
 
2.4%
4 1
 
1.2%
5 5
 
5.9%
6 4
 
4.7%
7 4
 
4.7%
8 3
 
3.5%
9 1
 
1.2%
ValueCountFrequency (%)
48 1
1.2%
47 1
1.2%
44 1
1.2%
42 1
1.2%
41 1
1.2%
37 1
1.2%
36 1
1.2%
34 1
1.2%
33 1
1.2%
32 1
1.2%

대구은행
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct56
Distinct (%)65.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.176471
Minimum0
Maximum220
Zeros17
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:50.010283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114
median42
Q390
95-th percentile190.2
Maximum220
Range220
Interquartile range (IQR)76

Descriptive statistics

Standard deviation59.625653
Coefficient of variation (CV)0.9746501
Kurtosis0.19167635
Mean61.176471
Median Absolute Deviation (MAD)37
Skewness1.0179022
Sum5200
Variance3555.2185
MonotonicityNot monotonic
2023-12-12T08:37:50.180499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17
 
20.0%
14 3
 
3.5%
34 2
 
2.4%
32 2
 
2.4%
66 2
 
2.4%
39 2
 
2.4%
79 2
 
2.4%
143 2
 
2.4%
75 2
 
2.4%
57 2
 
2.4%
Other values (46) 49
57.6%
ValueCountFrequency (%)
0 17
20.0%
6 2
 
2.4%
7 1
 
1.2%
13 1
 
1.2%
14 3
 
3.5%
17 1
 
1.2%
19 1
 
1.2%
20 1
 
1.2%
22 1
 
1.2%
26 2
 
2.4%
ValueCountFrequency (%)
220 1
1.2%
215 1
1.2%
202 1
1.2%
193 1
1.2%
192 1
1.2%
183 1
1.2%
169 1
1.2%
159 1
1.2%
151 1
1.2%
148 1
1.2%

부산은행
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct52
Distinct (%)61.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.023529
Minimum0
Maximum259
Zeros23
Zeros (%)27.1%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:50.347390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median41
Q390
95-th percentile150
Maximum259
Range259
Interquartile range (IQR)90

Descriptive statistics

Standard deviation54.518668
Coefficient of variation (CV)1.0091652
Kurtosis1.498598
Mean54.023529
Median Absolute Deviation (MAD)41
Skewness1.1560452
Sum4592
Variance2972.2852
MonotonicityNot monotonic
2023-12-12T08:37:50.515336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 23
27.1%
46 3
 
3.5%
33 2
 
2.4%
10 2
 
2.4%
17 2
 
2.4%
142 2
 
2.4%
105 2
 
2.4%
18 2
 
2.4%
91 2
 
2.4%
87 2
 
2.4%
Other values (42) 43
50.6%
ValueCountFrequency (%)
0 23
27.1%
5 1
 
1.2%
10 2
 
2.4%
14 1
 
1.2%
17 2
 
2.4%
18 2
 
2.4%
21 1
 
1.2%
22 1
 
1.2%
25 1
 
1.2%
30 1
 
1.2%
ValueCountFrequency (%)
259 1
1.2%
203 1
1.2%
176 1
1.2%
160 1
1.2%
152 1
1.2%
142 2
2.4%
133 1
1.2%
123 1
1.2%
118 1
1.2%
116 1
1.2%

전북은행
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.858824
Minimum0
Maximum65
Zeros36
Zeros (%)42.4%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:50.674513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q321
95-th percentile42.8
Maximum65
Range65
Interquartile range (IQR)21

Descriptive statistics

Standard deviation16.017961
Coefficient of variation (CV)1.2456786
Kurtosis1.1008871
Mean12.858824
Median Absolute Deviation (MAD)5
Skewness1.2899759
Sum1093
Variance256.57507
MonotonicityNot monotonic
2023-12-12T08:37:50.843166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 36
42.4%
3 5
 
5.9%
18 4
 
4.7%
21 3
 
3.5%
16 3
 
3.5%
28 3
 
3.5%
14 2
 
2.4%
13 2
 
2.4%
11 2
 
2.4%
17 2
 
2.4%
Other values (21) 23
27.1%
ValueCountFrequency (%)
0 36
42.4%
3 5
 
5.9%
4 1
 
1.2%
5 2
 
2.4%
7 1
 
1.2%
10 1
 
1.2%
11 2
 
2.4%
13 2
 
2.4%
14 2
 
2.4%
15 1
 
1.2%
ValueCountFrequency (%)
65 1
1.2%
59 1
1.2%
55 1
1.2%
49 1
1.2%
43 1
1.2%
42 2
2.4%
38 1
1.2%
36 1
1.2%
35 1
1.2%
33 1
1.2%

경남은행
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.035294
Minimum0
Maximum105
Zeros48
Zeros (%)56.5%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:51.038469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q319
95-th percentile57.8
Maximum105
Range105
Interquartile range (IQR)19

Descriptive statistics

Standard deviation20.713722
Coefficient of variation (CV)1.7210815
Kurtosis6.1283688
Mean12.035294
Median Absolute Deviation (MAD)0
Skewness2.353318
Sum1023
Variance429.05826
MonotonicityNot monotonic
2023-12-12T08:37:51.195011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 48
56.5%
32 3
 
3.5%
5 3
 
3.5%
11 2
 
2.4%
37 2
 
2.4%
28 2
 
2.4%
29 1
 
1.2%
15 1
 
1.2%
75 1
 
1.2%
12 1
 
1.2%
Other values (21) 21
24.7%
ValueCountFrequency (%)
0 48
56.5%
2 1
 
1.2%
4 1
 
1.2%
5 3
 
3.5%
6 1
 
1.2%
8 1
 
1.2%
9 1
 
1.2%
10 1
 
1.2%
11 2
 
2.4%
12 1
 
1.2%
ValueCountFrequency (%)
105 1
 
1.2%
81 1
 
1.2%
75 1
 
1.2%
68 1
 
1.2%
63 1
 
1.2%
37 2
2.4%
36 1
 
1.2%
34 1
 
1.2%
33 1
 
1.2%
32 3
3.5%

외환은행
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)27.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.988235
Minimum0
Maximum169
Zeros61
Zeros (%)71.8%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-12T08:37:51.366856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q365
95-th percentile155.2
Maximum169
Range169
Interquartile range (IQR)65

Descriptive statistics

Standard deviation56.894952
Coefficient of variation (CV)1.7247043
Kurtosis0.25592027
Mean32.988235
Median Absolute Deviation (MAD)0
Skewness1.3694503
Sum2804
Variance3237.0356
MonotonicityNot monotonic
2023-12-12T08:37:51.557866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 61
71.8%
169 2
 
2.4%
168 2
 
2.4%
101 1
 
1.2%
111 1
 
1.2%
141 1
 
1.2%
128 1
 
1.2%
156 1
 
1.2%
72 1
 
1.2%
124 1
 
1.2%
Other values (13) 13
 
15.3%
ValueCountFrequency (%)
0 61
71.8%
27 1
 
1.2%
62 1
 
1.2%
65 1
 
1.2%
72 1
 
1.2%
80 1
 
1.2%
83 1
 
1.2%
84 1
 
1.2%
94 1
 
1.2%
101 1
 
1.2%
ValueCountFrequency (%)
169 2
2.4%
168 2
2.4%
156 1
1.2%
152 1
1.2%
148 1
1.2%
144 1
1.2%
141 1
1.2%
140 1
1.2%
128 1
1.2%
124 1
1.2%

기타
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
0
83 
5
 
1
7
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)2.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 83
97.6%
5 1
 
1.2%
7 1
 
1.2%

Length

2023-12-12T08:37:51.703849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:51.858358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 83
97.6%
5 1
 
1.2%
7 1
 
1.2%

Interactions

2023-12-12T08:37:44.274692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:23.631034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:25.074931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:26.376830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:27.859309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:29.344014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:30.649705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:32.181694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:33.549221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.760887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:35.924786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:37.570429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:39.226651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:40.905563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:42.393887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:44.421214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:23.708157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:25.176661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:26.479295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:27.961050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:29.470009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:30.731692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:32.283376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:33.637009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.846686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:36.042497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:37.671843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:39.351532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:40.996051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:42.493284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:44.536605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:23.778976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:25.252862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:26.570398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:28.048554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:29.562253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:30.810048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:32.369968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:33.714457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.922318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:36.127300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:37.781770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:39.467569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:41.106704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:42.572163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:44.636941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:23.848981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:25.325944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:26.657729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:28.161533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:29.651792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:31.159917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:32.470975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:33.791185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.992352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:36.206038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:37.899083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:39.579756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:41.211626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:42.659814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:44.749534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:23.923142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:25.401019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:26.733163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:28.250115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:29.744436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:31.230319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:32.558785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:33.861197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:35.063204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:36.286923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:38.003150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:39.688896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:41.297353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:42.762143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:44.893118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:24.000009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:25.480546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:26.824779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:28.356176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:29.845037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:31.333020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:32.651608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:33.945254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:35.168902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:36.388567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:38.126939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:39.807245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:41.398820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:42.866126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:45.018254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:24.067125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:25.553310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:26.909312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:28.454949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:29.926436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:31.410506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:32.764755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.022611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:35.244040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:36.464276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:38.229685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:39.918227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:41.479500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:42.965607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:45.124651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:24.163954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:25.624050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:26.994134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:28.555302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:29.999906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:31.478803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:32.839690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.113989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:35.318784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:36.538330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:38.345575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:40.012331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:41.579191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:43.073283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:45.233077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:24.259072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:25.730465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:27.114457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:28.668482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:30.081830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:31.559898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:32.952317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.206421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:35.405670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:36.626212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:38.439615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:40.196950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:41.693949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:43.213878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:45.352707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:24.338645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:25.839803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:27.211141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:28.770353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:30.157615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:31.626937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:33.045492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.289108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:35.479530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:37.006004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:38.565139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:40.292393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:41.815127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:43.325166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:45.473856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:24.415693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:25.937896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:27.294212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:28.867591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:30.238617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:31.699769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:33.137922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.365724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:35.550413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:37.108469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:38.681216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:40.388569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:41.902532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:43.431092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:45.604301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:24.488551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:26.024429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:27.394037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:28.949418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:30.316053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:31.763820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:33.217391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.448370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:35.616208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:37.193323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:38.789101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:40.483608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:41.979453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:43.532078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:45.710953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:24.565018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:26.105046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:27.498002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:29.034998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:30.386221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:31.836604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:33.287932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.524175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:35.690309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:37.275826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:38.885401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:40.572989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:42.072891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:43.655428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:45.811617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:24.875858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:26.196365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:27.608927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:29.139762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:30.463867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:31.969433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:33.363262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.604533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:35.766574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:37.378339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:38.993108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:40.677051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:42.157927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:44.060175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:45.921904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:24.959630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:26.276740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:27.705365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:29.235280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:30.555083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:32.080986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:33.463861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:34.679816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:35.835965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:37.472268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:39.108473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:40.789937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:42.263254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:44.152592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:37:51.985369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년기준월합계국민은행기업은행농협은행신한은행우리은행하나은행광주은행대구은행부산은행전북은행경남은행외환은행기타
기준년1.0000.0000.6240.6000.1330.7090.6130.5640.5100.5840.6480.4630.3080.4740.6210.000
기준월0.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.2010.2180.0000.1920.000
합계0.6240.0001.0000.9300.6270.8840.9160.9500.8300.7910.8390.7940.7850.7590.2220.000
국민은행0.6000.0000.9301.0000.6810.7230.8940.8400.9160.5700.6580.8980.7000.7270.0000.000
기업은행0.1330.0000.6270.6811.0000.6250.5910.6180.7280.4430.5430.5800.5090.3810.0000.000
농협은행0.7090.0000.8840.7230.6251.0000.7200.8830.6710.6530.7910.6350.7650.6230.5970.504
신한은행0.6130.0000.9160.8940.5910.7201.0000.8110.7370.6440.6390.7770.6460.8520.3310.046
우리은행0.5640.0000.9500.8400.6180.8830.8111.0000.8150.7460.8160.7720.8270.6570.1630.597
하나은행0.5100.0000.8300.9160.7280.6710.7370.8151.0000.5110.5960.7940.5870.5890.0000.336
광주은행0.5840.0000.7910.5700.4430.6530.6440.7460.5111.0000.7610.4390.6940.3590.3870.526
대구은행0.6480.0000.8390.6580.5430.7910.6390.8160.5960.7611.0000.6790.8390.4680.5640.647
부산은행0.4630.2010.7940.8980.5800.6350.7770.7720.7940.4390.6791.0000.8080.7320.6490.948
전북은행0.3080.2180.7850.7000.5090.7650.6460.8270.5870.6940.8390.8081.0000.5800.5790.799
경남은행0.4740.0000.7590.7270.3810.6230.8520.6570.5890.3590.4680.7320.5801.0000.4330.000
외환은행0.6210.1920.2220.0000.0000.5970.3310.1630.0000.3870.5640.6490.5790.4331.0000.601
기타0.0000.0000.0000.0000.0000.5040.0460.5970.3360.5260.6470.9480.7990.0000.6011.000
2023-12-12T08:37:52.163855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년기준월합계국민은행기업은행농협은행신한은행우리은행하나은행광주은행대구은행부산은행전북은행경남은행외환은행기타
기준년1.000-0.0320.8410.7580.6270.8990.8050.8270.7370.6830.8600.8210.7810.7350.7640.000
기준월-0.0321.0000.1600.1440.1150.0760.1610.1270.1270.0150.0490.1130.1670.0230.0410.000
합계0.8410.1601.0000.9710.7810.9260.9690.9450.9140.6300.8150.8090.8080.7500.5140.000
국민은행0.7580.1440.9711.0000.7600.8600.9370.8760.8790.6070.7490.7660.7690.6810.3900.000
기업은행0.6270.1150.7810.7601.0000.7030.7370.7320.6810.3790.5900.6110.5670.5520.3490.000
농협은행0.8990.0760.9260.8600.7031.0000.8740.8840.8370.6610.8400.7920.8130.7420.6590.333
신한은행0.8050.1610.9690.9370.7370.8741.0000.9230.8800.6260.7790.7670.7460.7170.4640.000
우리은행0.8270.1270.9450.8760.7320.8840.9231.0000.8710.5960.7890.7620.7550.7460.5280.421
하나은행0.7370.1270.9140.8790.6810.8370.8800.8711.0000.6060.7360.7170.7310.6430.3980.147
광주은행0.6830.0150.6300.6070.3790.6610.6260.5960.6061.0000.7060.5460.5870.4240.4510.353
대구은행0.8600.0490.8150.7490.5900.8400.7790.7890.7360.7061.0000.7790.7420.6270.6160.473
부산은행0.8210.1130.8090.7660.6110.7920.7670.7620.7170.5460.7791.0000.7870.6620.5590.703
전북은행0.7810.1670.8080.7690.5670.8130.7460.7550.7310.5870.7420.7871.0000.6220.5230.663
경남은행0.7350.0230.7500.6810.5520.7420.7170.7460.6430.4240.6270.6620.6221.0000.5130.000
외환은행0.7640.0410.5140.3900.3490.6590.4640.5280.3980.4510.6160.5590.5230.5131.0000.312
기타0.0000.0000.0000.0000.0000.3330.0000.4210.1470.3530.4730.7030.6630.0000.3121.000

Missing values

2023-12-12T08:37:46.106598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:37:46.384596image/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

기준년기준월합계국민은행기업은행농협은행신한은행우리은행하나은행광주은행대구은행부산은행전북은행경남은행외환은행기타
0200814012013713983580000000
1200822611901114627110000000
22008347627531302985250000000
32008456828875315111670000000
4200858604463649126611420000000
5200869845825093115115290000000
6200871002579246914999820000000
7200885901733634209106320000000
8200896894107505290810000000
920081010515427054194180110000000
기준년기준월합계국민은행기업은행농협은행신한은행우리은행하나은행광주은행대구은행부산은행전북은행경남은행외환은행기타
752014458351973267761107574358524215583301010
76201455227191524952897272135526202911881440
77201464364160014262172253036028119123380800
7820147432914672195789046741892491832314620
792014841031311122528796544386301514732321240
8020149422314322365306326513515148874237720
8120141050161819138694751663433261921161851565
82201411463415661305078387104336193912841280
832014126119209323776010328885224812020349201417
8420151550720131595831043811447421598815361110