Overview

Dataset statistics

Number of variables32
Number of observations409
Missing cells4948
Missing cells (%)37.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory113.2 KiB
Average record size in memory283.3 B

Variable types

Numeric11
Text2
Categorical6
Unsupported12
Boolean1

Dataset

Description한국주택금융공사 채권관리부 업무 관련 공개 공공데이터 (해당 부서의 업무와 관련된 데이터베이스에서 공개 가능한 원천 데이터)
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15073249/fileData.do

Alerts

HDQUAT_BATCH_ACPT_YN has constant value ""Constant
STLE_DVCD is highly imbalanced (59.3%)Imbalance
BR_NN_APPRV_RSCD is highly imbalanced (95.5%)Imbalance
DDRSN_OCCR_DY has 409 (100.0%) missing valuesMissing
DISCHRG_TERM_DY has 409 (100.0%) missing valuesMissing
DISCHRG_ORG_CD has 409 (100.0%) missing valuesMissing
DISCHRG_ORG_NM has 409 (100.0%) missing valuesMissing
RMT_ORG_CD has 27 (6.6%) missing valuesMissing
CANCLE_COM_DY has 409 (100.0%) missing valuesMissing
RETURN_DY has 409 (100.0%) missing valuesMissing
DISCHRG_APPRV_DY has 6 (1.5%) missing valuesMissing
ORG_GUARNT_DY has 409 (100.0%) missing valuesMissing
BBNAPPRV_NOTI_DY has 7 (1.7%) missing valuesMissing
ONLIN_DEMND_YN has 409 (100.0%) missing valuesMissing
UPDT_TS has 409 (100.0%) missing valuesMissing
UPDT_ENO has 409 (100.0%) missing valuesMissing
UPDT_BRCD has 409 (100.0%) missing valuesMissing
REG_TS has 409 (100.0%) missing valuesMissing
TREAT_ENO is highly skewed (γ1 = 20.01242801)Skewed
REG_ENO is highly skewed (γ1 = 20.01242801)Skewed
ACPT_PTNO has unique valuesUnique
DDRSN_OCCR_DY is an unsupported type, check if it needs cleaning or further analysisUnsupported
DISCHRG_TERM_DY is an unsupported type, check if it needs cleaning or further analysisUnsupported
DISCHRG_ORG_CD is an unsupported type, check if it needs cleaning or further analysisUnsupported
DISCHRG_ORG_NM is an unsupported type, check if it needs cleaning or further analysisUnsupported
CANCLE_COM_DY is an unsupported type, check if it needs cleaning or further analysisUnsupported
RETURN_DY is an unsupported type, check if it needs cleaning or further analysisUnsupported
ORG_GUARNT_DY is an unsupported type, check if it needs cleaning or further analysisUnsupported
ONLIN_DEMND_YN is an unsupported type, check if it needs cleaning or further analysisUnsupported
UPDT_TS is an unsupported type, check if it needs cleaning or further analysisUnsupported
UPDT_ENO is an unsupported type, check if it needs cleaning or further analysisUnsupported
UPDT_BRCD is an unsupported type, check if it needs cleaning or further analysisUnsupported
REG_TS is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 16:54:34.404432
Analysis finished2023-12-12 16:54:34.793442
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

ACPT_PTNO
Real number (ℝ)

UNIQUE 

Distinct409
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0173823 × 1010
Minimum2.00804 × 1010
Maximum2.02004 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T01:54:34.874118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.00804 × 1010
5-th percentile2.01304 × 1010
Q12.01604 × 1010
median2.01804 × 1010
Q32.01904 × 1010
95-th percentile2.02004 × 1010
Maximum2.02004 × 1010
Range1.200001 × 108
Interquartile range (IQR)30000054

Descriptive statistics

Standard deviation24344751
Coefficient of variation (CV)0.0012067495
Kurtosis0.33550319
Mean2.0173823 × 1010
Median Absolute Deviation (MAD)19999982
Skewness-0.92617775
Sum8.2510936 × 1012
Variance5.9266688 × 1014
MonotonicityNot monotonic
2023-12-13T01:54:35.330790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200400097 1
 
0.2%
20170400003 1
 
0.2%
20160400052 1
 
0.2%
20160400049 1
 
0.2%
20160400050 1
 
0.2%
20160400053 1
 
0.2%
20160400058 1
 
0.2%
20160400055 1
 
0.2%
20160400057 1
 
0.2%
20170400001 1
 
0.2%
Other values (399) 399
97.6%
ValueCountFrequency (%)
20080400001 1
0.2%
20100400002 1
0.2%
20100400003 1
0.2%
20100400004 1
0.2%
20100400005 1
0.2%
20100400006 1
0.2%
20110400001 1
0.2%
20110400003 1
0.2%
20120400001 1
0.2%
20120400002 1
0.2%
ValueCountFrequency (%)
20200400097 1
0.2%
20200400096 1
0.2%
20200400095 1
0.2%
20200400094 1
0.2%
20200400093 1
0.2%
20200400092 1
0.2%
20200400091 1
0.2%
20200400090 1
0.2%
20200400089 1
0.2%
20200400088 1
0.2%

GUARNT_NO
Text

Distinct408
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-13T01:54:35.620420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters5726
Distinct characters24
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique407 ?
Unique (%)99.5%

Sample

1st rowRTAB2010000171
2nd rowRTPA2016000596
3rd rowRTHO2010000012
4th rowRTBA2017000881
5th rowRQAD2016000534
ValueCountFrequency (%)
rtpa2011000133 2
 
0.5%
rtho2010000073 1
 
0.2%
rtab2012000454 1
 
0.2%
rqad2014000634 1
 
0.2%
rtab2011000214 1
 
0.2%
rqad2009000019 1
 
0.2%
rqad2008000265 1
 
0.2%
rtoa2009000027 1
 
0.2%
rqad2010000509 1
 
0.2%
rtab2011000133 1
 
0.2%
Other values (398) 398
97.3%
2023-12-13T01:54:36.047462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2017
35.2%
2 600
 
10.5%
1 560
 
9.8%
R 409
 
7.1%
A 383
 
6.7%
T 336
 
5.9%
3 166
 
2.9%
4 154
 
2.7%
5 128
 
2.2%
9 121
 
2.1%
Other values (14) 852
14.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4090
71.4%
Uppercase Letter 1636
 
28.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 409
25.0%
A 383
23.4%
T 336
20.5%
B 115
 
7.0%
Q 88
 
5.4%
H 83
 
5.1%
D 77
 
4.7%
O 54
 
3.3%
P 31
 
1.9%
M 20
 
1.2%
Other values (4) 40
 
2.4%
Decimal Number
ValueCountFrequency (%)
0 2017
49.3%
2 600
 
14.7%
1 560
 
13.7%
3 166
 
4.1%
4 154
 
3.8%
5 128
 
3.1%
9 121
 
3.0%
7 121
 
3.0%
8 112
 
2.7%
6 111
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 4090
71.4%
Latin 1636
 
28.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 409
25.0%
A 383
23.4%
T 336
20.5%
B 115
 
7.0%
Q 88
 
5.4%
H 83
 
5.1%
D 77
 
4.7%
O 54
 
3.3%
P 31
 
1.9%
M 20
 
1.2%
Other values (4) 40
 
2.4%
Common
ValueCountFrequency (%)
0 2017
49.3%
2 600
 
14.7%
1 560
 
13.7%
3 166
 
4.1%
4 154
 
3.8%
5 128
 
3.1%
9 121
 
3.0%
7 121
 
3.0%
8 112
 
2.7%
6 111
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5726
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2017
35.2%
2 600
 
10.5%
1 560
 
9.8%
R 409
 
7.1%
A 383
 
6.7%
T 336
 
5.9%
3 166
 
2.9%
4 154
 
2.7%
5 128
 
2.2%
9 121
 
2.1%
Other values (14) 852
14.9%

MDBTR_CUST_NO
Real number (ℝ)

Distinct408
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84785813
Minimum8032944
Maximum1.2861801 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T01:54:36.228173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8032944
5-th percentile52313430
Q174544449
median85787648
Q396867418
95-th percentile1.1557953 × 108
Maximum1.2861801 × 108
Range1.2058507 × 108
Interquartile range (IQR)22322969

Descriptive statistics

Standard deviation20416469
Coefficient of variation (CV)0.24080053
Kurtosis2.3481664
Mean84785813
Median Absolute Deviation (MAD)11092185
Skewness-0.92389707
Sum3.4677397 × 1010
Variance4.168322 × 1014
MonotonicityNot monotonic
2023-12-13T01:54:36.397357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84360781 2
 
0.5%
79584640 1
 
0.2%
79600951 1
 
0.2%
105848315 1
 
0.2%
66300280 1
 
0.2%
88293210 1
 
0.2%
99459043 1
 
0.2%
82978955 1
 
0.2%
8032944 1
 
0.2%
69898508 1
 
0.2%
Other values (398) 398
97.3%
ValueCountFrequency (%)
8032944 1
0.2%
8571201 1
0.2%
8583309 1
0.2%
8833855 1
0.2%
9255348 1
0.2%
16272880 1
0.2%
18931307 1
0.2%
21615348 1
0.2%
23260050 1
0.2%
25547658 1
0.2%
ValueCountFrequency (%)
128618014 1
0.2%
128197962 1
0.2%
126725747 1
0.2%
126546515 1
0.2%
124393498 1
0.2%
123864494 1
0.2%
122844444 1
0.2%
121671867 1
0.2%
120992589 1
0.2%
119588894 1
0.2%

BBR_CD
Categorical

Distinct22
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
TAB
77 
THO
44 
QAD
37 
TAA
28 
TPA
26 
Other values (17)
197 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowTAB
2nd rowTQC
3rd rowTHO
4th rowTBB
5th rowQAD

Common Values

ValueCountFrequency (%)
TAB 77
18.8%
THO 44
10.8%
QAD 37
9.0%
TAA 28
 
6.8%
TPA 26
 
6.4%
TBA 24
 
5.9%
TAC 24
 
5.9%
THA 22
 
5.4%
THB 21
 
5.1%
TAD 20
 
4.9%
Other values (12) 86
21.0%

Length

2023-12-13T01:54:36.552883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tab 77
18.8%
tho 44
10.8%
qad 37
9.0%
taa 28
 
6.8%
tpa 26
 
6.4%
tba 24
 
5.9%
tac 24
 
5.9%
tha 22
 
5.4%
thb 21
 
5.1%
tad 20
 
4.9%
Other values (12) 86
21.0%

STLE_DVCD
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2
347 
1
60 
<NA>
 
2

Length

Max length4
Median length1
Mean length1.0146699
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 347
84.8%
1 60
 
14.7%
<NA> 2
 
0.5%

Length

2023-12-13T01:54:36.706722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:54:36.819615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 347
84.8%
1 60
 
14.7%
na 2
 
0.5%

DDEMND_ACPT_DY
Real number (ℝ)

Distinct336
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20173808
Minimum20080814
Maximum20201023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T01:54:36.966782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080814
5-th percentile20130318
Q120160310
median20180511
Q320190917
95-th percentile20200812
Maximum20201023
Range120209
Interquartile range (IQR)30607

Descriptive statistics

Standard deviation24264.083
Coefficient of variation (CV)0.0012027518
Kurtosis0.33499664
Mean20173808
Median Absolute Deviation (MAD)19506
Skewness-0.92603211
Sum8.2510874 × 109
Variance5.8874574 × 108
MonotonicityNot monotonic
2023-12-13T01:54:37.195225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160216 4
 
1.0%
20161206 3
 
0.7%
20190130 3
 
0.7%
20200918 3
 
0.7%
20200218 3
 
0.7%
20170511 3
 
0.7%
20200814 3
 
0.7%
20200811 3
 
0.7%
20181101 2
 
0.5%
20180927 2
 
0.5%
Other values (326) 380
92.9%
ValueCountFrequency (%)
20080814 1
0.2%
20100329 1
0.2%
20100614 1
0.2%
20100902 1
0.2%
20101005 1
0.2%
20101029 1
0.2%
20110214 1
0.2%
20111111 1
0.2%
20120103 1
0.2%
20120517 1
0.2%
ValueCountFrequency (%)
20201023 1
 
0.2%
20201019 1
 
0.2%
20201013 1
 
0.2%
20200924 1
 
0.2%
20200922 1
 
0.2%
20200918 3
0.7%
20200908 1
 
0.2%
20200902 1
 
0.2%
20200828 1
 
0.2%
20200827 1
 
0.2%

DDRSN_OCCR_DY
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing409
Missing (%)100.0%
Memory size3.7 KiB

DISCHRG_DEMND_DY
Real number (ℝ)

Distinct340
Distinct (%)83.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20173737
Minimum20080814
Maximum20201023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T01:54:37.410020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080814
5-th percentile20130318
Q120160308
median20180509
Q320190917
95-th percentile20200812
Maximum20201023
Range120209
Interquartile range (IQR)30609

Descriptive statistics

Standard deviation24323.609
Coefficient of variation (CV)0.0012057067
Kurtosis0.3221312
Mean20173737
Median Absolute Deviation (MAD)19504
Skewness-0.92320861
Sum8.2510582 × 109
Variance5.9163794 × 108
MonotonicityNot monotonic
2023-12-13T01:54:37.601120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180326 4
 
1.0%
20180615 3
 
0.7%
20200811 3
 
0.7%
20200814 3
 
0.7%
20200218 3
 
0.7%
20190130 3
 
0.7%
20200918 3
 
0.7%
20191023 2
 
0.5%
20180531 2
 
0.5%
20200413 2
 
0.5%
Other values (330) 381
93.2%
ValueCountFrequency (%)
20080814 1
0.2%
20100329 1
0.2%
20100614 1
0.2%
20100902 1
0.2%
20101005 1
0.2%
20101029 1
0.2%
20110214 1
0.2%
20111110 1
0.2%
20120103 1
0.2%
20120517 1
0.2%
ValueCountFrequency (%)
20201023 1
 
0.2%
20201019 1
 
0.2%
20201013 1
 
0.2%
20200924 1
 
0.2%
20200918 3
0.7%
20200917 1
 
0.2%
20200908 1
 
0.2%
20200902 1
 
0.2%
20200828 1
 
0.2%
20200827 1
 
0.2%

DISCHRG_TERM_DY
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing409
Missing (%)100.0%
Memory size3.7 KiB

DISCHRG_ORG_CD
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing409
Missing (%)100.0%
Memory size3.7 KiB

DISCHRG_ORG_NM
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing409
Missing (%)100.0%
Memory size3.7 KiB

RMT_ORG_CD
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)4.5%
Missing27
Missing (%)6.6%
Infinite0
Infinite (%)0.0%
Mean27.97644
Minimum3
Maximum88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T01:54:37.753119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q111
median19
Q331
95-th percentile88
Maximum88
Range85
Interquartile range (IQR)20

Descriptive statistics

Standard deviation27.900027
Coefficient of variation (CV)0.99726868
Kurtosis0.37592404
Mean27.97644
Median Absolute Deviation (MAD)8
Skewness1.4017967
Sum10687
Variance778.41152
MonotonicityNot monotonic
2023-12-13T01:54:37.867335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
19 98
24.0%
11 66
16.1%
4 44
10.8%
20 40
9.8%
88 39
 
9.5%
81 30
 
7.3%
3 13
 
3.2%
31 11
 
2.7%
6 9
 
2.2%
10 8
 
2.0%
Other values (7) 24
 
5.9%
(Missing) 27
 
6.6%
ValueCountFrequency (%)
3 13
 
3.2%
4 44
10.8%
5 1
 
0.2%
6 9
 
2.2%
10 8
 
2.0%
11 66
16.1%
19 98
24.0%
20 40
9.8%
21 4
 
1.0%
26 1
 
0.2%
ValueCountFrequency (%)
88 39
9.5%
81 30
7.3%
39 6
 
1.5%
37 2
 
0.5%
34 2
 
0.5%
32 8
 
2.0%
31 11
 
2.7%
26 1
 
0.2%
21 4
 
1.0%
20 40
9.8%

RMT_CD
Categorical

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
1
205 
2
201 
99
 
2
<NA>
 
1

Length

Max length4
Median length1
Mean length1.0122249
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row2
2nd row1
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 205
50.1%
2 201
49.1%
99 2
 
0.5%
<NA> 1
 
0.2%

Length

2023-12-13T01:54:38.002466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:54:38.151957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 205
50.1%
2 201
49.1%
99 2
 
0.5%
na 1
 
0.2%

CANCLE_COM_DY
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing409
Missing (%)100.0%
Memory size3.7 KiB

RETURN_DY
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing409
Missing (%)100.0%
Memory size3.7 KiB

DISCHRG_APPRV_DY
Real number (ℝ)

MISSING 

Distinct341
Distinct (%)84.6%
Missing6
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean20174284
Minimum20080917
Maximum20201029
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T01:54:38.311216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080917
5-th percentile20130334
Q120160320
median20180531
Q320190924
95-th percentile20200819
Maximum20201029
Range120112
Interquartile range (IQR)30605

Descriptive statistics

Standard deviation24274.783
Coefficient of variation (CV)0.0012032538
Kurtosis0.39614355
Mean20174284
Median Absolute Deviation (MAD)19576
Skewness-0.94795245
Sum8.1302364 × 109
Variance5.892651 × 108
MonotonicityNot monotonic
2023-12-13T01:54:38.512882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190422 4
 
1.0%
20200818 3
 
0.7%
20150310 3
 
0.7%
20180328 3
 
0.7%
20180912 3
 
0.7%
20190909 3
 
0.7%
20200311 3
 
0.7%
20180321 3
 
0.7%
20200903 3
 
0.7%
20200901 2
 
0.5%
Other values (331) 373
91.2%
(Missing) 6
 
1.5%
ValueCountFrequency (%)
20080917 1
0.2%
20100401 1
0.2%
20100616 1
0.2%
20100928 1
0.2%
20101012 1
0.2%
20101109 1
0.2%
20110221 1
0.2%
20111121 1
0.2%
20120214 1
0.2%
20120531 1
0.2%
ValueCountFrequency (%)
20201029 2
0.5%
20201013 1
 
0.2%
20201007 1
 
0.2%
20201005 1
 
0.2%
20200924 1
 
0.2%
20200923 1
 
0.2%
20200922 1
 
0.2%
20200911 1
 
0.2%
20200904 1
 
0.2%
20200903 3
0.7%

ORG_GUARNT_DY
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing409
Missing (%)100.0%
Memory size3.7 KiB

BBNAPPRV_NOTI_DY
Real number (ℝ)

MISSING 

Distinct340
Distinct (%)84.6%
Missing7
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean20174218
Minimum20080917
Maximum20201029
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T01:54:38.666559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080917
5-th percentile20130329
Q120160317
median20180526
Q320190923
95-th percentile20200819
Maximum20201029
Range120112
Interquartile range (IQR)30606

Descriptive statistics

Standard deviation24268.837
Coefficient of variation (CV)0.001202963
Kurtosis0.39405609
Mean20174218
Median Absolute Deviation (MAD)19580.5
Skewness-0.94610148
Sum8.1100356 × 109
Variance5.8897646 × 108
MonotonicityNot monotonic
2023-12-13T01:54:38.811529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190422 4
 
1.0%
20200818 3
 
0.7%
20150310 3
 
0.7%
20180328 3
 
0.7%
20180912 3
 
0.7%
20190909 3
 
0.7%
20200311 3
 
0.7%
20180321 3
 
0.7%
20200903 3
 
0.7%
20200901 2
 
0.5%
Other values (330) 372
91.0%
(Missing) 7
 
1.7%
ValueCountFrequency (%)
20080917 1
0.2%
20100401 1
0.2%
20100616 1
0.2%
20100928 1
0.2%
20101012 1
0.2%
20101109 1
0.2%
20110221 1
0.2%
20111121 1
0.2%
20120214 1
0.2%
20120531 1
0.2%
ValueCountFrequency (%)
20201029 2
0.5%
20201013 1
 
0.2%
20201007 1
 
0.2%
20201005 1
 
0.2%
20200924 1
 
0.2%
20200923 1
 
0.2%
20200922 1
 
0.2%
20200911 1
 
0.2%
20200904 1
 
0.2%
20200903 3
0.7%

TREAT_ENO
Real number (ℝ)

SKEWED 

Distinct153
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1695.0905
Minimum1020
Maximum52549
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T01:54:39.008789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1020
5-th percentile1181.4
Q11425
median1557
Q31692
95-th percentile1917
Maximum52549
Range51529
Interquartile range (IQR)267

Descriptive statistics

Standard deviation2529.5245
Coefficient of variation (CV)1.4922652
Kurtosis403.29821
Mean1695.0905
Median Absolute Deviation (MAD)132
Skewness20.012428
Sum693292
Variance6398494.3
MonotonicityNot monotonic
2023-12-13T01:54:39.196090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1598 20
 
4.9%
1641 14
 
3.4%
1532 13
 
3.2%
1425 13
 
3.2%
1300 12
 
2.9%
1475 11
 
2.7%
1917 10
 
2.4%
1302 10
 
2.4%
1656 10
 
2.4%
1650 8
 
2.0%
Other values (143) 288
70.4%
ValueCountFrequency (%)
1020 2
0.5%
1025 1
 
0.2%
1110 1
 
0.2%
1117 1
 
0.2%
1127 1
 
0.2%
1152 1
 
0.2%
1155 1
 
0.2%
1159 3
0.7%
1160 1
 
0.2%
1163 1
 
0.2%
ValueCountFrequency (%)
52549 1
 
0.2%
2003 1
 
0.2%
2002 1
 
0.2%
2001 1
 
0.2%
1980 1
 
0.2%
1977 2
0.5%
1970 1
 
0.2%
1968 3
0.7%
1938 1
 
0.2%
1937 3
0.7%

PRCSS_DY
Real number (ℝ)

Distinct353
Distinct (%)86.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20174080
Minimum20080820
Maximum20201029
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T01:54:39.403547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080820
5-th percentile20130318
Q120160310
median20180517
Q320190920
95-th percentile20200814
Maximum20201029
Range120209
Interquartile range (IQR)30610

Descriptive statistics

Standard deviation24255.137
Coefficient of variation (CV)0.0012022921
Kurtosis0.35975585
Mean20174080
Median Absolute Deviation (MAD)19590
Skewness-0.93129097
Sum8.2511986 × 109
Variance5.8831166 × 108
MonotonicityNot monotonic
2023-12-13T01:54:39.606797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170511 4
 
1.0%
20200814 4
 
1.0%
20160216 3
 
0.7%
20180622 3
 
0.7%
20200311 3
 
0.7%
20180927 3
 
0.7%
20180911 2
 
0.5%
20180517 2
 
0.5%
20180611 2
 
0.5%
20190422 2
 
0.5%
Other values (343) 381
93.2%
ValueCountFrequency (%)
20080820 1
0.2%
20100331 1
0.2%
20100614 1
0.2%
20100903 1
0.2%
20101012 1
0.2%
20101105 1
0.2%
20110214 1
0.2%
20111118 1
0.2%
20120110 1
0.2%
20120521 1
0.2%
ValueCountFrequency (%)
20201029 1
0.2%
20201026 1
0.2%
20201013 1
0.2%
20200929 1
0.2%
20200924 1
0.2%
20200922 1
0.2%
20200918 2
0.5%
20200908 1
0.2%
20200902 1
0.2%
20200901 1
0.2%

BR_NN_APPRV_RSCD
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
15
407 
<NA>
 
2

Length

Max length4
Median length2
Mean length2.00978
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row15
2nd row15
3rd row15
4th row15
5th row15

Common Values

ValueCountFrequency (%)
15 407
99.5%
<NA> 2
 
0.5%

Length

2023-12-13T01:54:39.790503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:54:39.940993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
15 407
99.5%
na 2
 
0.5%

HDQUAT_BATCH_ACPT_YN
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size541.0 B
False
409 
ValueCountFrequency (%)
False 409
100.0%
2023-12-13T01:54:40.044914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DISCHRG_ACPT_CD
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2
222 
1
187 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 222
54.3%
1 187
45.7%

Length

2023-12-13T01:54:40.152746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:54:40.281550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 222
54.3%
1 187
45.7%

ONLIN_DEMND_YN
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing409
Missing (%)100.0%
Memory size3.7 KiB

DDEMND_PLC_CD
Real number (ℝ)

Distinct299
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean197997.11
Minimum30009
Maximum884857
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T01:54:40.444263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30009
5-th percentile40280.4
Q163694
median115296
Q3213884
95-th percentile815462.8
Maximum884857
Range854848
Interquartile range (IQR)150190

Descriptive statistics

Standard deviation214344.62
Coefficient of variation (CV)1.0825644
Kurtosis3.6826669
Mean197997.11
Median Absolute Deviation (MAD)74935
Skewness2.1164417
Sum80980818
Variance4.5943614 × 1010
MonotonicityNot monotonic
2023-12-13T01:54:40.588889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193496 16
 
3.9%
207146 13
 
3.2%
206244 12
 
2.9%
310062 9
 
2.2%
37167 8
 
2.0%
113117 7
 
1.7%
42110 4
 
1.0%
117032 3
 
0.7%
213884 3
 
0.7%
40921 3
 
0.7%
Other values (289) 331
80.9%
ValueCountFrequency (%)
30009 2
 
0.5%
30119 1
 
0.2%
31163 1
 
0.2%
32311 1
 
0.2%
32829 1
 
0.2%
33297 1
 
0.2%
33514 1
 
0.2%
35240 1
 
0.2%
36980 1
 
0.2%
37167 8
2.0%
ValueCountFrequency (%)
884857 2
0.5%
883117 1
0.2%
882639 1
0.2%
841971 1
0.2%
841379 1
0.2%
841188 1
0.2%
819149 1
0.2%
818739 1
0.2%
818276 1
0.2%
817921 2
0.5%

DDEMND_PLC_NM
Text

Distinct319
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-13T01:54:40.944858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length8.9315403
Min length3

Characters and Unicode

Total characters3653
Distinct characters234
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique278 ?
Unique (%)68.0%

Sample

1st row기업 여신관리부
2nd row농협중앙회 안동시지부지점(영업소)
3rd row신한 인천동구청
4th row국민 구포
5th row우리 파주남(지)
ValueCountFrequency (%)
국민 140
 
16.9%
농협중앙회 47
 
5.7%
우리 40
 
4.8%
신한 40
 
4.8%
여신관리부 38
 
4.6%
하나 22
 
2.7%
농협 20
 
2.4%
농협은행 17
 
2.1%
기업 16
 
1.9%
국민은행 13
 
1.6%
Other values (310) 436
52.6%
2023-12-13T01:54:41.493009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
420
 
11.5%
지 185
 
5.1%
국 153
 
4.2%
민 153
 
4.2%
동 131
 
3.6%
신 115
 
3.1%
( 105
 
2.9%
리 104
 
2.8%
) 101
 
2.8%
점 91
 
2.5%
Other values (224) 2095
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2964
81.1%
Space Separator 421
 
11.5%
Open Punctuation 122
 
3.3%
Close Punctuation 118
 
3.2%
Uppercase Letter 24
 
0.7%
Other Punctuation 2
 
0.1%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 185
 
6.2%
국 153
 
5.2%
민 153
 
5.2%
동 131
 
4.4%
신 115
 
3.9%
리 104
 
3.5%
점 91
 
3.1%
농 85
 
2.9%
협 84
 
2.8%
부 75
 
2.5%
Other values (206) 1788
60.3%
Uppercase Letter
ValueCountFrequency (%)
E 4
16.7%
B 4
16.7%
K 4
16.7%
L 2
8.3%
S 2
8.3%
U 2
8.3%
P 2
8.3%
H 2
8.3%
N 2
8.3%
Space Separator
ValueCountFrequency (%)
420
99.8%
　 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 105
86.1%
（ 17
 
13.9%
Close Punctuation
ValueCountFrequency (%)
) 101
85.6%
） 17
 
14.4%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Other Punctuation
ValueCountFrequency (%)
? 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2964
81.1%
Common 665
 
18.2%
Latin 24
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 185
 
6.2%
국 153
 
5.2%
민 153
 
5.2%
동 131
 
4.4%
신 115
 
3.9%
리 104
 
3.5%
점 91
 
3.1%
농 85
 
2.9%
협 84
 
2.8%
부 75
 
2.5%
Other values (206) 1788
60.3%
Common
ValueCountFrequency (%)
420
63.2%
( 105
 
15.8%
) 101
 
15.2%
（ 17
 
2.6%
） 17
 
2.6%
? 2
 
0.3%
2 1
 
0.2%
1 1
 
0.2%
　 1
 
0.2%
Latin
ValueCountFrequency (%)
E 4
16.7%
B 4
16.7%
K 4
16.7%
L 2
8.3%
S 2
8.3%
U 2
8.3%
P 2
8.3%
H 2
8.3%
N 2
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2964
81.1%
ASCII 654
 
17.9%
None 35
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
420
64.2%
( 105
 
16.1%
) 101
 
15.4%
E 4
 
0.6%
B 4
 
0.6%
K 4
 
0.6%
L 2
 
0.3%
? 2
 
0.3%
S 2
 
0.3%
U 2
 
0.3%
Other values (5) 8
 
1.2%
Hangul
ValueCountFrequency (%)
지 185
 
6.2%
국 153
 
5.2%
민 153
 
5.2%
동 131
 
4.4%
신 115
 
3.9%
리 104
 
3.5%
점 91
 
3.1%
농 85
 
2.9%
협 84
 
2.8%
부 75
 
2.5%
Other values (206) 1788
60.3%
None
ValueCountFrequency (%)
（ 17
48.6%
） 17
48.6%
　 1
 
2.9%

UPDT_TS
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing409
Missing (%)100.0%
Memory size3.7 KiB

UPDT_ENO
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing409
Missing (%)100.0%
Memory size3.7 KiB

UPDT_BRCD
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing409
Missing (%)100.0%
Memory size3.7 KiB

REG_TS
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing409
Missing (%)100.0%
Memory size3.7 KiB

REG_ENO
Real number (ℝ)

SKEWED 

Distinct153
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1695.0905
Minimum1020
Maximum52549
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T01:54:41.724808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1020
5-th percentile1181.4
Q11425
median1557
Q31692
95-th percentile1917
Maximum52549
Range51529
Interquartile range (IQR)267

Descriptive statistics

Standard deviation2529.5245
Coefficient of variation (CV)1.4922652
Kurtosis403.29821
Mean1695.0905
Median Absolute Deviation (MAD)132
Skewness20.012428
Sum693292
Variance6398494.3
MonotonicityNot monotonic
2023-12-13T01:54:41.883502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1598 20
 
4.9%
1641 14
 
3.4%
1532 13
 
3.2%
1425 13
 
3.2%
1300 12
 
2.9%
1475 11
 
2.7%
1917 10
 
2.4%
1302 10
 
2.4%
1656 10
 
2.4%
1650 8
 
2.0%
Other values (143) 288
70.4%
ValueCountFrequency (%)
1020 2
0.5%
1025 1
 
0.2%
1110 1
 
0.2%
1117 1
 
0.2%
1127 1
 
0.2%
1152 1
 
0.2%
1155 1
 
0.2%
1159 3
0.7%
1160 1
 
0.2%
1163 1
 
0.2%
ValueCountFrequency (%)
52549 1
 
0.2%
2003 1
 
0.2%
2002 1
 
0.2%
2001 1
 
0.2%
1980 1
 
0.2%
1977 2
0.5%
1970 1
 
0.2%
1968 3
0.7%
1938 1
 
0.2%
1937 3
0.7%

REG_BRCD
Categorical

Distinct22
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
TAB
77 
THO
44 
QAD
37 
TAA
28 
TPA
26 
Other values (17)
197 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowTAB
2nd rowTQC
3rd rowTHO
4th rowTBB
5th rowQAD

Common Values

ValueCountFrequency (%)
TAB 77
18.8%
THO 44
10.8%
QAD 37
9.0%
TAA 28
 
6.8%
TPA 26
 
6.4%
TBA 24
 
5.9%
TAC 24
 
5.9%
THA 22
 
5.4%
THB 21
 
5.1%
TAD 20
 
4.9%
Other values (12) 86
21.0%

Length

2023-12-13T01:54:42.028422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tab 77
18.8%
tho 44
10.8%
qad 37
9.0%
taa 28
 
6.8%
tpa 26
 
6.4%
tba 24
 
5.9%
tac 24
 
5.9%
tha 22
 
5.4%
thb 21
 
5.1%
tad 20
 
4.9%
Other values (12) 86
21.0%

Sample

ACPT_PTNOGUARNT_NOMDBTR_CUST_NOBBR_CDSTLE_DVCDDDEMND_ACPT_DYDDRSN_OCCR_DYDISCHRG_DEMND_DYDISCHRG_TERM_DYDISCHRG_ORG_CDDISCHRG_ORG_NMRMT_ORG_CDRMT_CDCANCLE_COM_DYRETURN_DYDISCHRG_APPRV_DYORG_GUARNT_DYBBNAPPRV_NOTI_DYTREAT_ENOPRCSS_DYBR_NN_APPRV_RSCDHDQUAT_BATCH_ACPT_YNDISCHRG_ACPT_CDONLIN_DEMND_YNDDEMND_PLC_CDDDEMND_PLC_NMUPDT_TSUPDT_ENOUPDT_BRCDREG_TSREG_ENOREG_BRCD
020200400097RTAB201000017179584640TAB220201023<NA>20201023<NA><NA><NA>32<NA><NA>20201029<NA>2020102913852020102915N2<NA>37167기업 여신관리부<NA><NA><NA><NA>1385TAB
120200400096RTPA2016000596111686312TQC220201019<NA>20201019<NA><NA><NA>111<NA><NA>20201029<NA>2020102917472020102615N1<NA>117333농협중앙회 안동시지부지점(영업소)<NA><NA><NA><NA>1747TQC
220200400095RTHO201000001277928460THO120201013<NA>20201013<NA><NA><NA>882<NA><NA>20201013<NA>2020101319172020101315N2<NA>883117신한 인천동구청<NA><NA><NA><NA>1917THO
320200400094RTBA2017000881118648803TBB220200918<NA>20200918<NA><NA><NA>191<NA><NA>20201005<NA>2020100513042020092915N1<NA>41205국민 구포<NA><NA><NA><NA>1304TBB
420200400092RQAD2016000534110579718QAD120200922<NA>20200918<NA><NA><NA>202<NA><NA>20200922<NA>2020092214062020092215N2<NA>207667우리 파주남(지)<NA><NA><NA><NA>1406QAD
520200400091RTAA200800002369048329THA220200918<NA>20200918<NA><NA><NA>191<NA><NA>20200923<NA>2020092319702020091815N1<NA>40646국민 잠실<NA><NA><NA><NA>1970THA
620200400093RTPA201300011992576635TPA220200924<NA>20200924<NA><NA><NA>312<NA><NA>20201007<NA>2020100719132020092415N2<NA>310062대구 반월당(지)<NA><NA><NA><NA>1913TPA
720200400090RTAB2016000788112781973TAB220200918<NA>20200917<NA><NA><NA>202<NA><NA>20200924<NA>2020092413852020091815N2<NA>206244우리 여신관리부<NA><NA><NA><NA>1385TAB
820200400089RQAD200900027774544449QAD220200908<NA>20200908<NA><NA><NA>882<NA><NA>20200911<NA>2020091119772020090815N2<NA>268143신한 일산역 (지)<NA><NA><NA><NA>1977QAD
920200400088RQAD201000017578714068QAD220200902<NA>20200902<NA><NA><NA>812<NA><NA>20200903<NA>2020090319772020090215N2<NA>811066하나 여의도(지)<NA><NA><NA><NA>1977QAD
ACPT_PTNOGUARNT_NOMDBTR_CUST_NOBBR_CDSTLE_DVCDDDEMND_ACPT_DYDDRSN_OCCR_DYDISCHRG_DEMND_DYDISCHRG_TERM_DYDISCHRG_ORG_CDDISCHRG_ORG_NMRMT_ORG_CDRMT_CDCANCLE_COM_DYRETURN_DYDISCHRG_APPRV_DYORG_GUARNT_DYBBNAPPRV_NOTI_DYTREAT_ENOPRCSS_DYBR_NN_APPRV_RSCDHDQUAT_BATCH_ACPT_YNDISCHRG_ACPT_CDONLIN_DEMND_YNDDEMND_PLC_CDDDEMND_PLC_NMUPDT_TSUPDT_ENOUPDT_BRCDREG_TSREG_ENOREG_BRCD
39920120400002RQAD200900029764588826QAD220120517<NA>20120517<NA><NA><NA>42<NA><NA>20120531<NA>2012053114952012052115N2<NA>64208국민 홍릉<NA><NA><NA><NA>1495QAD
40020110400003RQAD201000041780228610QAD220111111<NA>20111110<NA><NA><NA>112<NA><NA>20111121<NA>2011112113562011111815N2<NA>110550농협 화양<NA><NA><NA><NA>1356QAD
40120120400001RTAA200800008770572059TAA220120103<NA>20120103<NA><NA><NA>202<NA><NA>20120214<NA>2012021411732012011015N2<NA>200910우리 낙성대역(지)<NA><NA><NA><NA>1173TAA
40220100400003RTHO200900001136420748THO120100614<NA>20100614<NA><NA><NA>882<NA><NA>20100616<NA>2010061613842010061415N2<NA>266093신한 산곡동(지)<NA><NA><NA><NA>1384THO
40320100400006RTPA200800000869459772TPA220101029<NA>20101029<NA><NA><NA>111<NA><NA>20101109<NA>2010110913592010110515N1<NA>117207농협중앙회 수성동지점지점(영업소)<NA><NA><NA><NA>1359TPA
40420100400002RTHO200800003969802125THO120100329<NA>20100329<NA><NA><NA>61<NA><NA>20100401<NA>2010040111522010033115N1<NA>63733국민 정왕동<NA><NA><NA><NA>1152THO
40520080400001RTPA200700001866081800TPA220080814<NA>20080814<NA><NA><NA>41<NA><NA>20080917<NA>2008091712472008082015N1<NA>46459국민　 시지<NA><NA><NA><NA>1247TPA
40620110400001RQAD200700009065008415QAD220110214<NA>20110214<NA><NA><NA><NA>1<NA><NA>20110221<NA>2011022114062011021415N2<NA>110903농협중앙회 주엽<NA><NA><NA><NA>1406QAD
40720100400005RTOA200700000964966189TOA220101005<NA>20101005<NA><NA><NA>61<NA><NA>20101012<NA>2010101213882010101215N1<NA>67920국민 진월동<NA><NA><NA><NA>1388TOA
40820100400004RTPA200900002774322616TPA220100902<NA>20100902<NA><NA><NA>41<NA><NA>20100928<NA>2010092813592010090315N1<NA>46459국민 시지<NA><NA><NA><NA>1359TPA