Overview

Dataset statistics

Number of variables39
Number of observations1000
Missing cells3000
Missing cells (%)7.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory339.0 KiB
Average record size in memory347.1 B

Variable types

Categorical26
Numeric9
Boolean1
Unsupported3

Dataset

Description한국주택금융공사 유동화자산부 업무 관련 공개 공공데이터 (해당 부서의 업무와 관련된 데이터베이스에서 공개 가능한 원천 데이터) 유동화계획코드,인수코드,납입회차,취급기관코드,매입시대출잔액,상환금액,대출잔액,청구금액,청구이자금액,청구연체료금액,원리금균등액,잔여회차,처리완료여부와 관련된 정보가 포함되어있습니다.
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15072813/fileData.do

Alerts

REPAY_AMT has constant value ""Constant
DDELAY_FEE_AMT has constant value ""Constant
CDELAY_FEE_AMT has constant value ""Constant
CRDELAY_FEE_AMT has constant value ""Constant
AREPAY_AMT has constant value ""Constant
AREPAY_INT_AMT has constant value ""Constant
EOUT_INT_AMT has constant value ""Constant
PDELAY_FEE_AMT has constant value ""Constant
DELAY_AMT has constant value ""Constant
DPRMS_INT_AMT has constant value ""Constant
DELAY_DCNT has constant value ""Constant
APAY_USE_DCNT has constant value ""Constant
APAY_OCCR_DCNT has constant value ""Constant
RDUAPRNINT_DCNT has constant value ""Constant
HREPAY_FEE_AMT has constant value ""Constant
RECKON_DY is highly imbalanced (93.5%)Imbalance
PAY_DY is highly imbalanced (93.5%)Imbalance
PRCSS_YN is highly imbalanced (88.8%)Imbalance
NTRD_APPLY_DY is highly imbalanced (93.4%)Imbalance
PDLAST_APPLY_DY is highly imbalanced (88.8%)Imbalance
RDLAST_APPLY_DY is highly imbalanced (88.8%)Imbalance
RDUALAST_STRT_DY is highly imbalanced (88.8%)Imbalance
HREPAY_AMT is highly imbalanced (98.0%)Imbalance
HREPAY_INT_AMT is highly imbalanced (98.0%)Imbalance
CNVNC_REPAY_YN has 1000 (100.0%) missing valuesMissing
REPURCH_CMPLT_YN has 1000 (100.0%) missing valuesMissing
RDUALAST_APPLY_DY has 1000 (100.0%) missing valuesMissing
CNVNC_REPAY_YN is an unsupported type, check if it needs cleaning or further analysisUnsupported
REPURCH_CMPLT_YN is an unsupported type, check if it needs cleaning or further analysisUnsupported
RDUALAST_APPLY_DY is an unsupported type, check if it needs cleaning or further analysisUnsupported
LOAN_RAMT has 902 (90.2%) zerosZeros
CLLCT_AMT has 985 (98.5%) zerosZeros
CLLCT_INT_AMT has 985 (98.5%) zerosZeros

Reproduction

Analysis started2023-12-12 17:34:45.662167
Analysis finished2023-12-12 17:34:46.111608
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

LIQD_PLAN_CD
Categorical

Distinct27
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
KHFCMB2016S-13
84 
KHFCMB2017S-17
80 
KHFCMB2018S-12
80 
KHFCMB2013S-23
 
62
KHFCMB2018S-04
 
59
Other values (22)
635 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st rowKHFCMB2018S-12
2nd rowKHFCMB2018S-12
3rd rowKHFCMB2018S-12
4th rowKHFCMB2018S-12
5th rowKHFCMB2018S-12

Common Values

ValueCountFrequency (%)
KHFCMB2016S-13 84
 
8.4%
KHFCMB2017S-17 80
 
8.0%
KHFCMB2018S-12 80
 
8.0%
KHFCMB2013S-23 62
 
6.2%
KHFCMB2018S-04 59
 
5.9%
KHFCMB2016S-20 42
 
4.2%
KHFCMB2016S-22 41
 
4.1%
KHFCMB2017S-08 41
 
4.1%
KHFCMB2018S-20 41
 
4.1%
KHFCMB2018S-19 41
 
4.1%
Other values (17) 429
42.9%

Length

2023-12-13T02:34:46.181376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
khfcmb2016s-13 84
 
8.4%
khfcmb2018s-12 80
 
8.0%
khfcmb2017s-17 80
 
8.0%
khfcmb2013s-23 62
 
6.2%
khfcmb2018s-04 59
 
5.9%
khfcmb2016s-20 42
 
4.2%
khfcmb2016s-22 41
 
4.1%
khfcmb2017s-08 41
 
4.1%
khfcmb2018s-20 41
 
4.1%
khfcmb2018s-19 41
 
4.1%
Other values (17) 429
42.9%

HOLD_CD
Categorical

Distinct29
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
B088-2016-0057
84 
B023-2018-0032
80 
B027-2013-0013
 
62
B088-2018-0014
 
59
B088-2016-0092
 
42
Other values (24)
673 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st rowB023-2018-0032
2nd rowB023-2018-0032
3rd rowB023-2018-0032
4th rowB023-2018-0032
5th rowB023-2018-0032

Common Values

ValueCountFrequency (%)
B088-2016-0057 84
 
8.4%
B023-2018-0032 80
 
8.0%
B027-2013-0013 62
 
6.2%
B088-2018-0014 59
 
5.9%
B088-2016-0092 42
 
4.2%
B088-2016-0105 41
 
4.1%
B020-2017-0044 41
 
4.1%
B088-2018-0058 41
 
4.1%
B023-2018-0047 41
 
4.1%
B023-2019-0040 41
 
4.1%
Other values (19) 468
46.8%

Length

2023-12-13T02:34:46.309330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
b088-2016-0057 84
 
8.4%
b023-2018-0032 80
 
8.0%
b027-2013-0013 62
 
6.2%
b088-2018-0014 59
 
5.9%
b088-2016-0092 42
 
4.2%
b088-2016-0105 41
 
4.1%
b020-2017-0044 41
 
4.1%
b088-2018-0058 41
 
4.1%
b023-2018-0047 41
 
4.1%
b023-2019-0040 41
 
4.1%
Other values (19) 468
46.8%

PAY_SEQ
Real number (ℝ)

Distinct303
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean217.61
Minimum8
Maximum360
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T02:34:46.425228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile67.95
Q1142
median233
Q3282
95-th percentile348
Maximum360
Range352
Interquartile range (IQR)140

Descriptive statistics

Standard deviation88.223689
Coefficient of variation (CV)0.40542112
Kurtosis-0.98462984
Mean217.61
Median Absolute Deviation (MAD)78
Skewness-0.22472107
Sum217610
Variance7783.4193
MonotonicityNot monotonic
2023-12-13T02:34:46.552177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38 13
 
1.3%
246 7
 
0.7%
245 7
 
0.7%
258 6
 
0.6%
343 6
 
0.6%
261 6
 
0.6%
257 6
 
0.6%
236 6
 
0.6%
235 6
 
0.6%
234 6
 
0.6%
Other values (293) 931
93.1%
ValueCountFrequency (%)
8 1
 
0.1%
38 13
1.3%
39 2
 
0.2%
40 2
 
0.2%
41 2
 
0.2%
42 2
 
0.2%
43 2
 
0.2%
44 2
 
0.2%
45 2
 
0.2%
46 2
 
0.2%
ValueCountFrequency (%)
360 4
0.4%
359 4
0.4%
358 4
0.4%
357 4
0.4%
356 4
0.4%
355 4
0.4%
354 4
0.4%
353 4
0.4%
352 4
0.4%
351 4
0.4%

TREAT_ORG_CD
Categorical

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
B088
418 
B020
242 
B023
202 
B003
76 
B027
62 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB023
2nd rowB023
3rd rowB023
4th rowB023
5th rowB023

Common Values

ValueCountFrequency (%)
B088 418
41.8%
B020 242
24.2%
B023 202
20.2%
B003 76
 
7.6%
B027 62
 
6.2%

Length

2023-12-13T02:34:46.707527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:46.807129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b088 418
41.8%
b020 242
24.2%
b023 202
20.2%
b003 76
 
7.6%
b027 62
 
6.2%

BHOUR_LOAN_RAMT
Real number (ℝ)

Distinct43
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1611045 × 108
Minimum14500000
Maximum3.9707145 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T02:34:46.921849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14500000
5-th percentile19963819
Q159760741
median93828798
Q31.6553889 × 108
95-th percentile2.4655014 × 108
Maximum3.9707145 × 108
Range3.8257145 × 108
Interquartile range (IQR)1.0577815 × 108

Descriptive statistics

Standard deviation77895653
Coefficient of variation (CV)0.67087549
Kurtosis1.9732772
Mean1.1611045 × 108
Median Absolute Deviation (MAD)52933729
Skewness1.2196953
Sum1.1611045 × 1011
Variance6.0677327 × 1015
MonotonicityNot monotonic
2023-12-13T02:34:47.068918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
199698769 59
 
5.9%
80000000 43
 
4.3%
19963819 42
 
4.2%
89000000 42
 
4.2%
149770465 42
 
4.2%
59760741 41
 
4.1%
99682027 41
 
4.1%
49860792 41
 
4.1%
29954335 41
 
4.1%
104811334 41
 
4.1%
Other values (33) 567
56.7%
ValueCountFrequency (%)
14500000 20
2.0%
19963819 42
4.2%
24320256 26
2.6%
29954335 41
4.1%
35000000 16
 
1.6%
44851865 40
4.0%
49860792 41
4.1%
50000000 15
 
1.5%
59760741 41
4.1%
63918000 1
 
0.1%
ValueCountFrequency (%)
397071451 22
2.2%
374850000 1
 
0.1%
345100000 1
 
0.1%
299044420 1
 
0.1%
287000000 1
 
0.1%
248546846 1
 
0.1%
246550138 40
4.0%
239608908 1
 
0.1%
224000000 40
4.0%
206000000 1
 
0.1%

REPAY_AMT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:47.210075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:47.311857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

LOAN_RAMT
Real number (ℝ)

ZEROS 

Distinct99
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6645174.1
Minimum0
Maximum3.1815 × 108
Zeros902
Zeros (%)90.2%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T02:34:47.451831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile67917842
Maximum3.1815 × 108
Range3.1815 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation25600794
Coefficient of variation (CV)3.8525393
Kurtosis55.138202
Mean6645174.1
Median Absolute Deviation (MAD)0
Skewness6.2039268
Sum6.6451741 × 109
Variance6.5540067 × 1014
MonotonicityNot monotonic
2023-12-13T02:34:47.671851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 902
90.2%
65339723 1
 
0.1%
69583334 1
 
0.1%
69163015 1
 
0.1%
68741803 1
 
0.1%
68319696 1
 
0.1%
67896692 1
 
0.1%
67472789 1
 
0.1%
67047985 1
 
0.1%
66622278 1
 
0.1%
Other values (89) 89
 
8.9%
ValueCountFrequency (%)
0 902
90.2%
1550092 1
 
0.1%
3096559 1
 
0.1%
4639426 1
 
0.1%
6178702 1
 
0.1%
7714394 1
 
0.1%
9246511 1
 
0.1%
10775062 1
 
0.1%
12300054 1
 
0.1%
13821496 1
 
0.1%
ValueCountFrequency (%)
318150000 1
0.1%
292900000 1
0.1%
280874534 1
0.1%
196695076 1
0.1%
125763306 1
0.1%
121725460 1
0.1%
97784000 1
0.1%
95062821 1
0.1%
89474000 1
0.1%
83493151 1
0.1%

DEMND_AMT
Real number (ℝ)

Distinct805
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean345615.71
Minimum1748
Maximum1575000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T02:34:47.862212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1748
5-th percentile38530.7
Q1138888
median298673
Q3461111
95-th percentile742327.95
Maximum1575000
Range1573252
Interquartile range (IQR)322223

Descriptive statistics

Standard deviation272626.7
Coefficient of variation (CV)0.78881456
Kurtosis5.9776464
Mean345615.71
Median Absolute Deviation (MAD)159785
Skewness2.0170644
Sum3.4561571 × 108
Variance7.432532 × 1010
MonotonicityNot monotonic
2023-12-13T02:34:48.033037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
247222 42
 
4.2%
461111 41
 
4.1%
138888 41
 
4.1%
67744 26
 
2.6%
376585 18
 
1.8%
91666 16
 
1.6%
1748 15
 
1.5%
269501 3
 
0.3%
277000 2
 
0.2%
95413 1
 
0.1%
Other values (795) 795
79.5%
ValueCountFrequency (%)
1748 15
1.5%
35630 1
 
0.1%
35710 1
 
0.1%
35790 1
 
0.1%
35870 1
 
0.1%
35951 1
 
0.1%
36031 1
 
0.1%
36112 1
 
0.1%
36193 1
 
0.1%
36274 1
 
0.1%
ValueCountFrequency (%)
1575000 1
0.1%
1550092 1
0.1%
1546467 1
0.1%
1542867 1
0.1%
1539276 1
0.1%
1535692 1
0.1%
1532117 1
0.1%
1528551 1
0.1%
1524992 1
0.1%
1521442 1
0.1%

DEMND_INT_AMT
Real number (ℝ)

Distinct997
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112116.81
Minimum303
Maximum901519
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T02:34:48.213196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum303
5-th percentile4118.4
Q124204.25
median63764
Q3160376
95-th percentile297608.9
Maximum901519
Range901216
Interquartile range (IQR)136171.75

Descriptive statistics

Standard deviation125948.83
Coefficient of variation (CV)1.1233716
Kurtosis6.3956869
Mean112116.81
Median Absolute Deviation (MAD)52758
Skewness2.2214724
Sum1.1211681 × 108
Variance1.5863108 × 1010
MonotonicityNot monotonic
2023-12-13T02:34:48.396910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1247 2
 
0.2%
45103 2
 
0.2%
259595 2
 
0.2%
545578 1
 
0.1%
550299 1
 
0.1%
549124 1
 
0.1%
547946 1
 
0.1%
546764 1
 
0.1%
544388 1
 
0.1%
552638 1
 
0.1%
Other values (987) 987
98.7%
ValueCountFrequency (%)
303 1
0.1%
417 1
0.1%
606 1
0.1%
833 1
0.1%
908 1
0.1%
994 1
0.1%
1030 1
0.1%
1185 1
0.1%
1191 1
0.1%
1199 1
0.1%
ValueCountFrequency (%)
901519 1
0.1%
832383 1
0.1%
806694 1
0.1%
566564 1
0.1%
559567 1
0.1%
558421 1
0.1%
557271 1
0.1%
556118 1
0.1%
554962 1
0.1%
553802 1
0.1%

DDELAY_FEE_AMT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:48.550462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:48.657563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

PRNINTEVEN_AMT
Real number (ℝ)

Distinct43
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean448954.28
Minimum1748
Maximum1575000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T02:34:48.769576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1748
5-th percentile62363
Q1195842
median378785
Q3601295
95-th percentile995320
Maximum1575000
Range1573252
Interquartile range (IQR)405453

Descriptive statistics

Standard deviation324603.29
Coefficient of variation (CV)0.7230208
Kurtosis1.4247317
Mean448954.28
Median Absolute Deviation (MAD)222510
Skewness1.1484192
Sum4.4895428 × 108
Variance1.0536729 × 1011
MonotonicityNot monotonic
2023-12-13T02:34:49.315132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
926231 59
 
5.9%
62363 42
 
4.2%
332127 42
 
4.2%
247222 42
 
4.2%
677576 42
 
4.2%
118799 41
 
4.1%
446258 41
 
4.1%
138888 41
 
4.1%
137915 41
 
4.1%
427541 41
 
4.1%
Other values (33) 568
56.8%
ValueCountFrequency (%)
1748 15
 
1.5%
62363 42
4.2%
67744 26
2.6%
90000 1
 
0.1%
91666 16
 
1.6%
118799 41
4.1%
137682 20
2.0%
137915 41
4.1%
138888 41
4.1%
195842 40
4.0%
ValueCountFrequency (%)
1575000 1
 
0.1%
1553692 22
 
2.2%
1450000 1
 
0.1%
1337106 1
 
0.1%
995320 40
4.0%
937436 1
 
0.1%
926231 59
5.9%
917475 40
4.0%
677576 42
4.2%
647848 40
4.0%

RECKON_DY
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
<NA>
982 
20201021
 
14
20191007
 
2
20191008
 
1
20201022
 
1

Length

Max length8
Median length4
Mean length4.072
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 982
98.2%
20201021 14
 
1.4%
20191007 2
 
0.2%
20191008 1
 
0.1%
20201022 1
 
0.1%

Length

2023-12-13T02:34:49.527568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:49.708048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 982
98.2%
20201021 14
 
1.4%
20191007 2
 
0.2%
20191008 1
 
0.1%
20201022 1
 
0.1%

PAY_DY
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
<NA>
982 
20201021
 
14
20191007
 
2
20191008
 
1
20201022
 
1

Length

Max length8
Median length4
Mean length4.072
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 982
98.2%
20201021 14
 
1.4%
20191007 2
 
0.2%
20191008 1
 
0.1%
20201022 1
 
0.1%

Length

2023-12-13T02:34:49.878010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:50.031899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 982
98.2%
20201021 14
 
1.4%
20191007 2
 
0.2%
20191008 1
 
0.1%
20201022 1
 
0.1%

CLLCT_AMT
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6935.739
Minimum0
Maximum1575000
Zeros985
Zeros (%)98.5%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T02:34:50.141193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1575000
Range1575000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation76987.879
Coefficient of variation (CV)11.10017
Kurtosis301.19684
Mean6935.739
Median Absolute Deviation (MAD)0
Skewness16.240165
Sum6935739
Variance5.9271335 × 109
MonotonicityNot monotonic
2023-12-13T02:34:50.275844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 985
98.5%
277000 2
 
0.2%
239603 1
 
0.1%
90000 1
 
0.1%
229515 1
 
0.1%
144027 1
 
0.1%
370872 1
 
0.1%
267335 1
 
0.1%
237128 1
 
0.1%
1450000 1
 
0.1%
Other values (5) 5
 
0.5%
ValueCountFrequency (%)
0 985
98.5%
90000 1
 
0.1%
144027 1
 
0.1%
229515 1
 
0.1%
237128 1
 
0.1%
239603 1
 
0.1%
267335 1
 
0.1%
277000 2
 
0.2%
304847 1
 
0.1%
370872 1
 
0.1%
ValueCountFrequency (%)
1575000 1
0.1%
1450000 1
0.1%
541000 1
0.1%
530412 1
0.1%
402000 1
0.1%
370872 1
0.1%
304847 1
0.1%
277000 2
0.2%
267335 1
0.1%
239603 1
0.1%

CLLCT_INT_AMT
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5418.295
Minimum0
Maximum901519
Zeros985
Zeros (%)98.5%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T02:34:50.436546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum901519
Range901519
Interquartile range (IQR)0

Descriptive statistics

Standard deviation55087.568
Coefficient of variation (CV)10.166956
Kurtosis179.518
Mean5418.295
Median Absolute Deviation (MAD)0
Skewness12.778909
Sum5418295
Variance3.0346402 × 109
MonotonicityNot monotonic
2023-12-13T02:34:50.554600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 985
98.5%
832383 1
 
0.1%
901519 1
 
0.1%
240220 1
 
0.1%
806694 1
 
0.1%
253068 1
 
0.1%
126837 1
 
0.1%
230553 1
 
0.1%
362251 1
 
0.1%
225058 1
 
0.1%
Other values (6) 6
 
0.6%
ValueCountFrequency (%)
0 985
98.5%
45045 1
 
0.1%
82737 1
 
0.1%
126837 1
 
0.1%
174721 1
 
0.1%
220025 1
 
0.1%
225058 1
 
0.1%
230553 1
 
0.1%
240220 1
 
0.1%
253068 1
 
0.1%
ValueCountFrequency (%)
901519 1
0.1%
832383 1
0.1%
806694 1
0.1%
566564 1
0.1%
362251 1
0.1%
350620 1
0.1%
253068 1
0.1%
240220 1
0.1%
230553 1
0.1%
225058 1
0.1%

CDELAY_FEE_AMT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:50.707335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:50.827155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

CRDELAY_FEE_AMT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:50.941805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:51.040600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

AREPAY_AMT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:51.158316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:51.272547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

AREPAY_INT_AMT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:51.388764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:51.478706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

EOUT_INT_AMT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:51.571903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:51.670549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

PDELAY_FEE_AMT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:51.777370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:51.890379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

DELAY_AMT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:52.004476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:52.091527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

DPRMS_INT_AMT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:52.197234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:52.315308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

DELAY_DCNT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:52.436801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:52.562495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

APAY_USE_DCNT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:52.679779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:52.790148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

APAY_OCCR_DCNT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:52.897951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:53.004754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

RMN_SEQ
Real number (ℝ)

Distinct281
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.07
Minimum0
Maximum352
Zeros7
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T02:34:53.128947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q143
median104
Q3153
95-th percentile271.05
Maximum352
Range352
Interquartile range (IQR)110

Descriptive statistics

Standard deviation86.150944
Coefficient of variation (CV)0.73589257
Kurtosis-0.59675242
Mean117.07
Median Absolute Deviation (MAD)57.5
Skewness0.61242148
Sum117070
Variance7421.9851
MonotonicityNot monotonic
2023-12-13T02:34:53.323626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17 9
 
0.9%
322 8
 
0.8%
18 8
 
0.8%
16 8
 
0.8%
15 8
 
0.8%
14 8
 
0.8%
13 8
 
0.8%
102 7
 
0.7%
6 7
 
0.7%
0 7
 
0.7%
Other values (271) 922
92.2%
ValueCountFrequency (%)
0 7
0.7%
1 7
0.7%
2 7
0.7%
3 7
0.7%
4 7
0.7%
5 7
0.7%
6 7
0.7%
7 7
0.7%
8 7
0.7%
9 7
0.7%
ValueCountFrequency (%)
352 1
 
0.1%
322 8
0.8%
321 1
 
0.1%
320 1
 
0.1%
319 1
 
0.1%
318 1
 
0.1%
317 1
 
0.1%
316 1
 
0.1%
315 1
 
0.1%
314 1
 
0.1%

PRCSS_YN
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
False
985 
True
 
15
ValueCountFrequency (%)
False 985
98.5%
True 15
 
1.5%
2023-12-13T02:34:53.468806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

CNVNC_REPAY_YN
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size8.9 KiB

REPURCH_CMPLT_YN
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size8.9 KiB

NTRD_APPLY_DY
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
<NA>
985 
20201020
 
7
20201021
 
7
20191005
 
1

Length

Max length8
Median length4
Mean length4.06
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 985
98.5%
20201020 7
 
0.7%
20201021 7
 
0.7%
20191005 1
 
0.1%

Length

2023-12-13T02:34:53.604523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:53.754883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 985
98.5%
20201020 7
 
0.7%
20201021 7
 
0.7%
20191005 1
 
0.1%

PDLAST_APPLY_DY
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
<NA>
985 
19000101
 
15

Length

Max length8
Median length4
Mean length4.06
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 985
98.5%
19000101 15
 
1.5%

Length

2023-12-13T02:34:53.909115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:54.023645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 985
98.5%
19000101 15
 
1.5%

RDLAST_APPLY_DY
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
<NA>
985 
19000101
 
15

Length

Max length8
Median length4
Mean length4.06
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 985
98.5%
19000101 15
 
1.5%

Length

2023-12-13T02:34:54.155482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:54.321638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 985
98.5%
19000101 15
 
1.5%

RDUALAST_STRT_DY
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
<NA>
985 
19000101
 
15

Length

Max length8
Median length4
Mean length4.06
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 985
98.5%
19000101 15
 
1.5%

Length

2023-12-13T02:34:54.448888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:54.587296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 985
98.5%
19000101 15
 
1.5%

RDUALAST_APPLY_DY
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size8.9 KiB

RDUAPRNINT_DCNT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:54.708653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:54.802794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

HREPAY_AMT
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
996 
563044
 
1
7516692
 
1
16300000
 
1
50000000
 
1

Length

Max length8
Median length1
Mean length1.025
Min length1

Unique

Unique4 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 996
99.6%
563044 1
 
0.1%
7516692 1
 
0.1%
16300000 1
 
0.1%
50000000 1
 
0.1%

Length

2023-12-13T02:34:54.918488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:55.029772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 996
99.6%
563044 1
 
0.1%
7516692 1
 
0.1%
16300000 1
 
0.1%
50000000 1
 
0.1%

HREPAY_INT_AMT
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
996 
458
 
1
12267
 
1
38015
 
1
117827
 
1

Length

Max length6
Median length1
Mean length1.015
Min length1

Unique

Unique4 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 996
99.6%
458 1
 
0.1%
12267 1
 
0.1%
38015 1
 
0.1%
117827 1
 
0.1%

Length

2023-12-13T02:34:55.160054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:55.274512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 996
99.6%
458 1
 
0.1%
12267 1
 
0.1%
38015 1
 
0.1%
117827 1
 
0.1%

HREPAY_FEE_AMT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1000
100.0%

Length

2023-12-13T02:34:55.414554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:34:55.515414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000
100.0%

Sample

LIQD_PLAN_CDHOLD_CDPAY_SEQTREAT_ORG_CDBHOUR_LOAN_RAMTREPAY_AMTLOAN_RAMTDEMND_AMTDEMND_INT_AMTDDELAY_FEE_AMTPRNINTEVEN_AMTRECKON_DYPAY_DYCLLCT_AMTCLLCT_INT_AMTCDELAY_FEE_AMTCRDELAY_FEE_AMTAREPAY_AMTAREPAY_INT_AMTEOUT_INT_AMTPDELAY_FEE_AMTDELAY_AMTDPRMS_INT_AMTDELAY_DCNTAPAY_USE_DCNTAPAY_OCCR_DCNTRMN_SEQPRCSS_YNCNVNC_REPAY_YNREPURCH_CMPLT_YNNTRD_APPLY_DYPDLAST_APPLY_DYRDLAST_APPLY_DYRDUALAST_STRT_DYRDUALAST_APPLY_DYRDUAPRNINT_DCNTHREPAY_AMTHREPAY_INT_AMTHREPAY_FEE_AMT
0KHFCMB2018S-12B023-2018-0032258B023149770465004951451824310677576<NA><NA>0000000000000102N<NA><NA><NA><NA><NA><NA><NA>0000
1KHFCMB2018S-12B023-2018-0032257B023149770465004936391839370677576<NA><NA>0000000000000103N<NA><NA><NA><NA><NA><NA><NA>0000
2KHFCMB2018S-12B023-2018-0032256B023149770465004921381854380677576<NA><NA>0000000000000104N<NA><NA><NA><NA><NA><NA><NA>0000
3KHFCMB2018S-12B023-2018-0032255B023149770465004906421869340677576<NA><NA>0000000000000105N<NA><NA><NA><NA><NA><NA><NA>0000
4KHFCMB2018S-12B023-2018-0032254B023149770465004891501884260677576<NA><NA>0000000000000106N<NA><NA><NA><NA><NA><NA><NA>0000
5KHFCMB2018S-12B023-2018-0032253B023149770465004876621899140677576<NA><NA>0000000000000107N<NA><NA><NA><NA><NA><NA><NA>0000
6KHFCMB2018S-12B023-2018-0032252B023149770465004861791913970677576<NA><NA>0000000000000108N<NA><NA><NA><NA><NA><NA><NA>0000
7KHFCMB2018S-12B023-2018-0032251B023149770465004847011928750677576<NA><NA>0000000000000109N<NA><NA><NA><NA><NA><NA><NA>0000
8KHFCMB2018S-12B023-2018-0032250B023149770465004832271943490677576<NA><NA>0000000000000110N<NA><NA><NA><NA><NA><NA><NA>0000
9KHFCMB2018S-12B023-2018-0032249B023149770465004817581958180677576<NA><NA>0000000000000111N<NA><NA><NA><NA><NA><NA><NA>0000
LIQD_PLAN_CDHOLD_CDPAY_SEQTREAT_ORG_CDBHOUR_LOAN_RAMTREPAY_AMTLOAN_RAMTDEMND_AMTDEMND_INT_AMTDDELAY_FEE_AMTPRNINTEVEN_AMTRECKON_DYPAY_DYCLLCT_AMTCLLCT_INT_AMTCDELAY_FEE_AMTCRDELAY_FEE_AMTAREPAY_AMTAREPAY_INT_AMTEOUT_INT_AMTPDELAY_FEE_AMTDELAY_AMTDPRMS_INT_AMTDELAY_DCNTAPAY_USE_DCNTAPAY_OCCR_DCNTRMN_SEQPRCSS_YNCNVNC_REPAY_YNREPURCH_CMPLT_YNNTRD_APPLY_DYPDLAST_APPLY_DYRDLAST_APPLY_DYRDUALAST_STRT_DYRDUALAST_APPLY_DYRDUAPRNINT_DCNTHREPAY_AMTHREPAY_INT_AMTHREPAY_FEE_AMT
990KHFCMB2017S-28B003-2017-015638B00334510000002929000001450000832383014500002020102120201021145000083238300000000000202Y<NA><NA>20201020190001011900010119000101<NA>0000
991KHFCMB2017S-28B003-2017-015338B0031834600000813640004020002305530402000202010212020102140200023055300000000000202Y<NA><NA>20201020190001011900010119000101<NA>0000
992KHFCMB2017S-28B003-2017-015338B00363918000044442000541000126837054100020201021202010215410001268370000000000082Y<NA><NA>20201020190001011900010119000101<NA>0000
993KHFCMB2017S-28B003-2017-015338B003994460000894740002770002530680277000202010212020102127700025306800000000000322Y<NA><NA>20201020190001011900010119000101<NA>0000
994KHFCMB2017S-28B003-2017-015338B003299044420028087453453041280669401337106202010212020102153041280669400000000000322Y<NA><NA>20201021190001011900010119000101<NA>0000
995KHFCMB2017S-28B003-2017-015338B0032485468460834931513048472402200545067202010212020102130484724022000000000000202Y<NA><NA>20201021190001011900010119000101<NA>0000
996KHFCMB2017S-28B003-2017-015338B00337485000003181500001575000901519015750002020102120201021157500090151900000000000202Y<NA><NA>20201020190001011900010119000101<NA>0000
997KHFCMB2015S-12B088-2015-0026192B088159872342002695011293340269501<NA><NA>000000000000048N<NA><NA><NA><NA><NA><NA><NA>0000
998KHFCMB2015S-12B088-2015-0026191B088159872342002695011438200269501<NA><NA>000000000000049N<NA><NA><NA><NA><NA><NA><NA>0000
999KHFCMB2015S-12B088-2015-0026190B088159872342002695011444500269501<NA><NA>000000000000050N<NA><NA><NA><NA><NA><NA><NA>0000