Overview

Dataset statistics

Number of variables42
Number of observations500
Missing cells546
Missing cells (%)2.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory169.1 KiB
Average record size in memory346.3 B

Variable types

Categorical26
Text7
Numeric7
Unsupported1
Boolean1

Dataset

Description해당 파일 데이터는 신용보증기금의 보증접수신용보증상세에 대한 정보를 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092854/fileData.do

Alerts

업무구분코드 has constant value ""Constant
접수채널구분코드 has constant value ""Constant
피보증인변경일자 has constant value ""Constant
이행장기지연사유코드 has constant value ""Constant
기보증포함운용여부 is highly imbalanced (96.2%)Imbalance
원화외화구분코드 is highly imbalanced (97.9%)Imbalance
적용환율구분코드 is highly imbalanced (97.9%)Imbalance
지급보증상대처구분코드 is highly imbalanced (88.2%)Imbalance
담보취득조건코드 is highly imbalanced (91.7%)Imbalance
주채무과목코드 is highly imbalanced (74.0%)Imbalance
주채무인수구분코드 is highly imbalanced (89.8%)Imbalance
마켓플레이스코드 is highly imbalanced (89.3%)Imbalance
보증심사신용등급코드 is highly imbalanced (91.9%)Imbalance
정책자금소관구분코드 is highly imbalanced (89.4%)Imbalance
자금소관부처코드 is highly imbalanced (93.4%)Imbalance
중소기업지원사업명 is highly imbalanced (68.2%)Imbalance
정책자금집행기관명 is highly imbalanced (68.2%)Imbalance
삭제여부 is highly imbalanced (91.9%)Imbalance
주채무과목명 has 22 (4.4%) missing valuesMissing
주채무미확정신청기한명 has 24 (4.8%) missing valuesMissing
처리지연사유내용 has 500 (100.0%) missing valuesMissing
원장번호 has unique valuesUnique
처리지연사유내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
포함기보증금액 has 379 (75.8%) zerosZeros
순보증사용일수 has 246 (49.2%) zerosZeros
순보증사용년수 has 276 (55.2%) zerosZeros
주채무승인금액 has 181 (36.2%) zerosZeros
주채무실행금액 has 268 (53.6%) zerosZeros

Reproduction

Analysis started2023-12-12 22:58:18.022771
Analysis finished2023-12-12 22:58:18.529605
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업무구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
G
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
G 500
100.0%

Length

2023-12-13T07:58:18.581870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:18.656403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 500
100.0%

원장번호
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:58:18.839414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters6000
Distinct characters35
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

Unique500 ?
Unique (%)100.0%

Sample

1st rowTBF202110056
2nd rowTQD202103509
3rd rowTAW202105034
4th rowTQK202102777
5th rowTBG202104021
ValueCountFrequency (%)
tbf202110056 1
 
0.2%
tah202104880 1
 
0.2%
tbg202103962 1
 
0.2%
tme202106023 1
 
0.2%
tia202103802 1
 
0.2%
tis202101789 1
 
0.2%
tnd201700499 1
 
0.2%
tmk202100680 1
 
0.2%
tpl201500824 1
 
0.2%
tbh202103528 1
 
0.2%
Other values (490) 490
98.0%
2023-12-13T07:58:19.163692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1360
22.7%
2 1078
18.0%
1 681
11.3%
T 493
 
8.2%
3 240
 
4.0%
5 233
 
3.9%
9 209
 
3.5%
6 187
 
3.1%
4 186
 
3.1%
A 178
 
3.0%
Other values (25) 1155
19.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4500
75.0%
Uppercase Letter 1500
 
25.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 493
32.9%
A 178
 
11.9%
H 123
 
8.2%
P 72
 
4.8%
I 70
 
4.7%
B 66
 
4.4%
O 49
 
3.3%
Q 49
 
3.3%
J 46
 
3.1%
M 42
 
2.8%
Other values (15) 312
20.8%
Decimal Number
ValueCountFrequency (%)
0 1360
30.2%
2 1078
24.0%
1 681
15.1%
3 240
 
5.3%
5 233
 
5.2%
9 209
 
4.6%
6 187
 
4.2%
4 186
 
4.1%
8 172
 
3.8%
7 154
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4500
75.0%
Latin 1500
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 493
32.9%
A 178
 
11.9%
H 123
 
8.2%
P 72
 
4.8%
I 70
 
4.7%
B 66
 
4.4%
O 49
 
3.3%
Q 49
 
3.3%
J 46
 
3.1%
M 42
 
2.8%
Other values (15) 312
20.8%
Common
ValueCountFrequency (%)
0 1360
30.2%
2 1078
24.0%
1 681
15.1%
3 240
 
5.3%
5 233
 
5.2%
9 209
 
4.6%
6 187
 
4.2%
4 186
 
4.1%
8 172
 
3.8%
7 154
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1360
22.7%
2 1078
18.0%
1 681
11.3%
T 493
 
8.2%
3 240
 
4.0%
5 233
 
3.9%
9 209
 
3.5%
6 187
 
3.1%
4 186
 
3.1%
A 178
 
3.0%
Other values (25) 1155
19.2%

기보증포함운용여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
498 
Y
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
498
99.6%
Y 2
 
0.4%

Length

2023-12-13T07:58:19.301791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:19.632989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 2
100.0%

포함기보증금액
Real number (ℝ)

ZEROS 

Distinct92
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52222785
Minimum0
Maximum1.5383203 × 109
Zeros379
Zeros (%)75.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:58:19.739589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.856 × 108
Maximum1.5383203 × 109
Range1.5383203 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5872681 × 108
Coefficient of variation (CV)3.0394168
Kurtosis34.771155
Mean52222785
Median Absolute Deviation (MAD)0
Skewness5.2548456
Sum2.6111392 × 1010
Variance2.51942 × 1016
MonotonicityNot monotonic
2023-12-13T07:58:19.875489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 379
75.8%
100000000 10
 
2.0%
180000000 7
 
1.4%
270000000 4
 
0.8%
300000000 3
 
0.6%
297000000 3
 
0.6%
285000000 3
 
0.6%
90000000 2
 
0.4%
117000000 2
 
0.4%
229500000 2
 
0.4%
Other values (82) 85
 
17.0%
ValueCountFrequency (%)
0 379
75.8%
8500000 1
 
0.2%
9072000 1
 
0.2%
9600000 1
 
0.2%
14400000 1
 
0.2%
16200000 1
 
0.2%
17000000 1
 
0.2%
18700000 1
 
0.2%
19000000 1
 
0.2%
21600000 1
 
0.2%
ValueCountFrequency (%)
1538320320 1
0.2%
1350000000 1
0.2%
1100000000 1
0.2%
1080000000 1
0.2%
1000000000 1
0.2%
722500000 1
0.2%
688000000 1
0.2%
680000000 1
0.2%
640000000 1
0.2%
555000000 1
0.2%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
347 
1
152 
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
2 347
69.4%
1 152
30.4%
1
 
0.2%

Length

2023-12-13T07:58:20.024853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:20.120209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 347
69.5%
1 152
30.5%
Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
21
233 
229 
12
 
23
11
 
15

Length

Max length2
Median length2
Mean length1.542
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row12
3rd row
4th row11
5th row

Common Values

ValueCountFrequency (%)
21 233
46.6%
229
45.8%
12 23
 
4.6%
11 15
 
3.0%

Length

2023-12-13T07:58:20.219243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:20.312842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
21 233
86.0%
12 23
 
8.5%
11 15
 
5.5%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
395 
00:00.0
105 

Length

Max length26
Median length26
Mean length22.01
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row0001-01-01 00:00:00.000000
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 395
79.0%
00:00.0 105
 
21.0%

Length

2023-12-13T07:58:20.410326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:20.502636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 395
44.1%
00:00:00.000000 395
44.1%
00:00.0 105
 
11.7%

순보증사용일수
Real number (ℝ)

ZEROS 

Distinct224
Distinct (%)44.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1451.68
Minimum0
Maximum10141
Zeros246
Zeros (%)49.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:58:20.595991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median12.5
Q32861
95-th percentile5638.1
Maximum10141
Range10141
Interquartile range (IQR)2861

Descriptive statistics

Standard deviation2064.0519
Coefficient of variation (CV)1.4218367
Kurtosis1.6537881
Mean1451.68
Median Absolute Deviation (MAD)12.5
Skewness1.4798573
Sum725840
Variance4260310.3
MonotonicityNot monotonic
2023-12-13T07:58:20.726445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 246
49.2%
2222 4
 
0.8%
2612 3
 
0.6%
794 3
 
0.6%
3252 2
 
0.4%
3152 2
 
0.4%
4795 2
 
0.4%
3491 2
 
0.4%
354 2
 
0.4%
5 2
 
0.4%
Other values (214) 232
46.4%
ValueCountFrequency (%)
0 246
49.2%
2 1
 
0.2%
5 2
 
0.4%
8 1
 
0.2%
17 1
 
0.2%
19 1
 
0.2%
45 1
 
0.2%
88 1
 
0.2%
132 2
 
0.4%
133 1
 
0.2%
ValueCountFrequency (%)
10141 1
0.2%
9345 1
0.2%
8692 1
0.2%
8572 1
0.2%
8238 1
0.2%
8173 1
0.2%
8038 1
0.2%
7704 1
0.2%
7658 1
0.2%
7183 1
0.2%

순보증사용년수
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.694
Minimum0
Maximum27
Zeros276
Zeros (%)55.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:58:20.889449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile15.05
Maximum27
Range27
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.4585672
Coefficient of variation (CV)1.4776847
Kurtosis1.9783881
Mean3.694
Median Absolute Deviation (MAD)0
Skewness1.5659227
Sum1847
Variance29.795956
MonotonicityNot monotonic
2023-12-13T07:58:21.009285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 276
55.2%
7 28
 
5.6%
9 23
 
4.6%
2 18
 
3.6%
3 18
 
3.6%
8 17
 
3.4%
4 17
 
3.4%
1 14
 
2.8%
11 13
 
2.6%
6 10
 
2.0%
Other values (16) 66
 
13.2%
ValueCountFrequency (%)
0 276
55.2%
1 14
 
2.8%
2 18
 
3.6%
3 18
 
3.6%
4 17
 
3.4%
5 8
 
1.6%
6 10
 
2.0%
7 28
 
5.6%
8 17
 
3.4%
9 23
 
4.6%
ValueCountFrequency (%)
27 1
 
0.2%
25 1
 
0.2%
23 2
 
0.4%
22 3
 
0.6%
21 1
 
0.2%
20 1
 
0.2%
19 2
 
0.4%
18 3
 
0.6%
17 8
1.6%
16 3
 
0.6%

원화외화구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
499 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
1 499
99.8%
2 1
 
0.2%

Length

2023-12-13T07:58:21.112914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:21.193777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 499
99.8%
2 1
 
0.2%

적용환율구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
499 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
499
99.8%
1 1
 
0.2%

Length

2023-12-13T07:58:21.277794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:21.360297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1
100.0%

지급보증상대처구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
492 
1
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
492
98.4%
1 8
 
1.6%

Length

2023-12-13T07:58:21.445047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:21.540575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8
100.0%

담보취득조건코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
488 
2
 
9
4
 
1
1
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)0.6%

Sample

1st row4
2nd row2
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
488
97.6%
2 9
 
1.8%
4 1
 
0.2%
1 1
 
0.2%
3 1
 
0.2%

Length

2023-12-13T07:58:21.635923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:21.715172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 9
75.0%
4 1
 
8.3%
1 1
 
8.3%
3 1
 
8.3%

접수채널구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2023-12-13T07:58:21.802124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:21.870989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

주채무과목코드
Categorical

IMBALANCE 

Distinct17
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
428 
 
19
9
 
12
24
 
11
23
 
6
Other values (12)
 
24

Length

Max length2
Median length1
Mean length1.076
Min length1

Unique

Unique7 ?
Unique (%)1.4%

Sample

1st row9
2nd row9
3rd row1
4th row1
5th row68

Common Values

ValueCountFrequency (%)
1 428
85.6%
19
 
3.8%
9 12
 
2.4%
24 11
 
2.2%
23 6
 
1.2%
68 5
 
1.0%
10 5
 
1.0%
5 3
 
0.6%
D3 2
 
0.4%
21 2
 
0.4%
Other values (7) 7
 
1.4%

Length

2023-12-13T07:58:21.946163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 428
89.0%
9 12
 
2.5%
24 11
 
2.3%
23 6
 
1.2%
68 5
 
1.0%
10 5
 
1.0%
5 3
 
0.6%
d3 2
 
0.4%
21 2
 
0.4%
26 1
 
0.2%
Other values (6) 6
 
1.2%

주채무과목명
Text

MISSING 

Distinct87
Distinct (%)18.2%
Missing22
Missing (%)4.4%
Memory size4.0 KiB
2023-12-13T07:58:22.106489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length30
Mean length9.9246862
Min length1

Characters and Unicode

Total characters4744
Distinct characters142
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)11.5%

Sample

1st row<기시>일반자금대출(일시상환)
2nd row기업시설중장기일반대출
3rd row기업일반운전자금대출
4th row기업일반자금대출
5th row
ValueCountFrequency (%)
중소기업자금대출 104
20.3%
기업일반자금대출 73
14.2%
일반자금대출 44
 
8.6%
기업일반운전자금대출 38
 
7.4%
기업운전일반자금대출 26
 
5.1%
대출 22
 
4.3%
소상공인 20
 
3.9%
기운>일반자금대출(일시상환 20
 
3.9%
중소기업자금회전대출 12
 
2.3%
기운>일반자금대출(분할상환 11
 
2.1%
Other values (79) 143
27.9%
2023-12-13T07:58:22.399741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
441
 
9.3%
436
 
9.2%
415
 
8.7%
411
 
8.7%
365
 
7.7%
326
 
6.9%
299
 
6.3%
283
 
6.0%
222
 
4.7%
161
 
3.4%
Other values (132) 1385
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4116
86.8%
Space Separator 223
 
4.7%
Math Symbol 102
 
2.2%
Open Punctuation 93
 
2.0%
Close Punctuation 89
 
1.9%
Uppercase Letter 61
 
1.3%
Decimal Number 31
 
0.7%
Dash Punctuation 16
 
0.3%
Other Punctuation 10
 
0.2%
Connector Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
441
10.7%
436
10.6%
415
10.1%
411
10.0%
365
8.9%
326
 
7.9%
299
 
7.3%
283
 
6.9%
161
 
3.9%
153
 
3.7%
Other values (95) 826
20.1%
Uppercase Letter
ValueCountFrequency (%)
B 13
21.3%
U 7
11.5%
C 5
 
8.2%
E 5
 
8.2%
X 4
 
6.6%
T 4
 
6.6%
3
 
4.9%
3
 
4.9%
3
 
4.9%
3
 
4.9%
Other values (7) 11
18.0%
Decimal Number
ValueCountFrequency (%)
2 13
41.9%
1 12
38.7%
0 4
 
12.9%
1
 
3.2%
1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
/ 4
40.0%
* 3
30.0%
2
20.0%
1
 
10.0%
Space Separator
ValueCountFrequency (%)
222
99.6%
  1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 86
92.5%
7
 
7.5%
Close Punctuation
ValueCountFrequency (%)
) 83
93.3%
6
 
6.7%
Math Symbol
ValueCountFrequency (%)
< 51
50.0%
> 51
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
75.0%
4
 
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4116
86.8%
Common 567
 
12.0%
Latin 61
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
441
10.7%
436
10.6%
415
10.1%
411
10.0%
365
8.9%
326
 
7.9%
299
 
7.3%
283
 
6.9%
161
 
3.9%
153
 
3.7%
Other values (95) 826
20.1%
Common
ValueCountFrequency (%)
222
39.2%
( 86
 
15.2%
) 83
 
14.6%
< 51
 
9.0%
> 51
 
9.0%
2 13
 
2.3%
- 12
 
2.1%
1 12
 
2.1%
7
 
1.2%
6
 
1.1%
Other values (10) 24
 
4.2%
Latin
ValueCountFrequency (%)
B 13
21.3%
U 7
11.5%
C 5
 
8.2%
E 5
 
8.2%
X 4
 
6.6%
T 4
 
6.6%
3
 
4.9%
3
 
4.9%
3
 
4.9%
3
 
4.9%
Other values (7) 11
18.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4116
86.8%
ASCII 590
 
12.4%
None 38
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
441
10.7%
436
10.6%
415
10.1%
411
10.0%
365
8.9%
326
 
7.9%
299
 
7.3%
283
 
6.9%
161
 
3.9%
153
 
3.7%
Other values (95) 826
20.1%
ASCII
ValueCountFrequency (%)
222
37.6%
( 86
 
14.6%
) 83
 
14.1%
< 51
 
8.6%
> 51
 
8.6%
2 13
 
2.2%
B 13
 
2.2%
- 12
 
2.0%
1 12
 
2.0%
U 7
 
1.2%
Other values (12) 40
 
6.8%
None
ValueCountFrequency (%)
7
18.4%
6
15.8%
4
10.5%
3
7.9%
3
7.9%
3
7.9%
3
7.9%
2
 
5.3%
1
 
2.6%
1
 
2.6%
Other values (5) 5
13.2%
Distinct53
Distinct (%)11.1%
Missing24
Missing (%)4.8%
Memory size4.0 KiB
2023-12-13T07:58:22.573205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length5
Mean length6.1491597
Min length1

Characters and Unicode

Total characters2927
Distinct characters40
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)7.1%

Sample

1st row발급후3년
2nd row발급후3년
3rd row발급후 5년
4th row발급후5년
5th row발급후 5년
ValueCountFrequency (%)
발급후1년 214
30.0%
발급후 111
15.5%
5년 95
13.3%
1년 89
12.5%
보증서 46
 
6.4%
발급일로부터 46
 
6.4%
취급후 16
 
2.2%
발급후3년 15
 
2.1%
취급후1년 8
 
1.1%
1년 7
 
1.0%
Other values (37) 67
 
9.4%
2023-12-13T07:58:22.850768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
467
16.0%
445
15.2%
411
14.0%
395
13.5%
1 331
11.3%
266
9.1%
5 104
 
3.6%
62
 
2.1%
55
 
1.9%
55
 
1.9%
Other values (30) 336
11.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2155
73.6%
Decimal Number 504
 
17.2%
Space Separator 268
 
9.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
467
21.7%
445
20.6%
411
19.1%
395
18.3%
62
 
2.9%
55
 
2.6%
55
 
2.6%
55
 
2.6%
54
 
2.5%
54
 
2.5%
Other values (16) 102
 
4.7%
Decimal Number
ValueCountFrequency (%)
1 331
65.7%
5 104
 
20.6%
3 19
 
3.8%
2 17
 
3.4%
14
 
2.8%
0 10
 
2.0%
3
 
0.6%
8 2
 
0.4%
1
 
0.2%
1
 
0.2%
Other values (2) 2
 
0.4%
Space Separator
ValueCountFrequency (%)
266
99.3%
  2
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2155
73.6%
Common 772
 
26.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
467
21.7%
445
20.6%
411
19.1%
395
18.3%
62
 
2.9%
55
 
2.6%
55
 
2.6%
55
 
2.6%
54
 
2.5%
54
 
2.5%
Other values (16) 102
 
4.7%
Common
ValueCountFrequency (%)
1 331
42.9%
266
34.5%
5 104
 
13.5%
3 19
 
2.5%
2 17
 
2.2%
14
 
1.8%
0 10
 
1.3%
3
 
0.4%
  2
 
0.3%
8 2
 
0.3%
Other values (4) 4
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2155
73.6%
ASCII 751
 
25.7%
None 21
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
467
21.7%
445
20.6%
411
19.1%
395
18.3%
62
 
2.9%
55
 
2.6%
55
 
2.6%
55
 
2.6%
54
 
2.5%
54
 
2.5%
Other values (16) 102
 
4.7%
ASCII
ValueCountFrequency (%)
1 331
44.1%
266
35.4%
5 104
 
13.8%
3 19
 
2.5%
2 17
 
2.3%
0 10
 
1.3%
8 2
 
0.3%
4 1
 
0.1%
9 1
 
0.1%
None
ValueCountFrequency (%)
14
66.7%
3
 
14.3%
  2
 
9.5%
1
 
4.8%
1
 
4.8%

주채무신청금액
Real number (ℝ)

Distinct114
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6716747 × 108
Minimum0
Maximum4.5 × 109
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:58:22.977566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15000000
Q150000000
median1.5 × 108
Q33 × 108
95-th percentile8.11 × 108
Maximum4.5 × 109
Range4.5 × 109
Interquartile range (IQR)2.5 × 108

Descriptive statistics

Standard deviation4.3810437 × 108
Coefficient of variation (CV)1.6398118
Kurtosis36.331026
Mean2.6716747 × 108
Median Absolute Deviation (MAD)1.3 × 108
Skewness5.2198909
Sum1.3358374 × 1011
Variance1.9193544 × 1017
MonotonicityNot monotonic
2023-12-13T07:58:23.099295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000000 67
 
13.4%
300000000 63
 
12.6%
100000000 62
 
12.4%
200000000 35
 
7.0%
10000000 20
 
4.0%
330000000 20
 
4.0%
50000000 19
 
3.8%
150000000 18
 
3.6%
500000000 15
 
3.0%
250000000 7
 
1.4%
Other values (104) 174
34.8%
ValueCountFrequency (%)
0 1
 
0.2%
9000000 1
 
0.2%
10000000 20
 
4.0%
11000000 1
 
0.2%
13000000 1
 
0.2%
15000000 3
 
0.6%
17000000 1
 
0.2%
18000000 1
 
0.2%
20000000 67
13.4%
22000000 1
 
0.2%
ValueCountFrequency (%)
4500000000 1
0.2%
4000000000 1
0.2%
3000000000 2
0.4%
2500000000 2
0.4%
2000000000 1
0.2%
1765837200 1
0.2%
1680000000 1
0.2%
1650000000 1
0.2%
1550000000 1
0.2%
1520000000 1
0.2%

주채무승인금액
Real number (ℝ)

ZEROS 

Distinct93
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9940347 × 108
Minimum0
Maximum4.5 × 109
Zeros181
Zeros (%)36.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:58:23.219957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1 × 108
Q32.85875 × 108
95-th percentile7 × 108
Maximum4.5 × 109
Range4.5 × 109
Interquartile range (IQR)2.85875 × 108

Descriptive statistics

Standard deviation3.9675534 × 108
Coefficient of variation (CV)1.9897113
Kurtosis42.232705
Mean1.9940347 × 108
Median Absolute Deviation (MAD)1 × 108
Skewness5.5293983
Sum9.9701737 × 1010
Variance1.574148 × 1017
MonotonicityNot monotonic
2023-12-13T07:58:23.341239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 181
36.2%
100000000 45
 
9.0%
300000000 44
 
8.8%
200000000 28
 
5.6%
50000000 19
 
3.8%
150000000 16
 
3.2%
330000000 13
 
2.6%
500000000 10
 
2.0%
400000000 6
 
1.2%
250000000 5
 
1.0%
Other values (83) 133
26.6%
ValueCountFrequency (%)
0 181
36.2%
9000000 1
 
0.2%
10000000 1
 
0.2%
11000000 1
 
0.2%
13000000 1
 
0.2%
17000000 1
 
0.2%
18000000 1
 
0.2%
20000000 1
 
0.2%
26000000 1
 
0.2%
27000000 3
 
0.6%
ValueCountFrequency (%)
4500000000 1
0.2%
3000000000 2
0.4%
2500000000 2
0.4%
1765837200 1
0.2%
1680000000 1
0.2%
1650000000 1
0.2%
1520000000 1
0.2%
1500000000 2
0.4%
1375000000 1
0.2%
1350000000 1
0.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
268 
00:00.0
232 

Length

Max length26
Median length26
Mean length17.184
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row0001-01-01 00:00:00.000000
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 268
53.6%
00:00.0 232
46.4%

Length

2023-12-13T07:58:23.448779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:23.533062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 268
34.9%
00:00:00.000000 268
34.9%
00:00.0 232
30.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
268 
00:00.0
232 

Length

Max length26
Median length26
Mean length17.184
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row0001-01-01 00:00:00.000000
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 268
53.6%
00:00.0 232
46.4%

Length

2023-12-13T07:58:23.619478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:23.700259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 268
34.9%
00:00:00.000000 268
34.9%
00:00.0 232
30.2%

주채무실행금액
Real number (ℝ)

ZEROS 

Distinct72
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0859483 × 108
Minimum0
Maximum3 × 109
Zeros268
Zeros (%)53.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:58:23.792514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.3 × 108
95-th percentile4.072 × 108
Maximum3 × 109
Range3 × 109
Interquartile range (IQR)1.3 × 108

Descriptive statistics

Standard deviation2.4226664 × 108
Coefficient of variation (CV)2.2309223
Kurtosis53.994548
Mean1.0859483 × 108
Median Absolute Deviation (MAD)0
Skewness6.0190741
Sum5.4297416 × 1010
Variance5.8693123 × 1016
MonotonicityNot monotonic
2023-12-13T07:58:23.905999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 268
53.6%
300000000 29
 
5.8%
100000000 26
 
5.2%
200000000 25
 
5.0%
50000000 17
 
3.4%
20000000 16
 
3.2%
150000000 9
 
1.8%
330000000 8
 
1.6%
10000000 7
 
1.4%
110000000 5
 
1.0%
Other values (62) 90
 
18.0%
ValueCountFrequency (%)
0 268
53.6%
10000000 7
 
1.4%
11000000 1
 
0.2%
20000000 16
 
3.2%
26000000 1
 
0.2%
27000000 2
 
0.4%
30000000 3
 
0.6%
35000000 1
 
0.2%
38000000 2
 
0.4%
40000000 2
 
0.4%
ValueCountFrequency (%)
3000000000 1
0.2%
1996016100 1
0.2%
1680000000 1
0.2%
1500000000 1
0.2%
1375000000 1
0.2%
850000000 1
0.2%
830000000 1
0.2%
760000000 1
0.2%
750000000 1
0.2%
700000000 2
0.4%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
268 
00:00.0
232 

Length

Max length26
Median length26
Mean length17.184
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row0001-01-01 00:00:00.000000
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 268
53.6%
00:00.0 232
46.4%

Length

2023-12-13T07:58:24.020215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:24.100358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 268
34.9%
00:00:00.000000 268
34.9%
00:00.0 232
30.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
260 
00:00.0
240 

Length

Max length26
Median length26
Mean length16.88
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row0001-01-01 00:00:00.000000
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 260
52.0%
00:00.0 240
48.0%

Length

2023-12-13T07:58:24.186792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:24.270121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 260
34.2%
00:00:00.000000 260
34.2%
00:00.0 240
31.6%

주채무인수구분코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
490 
2
 
5
1
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
490
98.0%
2 5
 
1.0%
1 5
 
1.0%

Length

2023-12-13T07:58:24.352888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:24.429864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5
50.0%
1 5
50.0%

피보증인변경일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
500 

Length

Max length26
Median length26
Mean length26
Min length26

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row0001-01-01 00:00:00.000000
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 500
100.0%

Length

2023-12-13T07:58:24.510892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:24.582039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 500
50.0%
00:00:00.000000 500
50.0%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
N
249 
212 
Y
39 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd row
4th rowN
5th row

Common Values

ValueCountFrequency (%)
N 249
49.8%
212
42.4%
Y 39
 
7.8%

Length

2023-12-13T07:58:24.657774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:24.738286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 249
86.5%
y 39
 
13.5%

마켓플레이스코드
Categorical

IMBALANCE 

Distinct9
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
480 
ANYSTL
 
9
EMTNET
 
4
BIZCRE
 
2
HMOBIS
 
1
Other values (4)
 
4

Length

Max length6
Median length1
Mean length1.2
Min length1

Unique

Unique5 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
480
96.0%
ANYSTL 9
 
1.8%
EMTNET 4
 
0.8%
BIZCRE 2
 
0.4%
HMOBIS 1
 
0.2%
KISCOC 1
 
0.2%
SPLINK 1
 
0.2%
SKCORP 1
 
0.2%
SOIL88 1
 
0.2%

Length

2023-12-13T07:58:24.834959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:24.944345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
anystl 9
45.0%
emtnet 4
20.0%
bizcre 2
 
10.0%
hmobis 1
 
5.0%
kiscoc 1
 
5.0%
splink 1
 
5.0%
skcorp 1
 
5.0%
soil88 1
 
5.0%

이행장기지연사유코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
500
100.0%

Length

2023-12-13T07:58:25.054286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:25.142377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

보증심사신용등급코드
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
488 
8
 
6
6
 
3
9
 
1
13
 
1

Length

Max length2
Median length1
Mean length1.002
Min length1

Unique

Unique3 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
488
97.6%
8 6
 
1.2%
6 3
 
0.6%
9 1
 
0.2%
13 1
 
0.2%
5 1
 
0.2%

Length

2023-12-13T07:58:25.226820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:25.312698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8 6
50.0%
6 3
25.0%
9 1
 
8.3%
13 1
 
8.3%
5 1
 
8.3%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
N
363 
125 
Y
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd row
4th rowN
5th row

Common Values

ValueCountFrequency (%)
N 363
72.6%
125
 
25.0%
Y 12
 
2.4%

Length

2023-12-13T07:58:25.404979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:25.754005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 363
96.8%
y 12
 
3.2%

정책자금소관구분코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
489 
2
 
9
99
 
2

Length

Max length2
Median length1
Mean length1.004
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
489
97.8%
2 9
 
1.8%
99 2
 
0.4%

Length

2023-12-13T07:58:25.848529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:25.926279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 9
81.8%
99 2
 
18.2%

자금소관부처코드
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
489 
84
 
2
99
 
2
87
 
1
56
 
1
Other values (5)
 
5

Length

Max length2
Median length1
Mean length1.022
Min length1

Unique

Unique7 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
489
97.8%
84 2
 
0.4%
99 2
 
0.4%
87 1
 
0.2%
56 1
 
0.2%
54 1
 
0.2%
83 1
 
0.2%
86 1
 
0.2%
88 1
 
0.2%
53 1
 
0.2%

Length

2023-12-13T07:58:26.015195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:58:26.116508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
84 2
18.2%
99 2
18.2%
87 1
9.1%
56 1
9.1%
54 1
9.1%
83 1
9.1%
86 1
9.1%
88 1
9.1%
53 1
9.1%

중소기업지원사업명
Categorical

IMBALANCE 

Distinct13
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
296 
<NA>
193 
2021년도 경상북도 중소기업육성자금
 
1
2021대전광역시 중소기업 경영안정자금
 
1
긴급경영안정자금(기술혁신형)
 
1
Other values (8)
 
8

Length

Max length29
Median length1
Mean length2.516
Min length1

Unique

Unique11 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
296
59.2%
<NA> 193
38.6%
2021년도 경상북도 중소기업육성자금 1
 
0.2%
2021대전광역시 중소기업 경영안정자금 1
 
0.2%
긴급경영안정자금(기술혁신형) 1
 
0.2%
중소기업육성자금 지원 1
 
0.2%
2021년도 특별경영안정자금 1
 
0.2%
수산발전운전자금대출 1
 
0.2%
2021년 제22차 충청남도 중소기업육성자금 지원기업 1
 
0.2%
2021년 경영안정자금 1
 
0.2%
Other values (3) 3
 
0.6%

Length

2023-12-13T07:58:26.227608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 193
86.5%
중소기업육성자금 4
 
1.8%
경영안정자금 4
 
1.8%
2021년 4
 
1.8%
중소기업 2
 
0.9%
지원 2
 
0.9%
2021년도 2
 
0.9%
충청남도 1
 
0.4%
경상남도 1
 
0.4%
하반기 1
 
0.4%
Other values (9) 9
 
4.0%

정책자금집행기관명
Categorical

IMBALANCE 

Distinct13
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
296 
<NA>
193 
칠곡군
 
1
(재)대전일자리경제진흥원
 
1
충청남도
 
1
Other values (8)
 
8

Length

Max length13
Median length1
Mean length2.312
Min length1

Unique

Unique11 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
296
59.2%
<NA> 193
38.6%
칠곡군 1
 
0.2%
(재)대전일자리경제진흥원 1
 
0.2%
충청남도 1
 
0.2%
인천광역시 남동구청 1
 
0.2%
충청북도기업진흥원 1
 
0.2%
수협은행 1
 
0.2%
충청남도경제진흥원장 1
 
0.2%
전라북도경제통상진흥원 1
 
0.2%
Other values (3) 3
 
0.6%

Length

2023-12-13T07:58:26.340203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 193
93.7%
칠곡군 1
 
0.5%
재)대전일자리경제진흥원 1
 
0.5%
충청남도 1
 
0.5%
인천광역시 1
 
0.5%
남동구청 1
 
0.5%
충청북도기업진흥원 1
 
0.5%
수협은행 1
 
0.5%
충청남도경제진흥원장 1
 
0.5%
전라북도경제통상진흥원 1
 
0.5%
Other values (4) 4
 
1.9%

처리지연사유내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing500
Missing (%)100.0%
Memory size4.5 KiB

삭제여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
495 
True
 
5
ValueCountFrequency (%)
False 495
99.0%
True 5
 
1.0%
2023-12-13T07:58:26.428137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Real number (ℝ)

Distinct41
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.888
Minimum1
Maximum55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:58:26.516904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median6
Q312
95-th percentile26.05
Maximum55
Range54
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.9276459
Coefficient of variation (CV)1.0044606
Kurtosis3.4392971
Mean8.888
Median Absolute Deviation (MAD)5
Skewness1.667643
Sum4444
Variance79.702862
MonotonicityNot monotonic
2023-12-13T07:58:26.635620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1 103
20.6%
2 63
12.6%
9 34
 
6.8%
10 33
 
6.6%
3 27
 
5.4%
5 25
 
5.0%
4 19
 
3.8%
8 17
 
3.4%
11 17
 
3.4%
6 16
 
3.2%
Other values (31) 146
29.2%
ValueCountFrequency (%)
1 103
20.6%
2 63
12.6%
3 27
 
5.4%
4 19
 
3.8%
5 25
 
5.0%
6 16
 
3.2%
7 11
 
2.2%
8 17
 
3.4%
9 34
 
6.8%
10 33
 
6.6%
ValueCountFrequency (%)
55 1
0.2%
53 1
0.2%
45 1
0.2%
43 1
0.2%
38 2
0.4%
37 1
0.2%
36 1
0.2%
34 1
0.2%
33 2
0.4%
32 1
0.2%
Distinct495
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:58:26.911149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3500
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique491 ?
Unique (%)98.2%

Sample

1st row32:46.1
2nd row32:45.6
3rd row32:42.9
4th row32:42.8
5th row32:38.3
ValueCountFrequency (%)
16:06.4 3
 
0.6%
41:23.0 2
 
0.4%
31:32.8 2
 
0.4%
24:11.9 2
 
0.4%
53:58.5 1
 
0.2%
51:35.7 1
 
0.2%
32:46.1 1
 
0.2%
54:18.9 1
 
0.2%
54:12.0 1
 
0.2%
54:03.4 1
 
0.2%
Other values (485) 485
97.0%
2023-12-13T07:58:27.291440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
4 341
9.7%
1 338
9.7%
2 338
9.7%
3 313
8.9%
0 289
8.3%
5 269
7.7%
9 168
 
4.8%
8 157
 
4.5%
Other values (2) 287
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2500
71.4%
Other Punctuation 1000
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 341
13.6%
1 338
13.5%
2 338
13.5%
3 313
12.5%
0 289
11.6%
5 269
10.8%
9 168
6.7%
8 157
6.3%
6 148
5.9%
7 139
5.6%
Other Punctuation
ValueCountFrequency (%)
: 500
50.0%
. 500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
4 341
9.7%
1 338
9.7%
2 338
9.7%
3 313
8.9%
0 289
8.3%
5 269
7.7%
9 168
 
4.8%
8 157
 
4.5%
Other values (2) 287
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
4 341
9.7%
1 338
9.7%
2 338
9.7%
3 313
8.9%
0 289
8.3%
5 269
7.7%
9 168
 
4.8%
8 157
 
4.5%
Other values (2) 287
8.2%
Distinct288
Distinct (%)57.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:58:27.648353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.444
Min length4

Characters and Unicode

Total characters2222
Distinct characters11
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

Unique209 ?
Unique (%)41.8%

Sample

1st row4882
2nd row3489
3rd row99002
4th row5690
5th row4216
ValueCountFrequency (%)
99006 23
 
4.6%
99016 21
 
4.2%
99001 21
 
4.2%
99002 19
 
3.8%
99023 18
 
3.6%
99007 14
 
2.8%
88889 6
 
1.2%
4493 5
 
1.0%
6116 4
 
0.8%
5463 4
 
0.8%
Other values (278) 365
73.0%
2023-12-13T07:58:28.123988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 447
20.1%
0 334
15.0%
6 256
11.5%
4 201
9.0%
5 179
8.1%
1 162
 
7.3%
3 151
 
6.8%
7 148
 
6.7%
2 135
 
6.1%
8 116
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2129
95.8%
Uppercase Letter 93
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 447
21.0%
0 334
15.7%
6 256
12.0%
4 201
9.4%
5 179
8.4%
1 162
 
7.6%
3 151
 
7.1%
7 148
 
7.0%
2 135
 
6.3%
8 116
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
C 93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2129
95.8%
Latin 93
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
9 447
21.0%
0 334
15.7%
6 256
12.0%
4 201
9.4%
5 179
8.4%
1 162
 
7.6%
3 151
 
7.1%
7 148
 
7.0%
2 135
 
6.3%
8 116
 
5.4%
Latin
ValueCountFrequency (%)
C 93
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2222
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 447
20.1%
0 334
15.0%
6 256
11.5%
4 201
9.0%
5 179
8.1%
1 162
 
7.3%
3 151
 
6.8%
7 148
 
6.7%
2 135
 
6.1%
8 116
 
5.2%
Distinct499
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:58:28.433725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3500
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique498 ?
Unique (%)99.6%

Sample

1st row41:18.2
2nd row20:34.5
3rd row32:42.9
4th row15:02.3
5th row32:38.3
ValueCountFrequency (%)
24:50.0 2
 
0.4%
24:19.5 1
 
0.2%
57:53.1 1
 
0.2%
49:45.0 1
 
0.2%
28:48.6 1
 
0.2%
48:16.5 1
 
0.2%
33:53.6 1
 
0.2%
52:57.8 1
 
0.2%
40:33.0 1
 
0.2%
53:51.9 1
 
0.2%
Other values (489) 489
97.8%
2023-12-13T07:58:28.891603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
2 334
9.5%
4 322
9.2%
1 311
8.9%
0 310
8.9%
3 308
8.8%
5 300
8.6%
9 166
 
4.7%
8 154
 
4.4%
Other values (2) 295
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2500
71.4%
Other Punctuation 1000
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 334
13.4%
4 322
12.9%
1 311
12.4%
0 310
12.4%
3 308
12.3%
5 300
12.0%
9 166
6.6%
8 154
6.2%
7 152
6.1%
6 143
5.7%
Other Punctuation
ValueCountFrequency (%)
: 500
50.0%
. 500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
2 334
9.5%
4 322
9.2%
1 311
8.9%
0 310
8.9%
3 308
8.8%
5 300
8.6%
9 166
 
4.7%
8 154
 
4.4%
Other values (2) 295
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
2 334
9.5%
4 322
9.2%
1 311
8.9%
0 310
8.9%
3 308
8.8%
5 300
8.6%
9 166
 
4.7%
8 154
 
4.4%
Other values (2) 295
8.4%
Distinct331
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:58:29.282984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.27
Min length4

Characters and Unicode

Total characters2135
Distinct characters13
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

Unique253 ?
Unique (%)50.6%

Sample

1st row4882
2nd row4532
3rd row99002
4th row3893
5th row4216
ValueCountFrequency (%)
99006 20
 
4.0%
99023 17
 
3.4%
99002 15
 
3.0%
99001 12
 
2.4%
99007 11
 
2.2%
99016 11
 
2.2%
4109 4
 
0.8%
3723 4
 
0.8%
9c743 4
 
0.8%
4830 3
 
0.6%
Other values (321) 399
79.8%
2023-12-13T07:58:29.772514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 350
16.4%
0 277
13.0%
3 275
12.9%
4 247
11.6%
5 217
10.2%
6 174
8.1%
2 167
7.8%
1 137
 
6.4%
7 130
 
6.1%
8 128
 
6.0%
Other values (3) 33
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2102
98.5%
Uppercase Letter 33
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 350
16.7%
0 277
13.2%
3 275
13.1%
4 247
11.8%
5 217
10.3%
6 174
8.3%
2 167
7.9%
1 137
 
6.5%
7 130
 
6.2%
8 128
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
C 21
63.6%
B 8
 
24.2%
A 4
 
12.1%

Most occurring scripts

ValueCountFrequency (%)
Common 2102
98.5%
Latin 33
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
9 350
16.7%
0 277
13.2%
3 275
13.1%
4 247
11.8%
5 217
10.3%
6 174
8.3%
2 167
7.9%
1 137
 
6.5%
7 130
 
6.2%
8 128
 
6.1%
Latin
ValueCountFrequency (%)
C 21
63.6%
B 8
 
24.2%
A 4
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 350
16.4%
0 277
13.0%
3 275
12.9%
4 247
11.6%
5 217
10.2%
6 174
8.1%
2 167
7.8%
1 137
 
6.4%
7 130
 
6.1%
8 128
 
6.0%
Other values (3) 33
 
1.5%

Sample

업무구분코드원장번호기보증포함운용여부포함기보증금액보증서형태코드전자보증발급상태코드보증서발급일자순보증사용일수순보증사용년수원화외화구분코드적용환율구분코드지급보증상대처구분코드담보취득조건코드접수채널구분코드주채무과목코드주채무과목명주채무미확정신청기한명주채무신청금액주채무승인금액주채무실행입력일자주채무실행일자주채무실행금액주채무약정기간시작일자주채무약정기간종료일자주채무인수구분코드피보증인변경일자자동기한연장요청여부마켓플레이스코드이행장기지연사유코드보증심사신용등급코드정책자금여부정책자금소관구분코드자금소관부처코드중소기업지원사업명정책자금집행기관명처리지연사유내용삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
0GTBF20211005602110001-01-01 00:00:00.0000008801419<기시>일반자금대출(일시상환)발급후3년120000000012000000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000NN<NA>N532:46.1488241:18.24882
1GTQD20210350902120001-01-01 00:00:00.0000004501219기업시설중장기일반대출발급후3년152000000015200000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000YN<NA>N732:45.6348920:34.54532
2GTAW202105034010001-01-01 00:00:00.00000000111기업일반운전자금대출발급후 5년2000000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000<NA><NA><NA>N132:42.99900232:42.999002
3GTQK20210277702110001-01-01 00:00:00.00000020685111기업일반자금대출발급후5년6000000006000000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000NN<NA>N732:42.8569015:02.33893
4GTBG202104021010001-01-01 00:00:00.0000008038221168<NA>15000000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000<NA>N132:38.3421632:38.34216
5GTHD202102068010001-01-01 00:00:00.00000000111기업일반운전자금대출발급후 5년1000000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000<NA><NA><NA>N132:31.69900232:31.699002
6GTHJ202105947010001-01-01 00:00:00.00000000111소상공인 대출발급후 5년20000000000:00.000:00.02000000000:00.000:00.00001-01-01 00:00:00.000000<NA><NA><NA>N232:25.29900657:39.299006
7GTOA201800221022100:00.000111기업운전일반자금대출(통장대출)승인후 1년10000000010000000000:00.000:00.010000000000:00.000:00.00001-01-01 00:00:00.000000NN<NA><NA><NA>N2032:21.3449204:38.62773
8GTHI202105790020001-01-01 00:00:00.00000000111일반자금대출발급후 1년8000000008000000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000N<NA>N432:19.8514224:16.95142
9GTBH202103487010001-01-01 00:00:00.00000000111소상공인 대출발급후 5년20000000000:00.000:00.02000000000:00.000:00.00001-01-01 00:00:00.000000<NA><NA><NA>N232:15.09900600:03.999006
업무구분코드원장번호기보증포함운용여부포함기보증금액보증서형태코드전자보증발급상태코드보증서발급일자순보증사용일수순보증사용년수원화외화구분코드적용환율구분코드지급보증상대처구분코드담보취득조건코드접수채널구분코드주채무과목코드주채무과목명주채무미확정신청기한명주채무신청금액주채무승인금액주채무실행입력일자주채무실행일자주채무실행금액주채무약정기간시작일자주채무약정기간종료일자주채무인수구분코드피보증인변경일자자동기한연장요청여부마켓플레이스코드이행장기지연사유코드보증심사신용등급코드정책자금여부정책자금소관구분코드자금소관부처코드중소기업지원사업명정책자금집행기관명처리지연사유내용삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
490GTAH202104812020001-01-01 00:00:00.00000029097111중소기업자금회전대출보증서 발급일로부터 1년2700000002700000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000NN<NA>N1233:19.7604756:09.63772
491GTHJ2020031622700000002210001-01-01 00:00:00.00000015184111중소기업자금대출발급후1년50000000050000000000:00.000:00.050000000000:00.000:00.00001-01-01 00:00:00.000000NN<NA>N1333:12.79C66105:21.33564
492GTPD20170088410000000022100:00.072611111우리CUBE론(신규)-운전(일시)발급후1년12500000012500000000:00.000:00.012500000000:00.000:00.00001-01-01 00:00:00.000000NN<NA><NA><NA>N1332:53.2608719:04.15410
493GTMF202102004960000002110001-01-01 00:00:00.0000005439141124<기운>B2B구매자금대출(총액중소)발급후1년1200000001200000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000NSOIL88N<NA>N532:49.1598719:39.25987
494GTQL2020013193496000002210001-01-01 00:00:00.000000718319111기업일반운전자금발급후 1년43700000043700000000:00.000:00.043700000000:00.000:00.00001-01-01 00:00:00.000000NN<NA>N832:06.1614528:26.79C043
495GTAP20210390702120001-01-01 00:00:00.00000000111<기운>일반자금대출(일시상환)발급후1년50000000500000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000YN<NA>N531:33.6404348:04.94043
496GTMB202103700010001-01-01 00:00:00.00000000111<기운>일반자금대출(분할상환) 소상발급후 5년2000000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000<NA><NA><NA>N131:28.49901631:28.499016
497GTAD202103823020001-01-01 00:00:00.00000000111중소기업자금대출발급후1년10000000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000N<NA>N231:08.5540524:59.85405
498GTME202106006010001-01-01 00:00:00.00000000111소상공인 대출발급후 5년20000000000:00.000:00.02000000000:00.000:00.00001-01-01 00:00:00.000000<NA><NA><NA>N231:02.79900647:48.599006
499GTAD20180092522800000022100:00.023596111기업일반자금대출발급후1년28500000028500000000:00.000:00.028500000000:00.000:00.00001-01-01 00:00:00.000000NN<NA><NA><NA>N1430:56.9540017:44.15585