Overview

Dataset statistics

Number of variables23
Number of observations500
Missing cells50
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory93.4 KiB
Average record size in memory191.3 B

Variable types

Categorical10
Numeric6
Text4
Boolean3

Dataset

Description해당 파일 데이터는 신용보증기금의 보증사후관리 부실통지 시스템 정보를 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15093246/fileData.do

Alerts

기준일자 has constant value ""Constant
업무구분코드 has constant value ""Constant
취급일자 has constant value ""Constant
부실사유발생일자 has constant value ""Constant
부실기표일자 has constant value ""Constant
삭제여부 has constant value ""Constant
처리직원번호 has constant value ""Constant
단기고액부실여부 is highly imbalanced (74.0%)Imbalance
한도거래방법여부 is highly imbalanced (60.5%)Imbalance
이메일전송여부 is highly imbalanced (62.1%)Imbalance
최종수정수 is highly imbalanced (77.6%)Imbalance
주요사업장전화번호 has 48 (9.6%) missing valuesMissing
부실금액 has 41 (8.2%) zerosZeros

Reproduction

Analysis started2023-12-12 10:31:53.309524
Analysis finished2023-12-12 10:31:53.694691
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
500 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row00:00.0
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 500
100.0%

Length

2023-12-12T19:31:53.784713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:31:53.884787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

통지일련번호
Real number (ℝ)

Distinct47
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.894
Minimum1
Maximum47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T19:31:54.002439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median13
Q320
95-th percentile31
Maximum47
Range46
Interquartile range (IQR)14

Descriptive statistics

Standard deviation9.3514525
Coefficient of variation (CV)0.67305689
Kurtosis0.44341238
Mean13.894
Median Absolute Deviation (MAD)7
Skewness0.80367531
Sum6947
Variance87.449663
MonotonicityNot monotonic
2023-12-12T19:31:54.154498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
1 22
 
4.4%
2 22
 
4.4%
6 21
 
4.2%
3 21
 
4.2%
8 21
 
4.2%
7 21
 
4.2%
5 21
 
4.2%
4 21
 
4.2%
12 20
 
4.0%
11 20
 
4.0%
Other values (37) 290
58.0%
ValueCountFrequency (%)
1 22
4.4%
2 22
4.4%
3 21
4.2%
4 21
4.2%
5 21
4.2%
6 21
4.2%
7 21
4.2%
8 21
4.2%
9 20
4.0%
10 19
3.8%
ValueCountFrequency (%)
47 1
0.2%
46 1
0.2%
45 1
0.2%
44 1
0.2%
43 1
0.2%
42 1
0.2%
41 1
0.2%
40 1
0.2%
39 1
0.2%
38 1
0.2%

기업고객ID
Text

Distinct209
Distinct (%)41.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T19:31:54.419135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters5000
Distinct characters62
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)11.6%

Sample

1st row9dc2k5nGba
2nd row9dc2k5nGba
3rd row9c6OeGxqp0
4th row9c6OeGxqp0
5th row9cBX5xrCKx
ValueCountFrequency (%)
9ckkiajuhw 12
 
2.4%
9bjxussgt5 10
 
2.0%
9cnzxuye3j 10
 
2.0%
aaaaadj5xm 8
 
1.6%
9czxc7wvq0 8
 
1.6%
9cjwko776d 8
 
1.6%
9cymggc3y6 8
 
1.6%
9byeo0h9pg 8
 
1.6%
9crx3xknnf 7
 
1.4%
9ddrb3rzka 6
 
1.2%
Other values (199) 415
83.0%
2023-12-12T19:31:54.762840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 537
 
10.7%
c 421
 
8.4%
d 197
 
3.9%
a 195
 
3.9%
J 101
 
2.0%
y 100
 
2.0%
b 96
 
1.9%
G 95
 
1.9%
6 94
 
1.9%
5 91
 
1.8%
Other values (52) 3073
61.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2231
44.6%
Uppercase Letter 1589
31.8%
Decimal Number 1180
23.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 421
18.9%
d 197
 
8.8%
a 195
 
8.7%
y 100
 
4.5%
b 96
 
4.3%
x 90
 
4.0%
e 88
 
3.9%
z 80
 
3.6%
h 71
 
3.2%
u 68
 
3.0%
Other values (16) 825
37.0%
Uppercase Letter
ValueCountFrequency (%)
J 101
 
6.4%
G 95
 
6.0%
K 80
 
5.0%
W 79
 
5.0%
O 78
 
4.9%
I 68
 
4.3%
E 67
 
4.2%
X 65
 
4.1%
C 65
 
4.1%
Y 63
 
4.0%
Other values (16) 828
52.1%
Decimal Number
ValueCountFrequency (%)
9 537
45.5%
6 94
 
8.0%
5 91
 
7.7%
3 81
 
6.9%
7 76
 
6.4%
0 69
 
5.8%
2 61
 
5.2%
4 58
 
4.9%
1 57
 
4.8%
8 56
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 3820
76.4%
Common 1180
 
23.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 421
 
11.0%
d 197
 
5.2%
a 195
 
5.1%
J 101
 
2.6%
y 100
 
2.6%
b 96
 
2.5%
G 95
 
2.5%
x 90
 
2.4%
e 88
 
2.3%
K 80
 
2.1%
Other values (42) 2357
61.7%
Common
ValueCountFrequency (%)
9 537
45.5%
6 94
 
8.0%
5 91
 
7.7%
3 81
 
6.9%
7 76
 
6.4%
0 69
 
5.8%
2 61
 
5.2%
4 58
 
4.9%
1 57
 
4.8%
8 56
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 537
 
10.7%
c 421
 
8.4%
d 197
 
3.9%
a 195
 
3.9%
J 101
 
2.0%
y 100
 
2.0%
b 96
 
1.9%
G 95
 
1.9%
6 94
 
1.9%
5 91
 
1.8%
Other values (52) 3073
61.5%

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

2023-12-12T19:31:54.896615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:31:54.972327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 500
100.0%

주요사업장전화번호
Text

MISSING 

Distinct183
Distinct (%)40.5%
Missing48
Missing (%)9.6%
Memory size4.0 KiB
2023-12-12T19:31:55.156585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters10848
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)11.3%

Sample

1st rowAAEgGpUy7lC/DxDLm71Xa2fX
2nd rowAAEgGpUy7lC/DxDLm71Xa2fX
3rd rowAAGNedjyw3+EJe7gf4bNIMJ+
4th rowAAGNedjyw3+EJe7gf4bNIMJ+
5th rowAAGhWZwHEVKMr/QiA0x/fCQG
ValueCountFrequency (%)
aage1ukhfa+wl9aivekamdts 12
 
2.7%
aagvdnoqjcmqp38we8gjoto7 10
 
2.2%
aagw0yjopmpt2yddy6l8ijto 10
 
2.2%
aagpwxs1mexqaojpx30gvec 8
 
1.8%
aagwomxkudhxq/hi+05xdnw0 8
 
1.8%
aaepihcyqtp72ddv6alayg5t 8
 
1.8%
aaehfjy/ehxr52bzdswrt265 8
 
1.8%
aahdsdsxk3lyhhkq8p4hem1w 8
 
1.8%
aah/zese2vkwws2nawowdrqq 7
 
1.5%
aahtrhefwjvxlxfbmr1wahox 6
 
1.3%
Other values (173) 367
81.2%
2023-12-12T19:31:55.506136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1019
 
9.4%
H 285
 
2.6%
G 262
 
2.4%
E 259
 
2.4%
F 237
 
2.2%
d 197
 
1.8%
D 193
 
1.8%
W 190
 
1.8%
2 189
 
1.7%
Y 185
 
1.7%
Other values (54) 7832
72.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 5273
48.6%
Lowercase Letter 3887
35.8%
Decimal Number 1343
 
12.4%
Other Punctuation 184
 
1.7%
Math Symbol 161
 
1.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1019
19.3%
H 285
 
5.4%
G 262
 
5.0%
E 259
 
4.9%
F 237
 
4.5%
D 193
 
3.7%
W 190
 
3.6%
Y 185
 
3.5%
X 182
 
3.5%
Q 177
 
3.4%
Other values (16) 2284
43.3%
Lowercase Letter
ValueCountFrequency (%)
d 197
 
5.1%
w 177
 
4.6%
x 177
 
4.6%
o 175
 
4.5%
f 167
 
4.3%
i 164
 
4.2%
k 164
 
4.2%
s 163
 
4.2%
j 163
 
4.2%
p 159
 
4.1%
Other values (16) 2181
56.1%
Decimal Number
ValueCountFrequency (%)
2 189
14.1%
0 151
11.2%
8 148
11.0%
3 134
10.0%
1 133
9.9%
4 132
9.8%
9 126
9.4%
6 117
8.7%
7 107
8.0%
5 106
7.9%
Other Punctuation
ValueCountFrequency (%)
/ 184
100.0%
Math Symbol
ValueCountFrequency (%)
+ 161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9160
84.4%
Common 1688
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1019
 
11.1%
H 285
 
3.1%
G 262
 
2.9%
E 259
 
2.8%
F 237
 
2.6%
d 197
 
2.2%
D 193
 
2.1%
W 190
 
2.1%
Y 185
 
2.0%
X 182
 
2.0%
Other values (42) 6151
67.2%
Common
ValueCountFrequency (%)
2 189
11.2%
/ 184
10.9%
+ 161
9.5%
0 151
8.9%
8 148
8.8%
3 134
7.9%
1 133
7.9%
4 132
7.8%
9 126
7.5%
6 117
6.9%
Other values (2) 213
12.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10848
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 1019
 
9.4%
H 285
 
2.6%
G 262
 
2.4%
E 259
 
2.4%
F 237
 
2.2%
d 197
 
1.8%
D 193
 
1.8%
W 190
 
1.8%
2 189
 
1.7%
Y 185
 
1.7%
Other values (54) 7832
72.2%

대표자전화번호
Text

Distinct205
Distinct (%)41.2%
Missing2
Missing (%)0.4%
Memory size4.0 KiB
2023-12-12T19:31:55.758447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters11952
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)11.4%

Sample

1st rowAAHazdPo8YRT0SvPFRbNsdio
2nd rowAAHazdPo8YRT0SvPFRbNsdio
3rd rowAAFrJT3rxU/jejZOSKy2gk6T
4th rowAAFrJT3rxU/jejZOSKy2gk6T
5th rowAAGMaeTR5b/xodyWLyIOwEJC
ValueCountFrequency (%)
aahmzu8fkivk4pjsfxpx1kgk 12
 
2.4%
aaebv9j6dqo0aae11l9yrdqx 10
 
2.0%
aaelarh8chuzpk/pw/npu+no 10
 
2.0%
aahqznvped9ypw/e/wnzfuwd 8
 
1.6%
aag7nazjtxaiteishhhxugyf 8
 
1.6%
aafjf5gte+gxvkmayfohbuxp 8
 
1.6%
aafqptvfy3ut/ck9zkz2zdfy 8
 
1.6%
aah20h5ks/hkhnolyuydic+t 8
 
1.6%
aahsfhvtncum73uckdvoc5pc 7
 
1.4%
aahqvz0g7bxq9lzlktayuxd2 6
 
1.2%
Other values (195) 413
82.9%
2023-12-12T19:31:56.203231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1147
 
9.6%
H 341
 
2.9%
F 301
 
2.5%
G 282
 
2.4%
E 265
 
2.2%
T 229
 
1.9%
Y 226
 
1.9%
k 224
 
1.9%
p 210
 
1.8%
K 201
 
1.7%
Other values (54) 8526
71.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 5781
48.4%
Lowercase Letter 4318
36.1%
Decimal Number 1491
 
12.5%
Math Symbol 183
 
1.5%
Other Punctuation 179
 
1.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1147
19.8%
H 341
 
5.9%
F 301
 
5.2%
G 282
 
4.9%
E 265
 
4.6%
T 229
 
4.0%
Y 226
 
3.9%
K 201
 
3.5%
V 184
 
3.2%
D 183
 
3.2%
Other values (16) 2422
41.9%
Lowercase Letter
ValueCountFrequency (%)
k 224
 
5.2%
p 210
 
4.9%
x 199
 
4.6%
c 197
 
4.6%
v 193
 
4.5%
z 192
 
4.4%
h 185
 
4.3%
d 184
 
4.3%
f 180
 
4.2%
g 163
 
3.8%
Other values (16) 2391
55.4%
Decimal Number
ValueCountFrequency (%)
9 169
11.3%
1 168
11.3%
6 167
11.2%
2 154
10.3%
5 147
9.9%
0 146
9.8%
3 145
9.7%
4 136
9.1%
8 131
8.8%
7 128
8.6%
Math Symbol
ValueCountFrequency (%)
+ 183
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 179
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10099
84.5%
Common 1853
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1147
 
11.4%
H 341
 
3.4%
F 301
 
3.0%
G 282
 
2.8%
E 265
 
2.6%
T 229
 
2.3%
Y 226
 
2.2%
k 224
 
2.2%
p 210
 
2.1%
K 201
 
2.0%
Other values (42) 6673
66.1%
Common
ValueCountFrequency (%)
+ 183
9.9%
/ 179
9.7%
9 169
9.1%
1 168
9.1%
6 167
9.0%
2 154
8.3%
5 147
7.9%
0 146
7.9%
3 145
7.8%
4 136
7.3%
Other values (2) 259
14.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 1147
 
9.6%
H 341
 
2.9%
F 301
 
2.5%
G 282
 
2.4%
E 265
 
2.2%
T 229
 
1.9%
Y 226
 
1.9%
k 224
 
1.9%
p 210
 
1.8%
K 201
 
1.7%
Other values (54) 8526
71.3%

취급종류코드
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
410 
64 
6
 
26

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 (%)
1 410
82.0%
64
 
12.8%
6 26
 
5.2%

Length

2023-12-12T19:31:56.369003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:31:56.510539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 410
94.0%
6 26
 
6.0%

취급일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
500 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row00:00.0
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 500
100.0%

Length

2023-12-12T19:31:56.625029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:31:56.727161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

취급금액
Real number (ℝ)

Distinct78
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.124789 × 108
Minimum3000000
Maximum2.96 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T19:31:56.863009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile42375000
Q190000000
median1.8 × 108
Q33 × 108
95-th percentile1.5 × 109
Maximum2.96 × 109
Range2.957 × 109
Interquartile range (IQR)2.1 × 108

Descriptive statistics

Standard deviation3.981462 × 108
Coefficient of variation (CV)1.2741539
Kurtosis6.6792678
Mean3.124789 × 108
Median Absolute Deviation (MAD)1.1 × 108
Skewness2.4552461
Sum1.5623945 × 1011
Variance1.5852039 × 1017
MonotonicityNot monotonic
2023-12-12T19:31:57.053786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000000 50
 
10.0%
180000000 32
 
6.4%
1500000000 32
 
6.4%
90000000 29
 
5.8%
300000000 27
 
5.4%
100000000 21
 
4.2%
95000000 21
 
4.2%
270000000 21
 
4.2%
135000000 20
 
4.0%
200000000 18
 
3.6%
Other values (68) 229
45.8%
ValueCountFrequency (%)
3000000 1
 
0.2%
9500000 2
 
0.4%
12500000 2
 
0.4%
20000000 6
1.2%
25000000 1
 
0.2%
30000000 2
 
0.4%
36000000 3
 
0.6%
40000000 8
1.6%
42500000 1
 
0.2%
45000000 9
1.8%
ValueCountFrequency (%)
2960000000 1
 
0.2%
1500000000 32
6.4%
1485000000 2
 
0.4%
1000000000 9
 
1.8%
810000000 3
 
0.6%
765000000 2
 
0.4%
700000000 14
2.8%
697000000 2
 
0.4%
665000000 3
 
0.6%
630000000 6
 
1.2%

신용등급코드값
Categorical

Distinct31
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
KS9
89 
KS10
47 
KS8
45 
KS11
42 
KS12
 
25
Other values (26)
252 

Length

Max length4
Median length3
Mean length3.05
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowAS11
2nd rowAS11
3rd rowKS11
4th rowKS11
5th rowKS8

Common Values

ValueCountFrequency (%)
KS9 89
17.8%
KS10 47
 
9.4%
KS8 45
 
9.0%
KS11 42
 
8.4%
KS12 25
 
5.0%
KS6 23
 
4.6%
8 23
 
4.6%
7 23
 
4.6%
KS7 21
 
4.2%
11 16
 
3.2%
Other values (21) 146
29.2%

Length

2023-12-12T19:31:57.303859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ks9 89
17.9%
ks10 47
 
9.5%
ks8 45
 
9.1%
ks11 42
 
8.5%
ks12 25
 
5.0%
ks6 23
 
4.6%
8 23
 
4.6%
7 23
 
4.6%
ks7 21
 
4.2%
11 16
 
3.2%
Other values (20) 142
28.6%

부실사유발생일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
500 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row00:00.0
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 500
100.0%

Length

2023-12-12T19:31:57.874146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:31:57.990820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

부실기표일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
500 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row00:00.0
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 500
100.0%

Length

2023-12-12T19:31:58.141206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:31:58.261219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

부실사유코드
Real number (ℝ)

Distinct13
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.386
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T19:31:58.367713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile19
Maximum20
Range19
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.6285907
Coefficient of variation (CV)1.0553102
Kurtosis4.0785794
Mean4.386
Median Absolute Deviation (MAD)1
Skewness2.1406253
Sum2193
Variance21.423852
MonotonicityNot monotonic
2023-12-12T19:31:58.506604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 135
27.0%
2 119
23.8%
4 74
14.8%
6 66
13.2%
5 40
 
8.0%
19 15
 
3.0%
20 12
 
2.4%
13 11
 
2.2%
3 8
 
1.6%
15 7
 
1.4%
Other values (3) 13
 
2.6%
ValueCountFrequency (%)
1 135
27.0%
2 119
23.8%
3 8
 
1.6%
4 74
14.8%
5 40
 
8.0%
6 66
13.2%
7 3
 
0.6%
9 6
 
1.2%
13 11
 
2.2%
14 4
 
0.8%
ValueCountFrequency (%)
20 12
 
2.4%
19 15
 
3.0%
15 7
 
1.4%
14 4
 
0.8%
13 11
 
2.2%
9 6
 
1.2%
7 3
 
0.6%
6 66
13.2%
5 40
8.0%
4 74
14.8%

부실금액
Real number (ℝ)

ZEROS 

Distinct106
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7447767 × 108
Minimum0
Maximum1.188 × 109
Zeros41
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T19:31:58.673764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q150000000
median1.17 × 108
Q32.553125 × 108
95-th percentile5 × 108
Maximum1.188 × 109
Range1.188 × 109
Interquartile range (IQR)2.053125 × 108

Descriptive statistics

Standard deviation1.7352939 × 108
Coefficient of variation (CV)0.99456504
Kurtosis6.8905552
Mean1.7447767 × 108
Median Absolute Deviation (MAD)72000000
Skewness2.1703064
Sum8.7238837 × 1010
Variance3.0112451 × 1016
MonotonicityNot monotonic
2023-12-12T19:31:58.904760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000000 44
 
8.8%
0 41
 
8.2%
90000000 24
 
4.8%
300000000 23
 
4.6%
100000000 20
 
4.0%
95000000 18
 
3.6%
270000000 16
 
3.2%
180000000 16
 
3.2%
200000000 15
 
3.0%
135000000 14
 
2.8%
Other values (96) 269
53.8%
ValueCountFrequency (%)
0 41
8.2%
3000000 1
 
0.2%
9500000 2
 
0.4%
11730021 2
 
0.4%
20000000 6
 
1.2%
25000000 1
 
0.2%
30000000 2
 
0.4%
32000000 3
 
0.6%
32121000 2
 
0.4%
35000000 2
 
0.4%
ValueCountFrequency (%)
1188000000 2
0.4%
1000000000 2
0.4%
810000000 3
0.6%
700000000 2
0.4%
697000000 2
0.4%
581040000 2
0.4%
570000000 4
0.8%
567000000 2
0.4%
560000000 2
0.4%
513000000 2
0.4%

기업부실금액
Real number (ℝ)

Distinct133
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3215081 × 108
Minimum9500000
Maximum1.7320375 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T19:31:59.094582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9500000
5-th percentile41608338
Q11 × 108
median2.705 × 108
Q36.473123 × 108
95-th percentile1.4325 × 109
Maximum1.7320375 × 109
Range1.7225375 × 109
Interquartile range (IQR)5.473123 × 108

Descriptive statistics

Standard deviation4.2248948 × 108
Coefficient of variation (CV)0.97764361
Kurtosis0.71613879
Mean4.3215081 × 108
Median Absolute Deviation (MAD)1.98 × 108
Skewness1.2936526
Sum2.1607541 × 1011
Variance1.7849736 × 1017
MonotonicityNot monotonic
2023-12-12T19:31:59.332122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000000 32
 
6.4%
100000000 14
 
2.8%
300000000 14
 
2.8%
1487300000 12
 
2.4%
90000000 12
 
2.4%
270000000 12
 
2.4%
1432500000 10
 
2.0%
200000000 10
 
2.0%
1280040000 10
 
2.0%
180000000 9
 
1.8%
Other values (123) 365
73.0%
ValueCountFrequency (%)
9500000 2
 
0.4%
11730021 2
 
0.4%
20000000 6
1.2%
25000000 1
 
0.2%
30000000 2
 
0.4%
32121000 2
 
0.4%
35000000 2
 
0.4%
40000000 6
1.2%
40500000 2
 
0.4%
41666672 2
 
0.4%
ValueCountFrequency (%)
1732037500 3
 
0.6%
1545851500 3
 
0.6%
1487300000 12
2.4%
1432500000 10
2.0%
1410000000 8
1.6%
1280040000 10
2.0%
1188000000 2
 
0.4%
1184000000 1
 
0.2%
1171000000 6
1.2%
1060402196 2
 
0.4%

단기고액부실여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
478 
True
 
22
ValueCountFrequency (%)
False 478
95.6%
True 22
 
4.4%
2023-12-12T19:31:59.462565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

취급자직원번호
Real number (ℝ)

Distinct328
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4247.5
Minimum2451
Maximum5941
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T19:31:59.611010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2451
5-th percentile3012
Q13600.5
median4076
Q34993
95-th percentile5706.65
Maximum5941
Range3490
Interquartile range (IQR)1392.5

Descriptive statistics

Standard deviation854.70134
Coefficient of variation (CV)0.20122457
Kurtosis-0.83972087
Mean4247.5
Median Absolute Deviation (MAD)596
Skewness0.25831934
Sum2123750
Variance730514.39
MonotonicityNot monotonic
2023-12-12T19:31:59.796142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2458 6
 
1.2%
3012 5
 
1.0%
5218 5
 
1.0%
3734 5
 
1.0%
4256 5
 
1.0%
4060 5
 
1.0%
4877 4
 
0.8%
3982 4
 
0.8%
4076 4
 
0.8%
3745 4
 
0.8%
Other values (318) 453
90.6%
ValueCountFrequency (%)
2451 1
 
0.2%
2458 6
1.2%
2522 1
 
0.2%
2573 2
 
0.4%
2710 1
 
0.2%
2728 1
 
0.2%
2768 1
 
0.2%
2829 1
 
0.2%
2847 2
 
0.4%
2915 1
 
0.2%
ValueCountFrequency (%)
5941 1
0.2%
5939 1
0.2%
5937 1
0.2%
5930 1
0.2%
5917 1
0.2%
5899 1
0.2%
5894 1
0.2%
5893 1
0.2%
5892 1
0.2%
5887 1
0.2%

한도거래방법여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
461 
True
 
39
ValueCountFrequency (%)
False 461
92.2%
True 39
 
7.8%
2023-12-12T19:31:59.964352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

이메일전송여부
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Y
445 
Z
 
37
N
 
18

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Y 445
89.0%
Z 37
 
7.4%
N 18
 
3.6%

Length

2023-12-12T19:32:00.087629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:00.198292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 445
89.0%
z 37
 
7.4%
n 18
 
3.6%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
500 
ValueCountFrequency (%)
False 500
100.0%
2023-12-12T19:32:00.307609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
482 
1
 
18

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 (%)
2 482
96.4%
1 18
 
3.6%

Length

2023-12-12T19:32:00.437647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:00.580621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 482
96.4%
1 18
 
3.6%

처리시각
Text

Distinct55
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T19:32:00.851101image/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

Unique2 ?
Unique (%)0.4%

Sample

1st row34:05.0
2nd row34:05.0
3rd row34:05.0
4th row34:05.0
5th row34:05.0
ValueCountFrequency (%)
01:36.0 25
 
5.0%
01:48.0 24
 
4.8%
01:49.0 23
 
4.6%
01:42.0 21
 
4.2%
01:33.0 19
 
3.8%
01:35.0 17
 
3.4%
01:47.0 17
 
3.4%
01:41.0 16
 
3.2%
01:34.0 15
 
3.0%
01:37.0 15
 
3.0%
Other values (45) 308
61.6%
2023-12-12T19:32:01.320002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1000
28.6%
: 500
14.3%
. 500
14.3%
1 436
12.5%
3 274
 
7.8%
4 239
 
6.8%
2 180
 
5.1%
5 142
 
4.1%
6 72
 
2.1%
8 61
 
1.7%
Other values (2) 96
 
2.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1000
40.0%
1 436
17.4%
3 274
 
11.0%
4 239
 
9.6%
2 180
 
7.2%
5 142
 
5.7%
6 72
 
2.9%
8 61
 
2.4%
7 52
 
2.1%
9 44
 
1.8%
Other Punctuation
ValueCountFrequency (%)
: 500
50.0%
. 500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1000
28.6%
: 500
14.3%
. 500
14.3%
1 436
12.5%
3 274
 
7.8%
4 239
 
6.8%
2 180
 
5.1%
5 142
 
4.1%
6 72
 
2.1%
8 61
 
1.7%
Other values (2) 96
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1000
28.6%
: 500
14.3%
. 500
14.3%
1 436
12.5%
3 274
 
7.8%
4 239
 
6.8%
2 180
 
5.1%
5 142
 
4.1%
6 72
 
2.1%
8 61
 
1.7%
Other values (2) 96
 
2.7%

처리직원번호
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
BATCH 500
100.0%

Length

2023-12-12T19:32:01.508345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:01.636989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
batch 500
100.0%

Sample

기준일자통지일련번호기업고객ID업무구분코드주요사업장전화번호대표자전화번호취급종류코드취급일자취급금액신용등급코드값부실사유발생일자부실기표일자부실사유코드부실금액기업부실금액단기고액부실여부취급자직원번호한도거래방법여부이메일전송여부삭제여부최종수정수처리시각처리직원번호
000:00.0179dc2k5nGbaGAAEgGpUy7lC/DxDLm71Xa2fXAAHazdPo8YRT0SvPFRbNsdio100:00.050000000AS1100:00.000:00.045000000050000000N3626NNN134:05.0BATCH
100:00.0189dc2k5nGbaGAAEgGpUy7lC/DxDLm71Xa2fXAAHazdPo8YRT0SvPFRbNsdio100:00.050000000AS1100:00.000:00.045000000050000000N5732NNN134:05.0BATCH
200:00.0159c6OeGxqp0G<NA>AAFrJT3rxU/jejZOSKy2gk6T100:00.095000000KS1100:00.000:00.0156270001262700012N3895NNN134:05.0BATCH
300:00.0169c6OeGxqp0G<NA>AAFrJT3rxU/jejZOSKy2gk6T100:00.095000000KS1100:00.000:00.0156270001262700012N4376NNN134:05.0BATCH
400:00.0149cBX5xrCKxGAAGNedjyw3+EJe7gf4bNIMJ+AAGMaeTR5b/xodyWLyIOwEJC100:00.0405000000KS800:00.000:00.04405000000651000000N4229NNN134:05.0BATCH
500:00.0139cBX5xrCKxGAAGNedjyw3+EJe7gf4bNIMJ+AAGMaeTR5b/xodyWLyIOwEJC100:00.0172000000KS700:00.000:00.04156000000651000000N4075NNN134:04.0BATCH
600:00.0129c2pYjk5KsGAAGhWZwHEVKMr/QiA0x/fCQGAAEfsvWY+4g6ZpC3gUNKNY13600:00.090000000KS900:00.000:00.049000000090000000N4184NNN134:04.0BATCH
700:00.0119c2pYjk5KsGAAGhWZwHEVKMr/QiA0x/fCQGAAEfsvWY+4g6ZpC3gUNKNY13600:00.090000000KS900:00.000:00.049000000090000000N5706NNN134:04.0BATCH
800:00.0109dbD6JLAzQG<NA>AAFFI0Dk2gKiLi/PJtYy2VTC100:00.0100000000KS1100:00.000:00.02100000000100000000N3728NNN134:04.0BATCH
900:00.099dbD6JLAzQG<NA>AAFFI0Dk2gKiLi/PJtYy2VTC100:00.0100000000KS1100:00.000:00.02100000000100000000N4613NNN134:04.0BATCH
기준일자통지일련번호기업고객ID업무구분코드주요사업장전화번호대표자전화번호취급종류코드취급일자취급금액신용등급코드값부실사유발생일자부실기표일자부실사유코드부실금액기업부실금액단기고액부실여부취급자직원번호한도거래방법여부이메일전송여부삭제여부최종수정수처리시각처리직원번호
49000:00.025aaaaadjEIhGAAFJhyy+5rTsphZkXDmUHUbuAAGr1iF0MHEXB5JF/HQPPtPK100:00.02700000001000:00.000:00.04243000000243000000N4946NYN201:48.0BATCH
49100:00.0159byEO0h9pGGAAGwOMXKudHXq/Hi+05XDnW0AAHqznvPed9YpW/e/wnZfUWD00:00.0300000000600:00.000:00.050468500004N4376YZN248:55.0BATCH
49200:00.0149byEO0h9pGGAAGwOMXKudHXq/Hi+05XDnW0AAHqznvPed9YpW/e/wnZfUWD00:00.0300000000600:00.000:00.050468500004N3423YZN248:55.0BATCH
49300:00.079bHbuaih2oGAAG3QxZDZWvTdJNVp0DD+JbwAAGYLMU9zdHeElWrmaMXGoRg00:00.06300000001000:00.000:00.0201060402196N3330NZN248:55.0BATCH
49400:00.0129dc2n7L0gxGAAF76bZAxrP0Si8qh4VAdq86AAGktjUxBTxyAulc1Hk7uHW+100:00.05000000000:00.000:00.0204500000045000000N5582NYN202:02.0BATCH
49500:00.0119dc2n7L0gxGAAF76bZAxrP0Si8qh4VAdq86AAGktjUxBTxyAulc1Hk7uHW+100:00.05000000000:00.000:00.0204500000045000000N3723NYN202:02.0BATCH
49600:00.019c6pYPowOoGAAGsuTYGgmGsaqEE4Tj1uJqPAAGPf+wF4JrxQPuKYG1+oaQ1100:00.01260000001000:00.000:00.06126000000296000000N4229NYN202:02.0BATCH
49700:00.029c6pYPowOoGAAGsuTYGgmGsaqEE4Tj1uJqPAAGPf+wF4JrxQPuKYG1+oaQ1100:00.01700000001000:00.000:00.06170000000296000000N4229NYN202:02.0BATCH
49800:00.0189c5JpxQHF1G<NA>AAGVpmV3vUatgrPWrtZsvR+e00:00.01000000000KS700:00.000:00.015000000001000000000N4142NYN202:01.0BATCH
49900:00.0179c5JpxQHF1G<NA>AAGVpmV3vUatgrPWrtZsvR+e00:00.01000000000KS700:00.000:00.015000000001000000000N4209NYN202:01.0BATCH