Overview

Dataset statistics

Number of variables53
Number of observations500
Missing cells516
Missing cells (%)1.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory215.5 KiB
Average record size in memory441.3 B

Variable types

Categorical30
Text10
DateTime1
Numeric11
Boolean1

Dataset

Description해당 파일 데이터는 신용보증기금의 보증접수원장마스터에 대한 정보를 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092852/fileData.do

Alerts

업무구분코드 has constant value ""Constant
상담등록일자 has constant value ""Constant
신청기한월수 has constant value ""Constant
접수일자 is highly imbalanced (77.6%)Imbalance
개별한도거래구분코드 is highly imbalanced (89.4%)Imbalance
거래방법코드 is highly imbalanced (75.2%)Imbalance
일반특별구분코드 is highly imbalanced (89.1%)Imbalance
취급종류코드 is highly imbalanced (78.7%)Imbalance
취급방법코드 is highly imbalanced (50.1%)Imbalance
자금용도코드 is highly imbalanced (71.9%)Imbalance
승인구분코드 is highly imbalanced (65.9%)Imbalance
한도방법건별발급기한 is highly imbalanced (91.9%)Imbalance
한도방법건별취급기한 is highly imbalanced (91.9%)Imbalance
삭제여부 is highly imbalanced (97.9%)Imbalance
미확정신청기한명 has 19 (3.8%) missing valuesMissing
불승인감액승인사유단순내용 has 497 (99.4%) missing valuesMissing
원장ID has unique valuesUnique
신청기한년수 has 153 (30.6%) zerosZeros
보증비율 has 16 (3.2%) zerosZeros
승인금액 has 80 (16.0%) zerosZeros
승인잔액 has 81 (16.2%) zerosZeros
보증금액 has 140 (28.0%) zerosZeros
보증잔액 has 208 (41.6%) zerosZeros

Reproduction

Analysis started2023-12-12 22:31:19.579614
Analysis finished2023-12-12 22:31:20.314340
Duration0.73 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

2023-12-13T07:31:20.365218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:20.436366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 500
100.0%

원장ID
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:31:20.632924image/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

Unique500 ?
Unique (%)100.0%

Sample

1st row9dbs7SzXY8
2nd row9dnMVAfEv0
3rd row9dnAVQQabK
4th row9dnSGQZ1Pp
5th row9cEklu6yXZ
ValueCountFrequency (%)
9dbs7szxy8 1
 
0.2%
9dnlr6ql9t 1
 
0.2%
9dghtagn7f 1
 
0.2%
9dnmyk1h0k 1
 
0.2%
9dnow2xft2 1
 
0.2%
9cwhjmkozq 1
 
0.2%
9dnswdhdnf 1
 
0.2%
9dftkhlpng 1
 
0.2%
9ceqzppcwj 1
 
0.2%
9ceqsactvf 1
 
0.2%
Other values (490) 490
98.0%
2023-12-13T07:31:20.952655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 542
 
10.8%
d 378
 
7.6%
n 275
 
5.5%
c 213
 
4.3%
S 143
 
2.9%
e 118
 
2.4%
a 117
 
2.3%
5 89
 
1.8%
L 87
 
1.7%
Y 80
 
1.6%
Other values (52) 2958
59.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2236
44.7%
Uppercase Letter 1693
33.9%
Decimal Number 1071
21.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 378
16.9%
n 275
 
12.3%
c 213
 
9.5%
e 118
 
5.3%
a 117
 
5.2%
b 75
 
3.4%
m 65
 
2.9%
y 63
 
2.8%
u 63
 
2.8%
f 60
 
2.7%
Other values (16) 809
36.2%
Uppercase Letter
ValueCountFrequency (%)
S 143
 
8.4%
L 87
 
5.1%
Y 80
 
4.7%
W 80
 
4.7%
O 79
 
4.7%
E 79
 
4.7%
Z 78
 
4.6%
M 78
 
4.6%
H 77
 
4.5%
J 69
 
4.1%
Other values (16) 843
49.8%
Decimal Number
ValueCountFrequency (%)
9 542
50.6%
5 89
 
8.3%
1 73
 
6.8%
7 69
 
6.4%
0 59
 
5.5%
4 51
 
4.8%
6 48
 
4.5%
2 48
 
4.5%
8 47
 
4.4%
3 45
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 3929
78.6%
Common 1071
 
21.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 378
 
9.6%
n 275
 
7.0%
c 213
 
5.4%
S 143
 
3.6%
e 118
 
3.0%
a 117
 
3.0%
L 87
 
2.2%
Y 80
 
2.0%
W 80
 
2.0%
O 79
 
2.0%
Other values (42) 2359
60.0%
Common
ValueCountFrequency (%)
9 542
50.6%
5 89
 
8.3%
1 73
 
6.8%
7 69
 
6.4%
0 59
 
5.5%
4 51
 
4.8%
6 48
 
4.5%
2 48
 
4.5%
8 47
 
4.4%
3 45
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 542
 
10.8%
d 378
 
7.6%
n 275
 
5.5%
c 213
 
4.3%
S 143
 
2.9%
e 118
 
2.4%
a 117
 
2.3%
5 89
 
1.8%
L 87
 
1.7%
Y 80
 
1.6%
Other values (52) 2958
59.2%
Distinct393
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:31:21.199591image/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

Unique346 ?
Unique (%)69.2%

Sample

1st row9a6qgM9dgY
2nd row9dicnKm0zj
3rd row9b6FkYxlLn
4th row9ccr1r83PJ
5th row9bGQRbVsAP
ValueCountFrequency (%)
aaaaaapt0c 42
 
8.4%
9bzzbgzeur 9
 
1.8%
9c85mayhln 4
 
0.8%
9bujudiniz 4
 
0.8%
9bo2p43wh6 4
 
0.8%
9bkenw0x4i 3
 
0.6%
9bt3cojl0l 3
 
0.6%
9b1gcy2x7t 3
 
0.6%
9bk7afk4fy 3
 
0.6%
9c5ubfuhfr 3
 
0.6%
Other values (383) 422
84.4%
2023-12-13T07:31:21.575768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 566
 
11.3%
9 465
 
9.3%
d 238
 
4.8%
c 182
 
3.6%
b 180
 
3.6%
n 147
 
2.9%
0 95
 
1.9%
T 95
 
1.9%
C 93
 
1.9%
p 87
 
1.7%
Other values (52) 2852
57.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2445
48.9%
Uppercase Letter 1542
30.8%
Decimal Number 1013
20.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 566
23.1%
d 238
 
9.7%
c 182
 
7.4%
b 180
 
7.4%
n 147
 
6.0%
p 87
 
3.6%
m 64
 
2.6%
k 62
 
2.5%
z 62
 
2.5%
g 60
 
2.5%
Other values (16) 797
32.6%
Uppercase Letter
ValueCountFrequency (%)
T 95
 
6.2%
C 93
 
6.0%
S 72
 
4.7%
B 69
 
4.5%
Y 67
 
4.3%
R 66
 
4.3%
G 65
 
4.2%
J 65
 
4.2%
D 62
 
4.0%
M 61
 
4.0%
Other values (16) 827
53.6%
Decimal Number
ValueCountFrequency (%)
9 465
45.9%
0 95
 
9.4%
5 82
 
8.1%
3 64
 
6.3%
6 63
 
6.2%
2 62
 
6.1%
4 56
 
5.5%
7 49
 
4.8%
1 45
 
4.4%
8 32
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 3987
79.7%
Common 1013
 
20.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 566
 
14.2%
d 238
 
6.0%
c 182
 
4.6%
b 180
 
4.5%
n 147
 
3.7%
T 95
 
2.4%
C 93
 
2.3%
p 87
 
2.2%
S 72
 
1.8%
B 69
 
1.7%
Other values (42) 2258
56.6%
Common
ValueCountFrequency (%)
9 465
45.9%
0 95
 
9.4%
5 82
 
8.1%
3 64
 
6.3%
6 63
 
6.2%
2 62
 
6.1%
4 56
 
5.5%
7 49
 
4.8%
1 45
 
4.4%
8 32
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 566
 
11.3%
9 465
 
9.3%
d 238
 
4.8%
c 182
 
3.6%
b 180
 
3.6%
n 147
 
2.9%
0 95
 
1.9%
T 95
 
1.9%
C 93
 
1.9%
p 87
 
1.7%
Other values (52) 2852
57.0%

상담등록일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-13 00:00:00
Maximum2023-12-13 00:00:00
2023-12-13T07:31:21.675768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:31:21.748947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

접수일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
482 
0001-01-01 00:00:00.000000
 
18

Length

Max length26
Median length7
Mean length7.684
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 (%)
00:00.0 482
96.4%
0001-01-01 00:00:00.000000 18
 
3.6%

Length

2023-12-13T07:31:21.851305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:21.944091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 482
93.1%
0001-01-01 18
 
3.5%
00:00:00.000000 18
 
3.5%

원장진행상태코드
Real number (ℝ)

Distinct9
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.348
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:31:22.007167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median6
Q36
95-th percentile10
Maximum13
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.4663865
Coefficient of variation (CV)0.46117922
Kurtosis2.0432895
Mean5.348
Median Absolute Deviation (MAD)0
Skewness0.34625779
Sum2674
Variance6.0830621
MonotonicityNot monotonic
2023-12-13T07:31:22.092838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
6 359
71.8%
1 56
 
11.2%
2 50
 
10.0%
13 18
 
3.6%
10 9
 
1.8%
5 3
 
0.6%
7 2
 
0.4%
4 2
 
0.4%
3 1
 
0.2%
ValueCountFrequency (%)
1 56
 
11.2%
2 50
 
10.0%
3 1
 
0.2%
4 2
 
0.4%
5 3
 
0.6%
6 359
71.8%
7 2
 
0.4%
10 9
 
1.8%
13 18
 
3.6%
ValueCountFrequency (%)
13 18
 
3.6%
10 9
 
1.8%
7 2
 
0.4%
6 359
71.8%
5 3
 
0.6%
4 2
 
0.4%
3 1
 
0.2%
2 50
 
10.0%
1 56
 
11.2%
Distinct16
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.196
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:31:22.178041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q113
median19
Q320
95-th percentile22
Maximum27
Range26
Interquartile range (IQR)7

Descriptive statistics

Standard deviation7.1713626
Coefficient of variation (CV)0.47192436
Kurtosis-0.46514144
Mean15.196
Median Absolute Deviation (MAD)2
Skewness-0.85276924
Sum7598
Variance51.428441
MonotonicityNot monotonic
2023-12-13T07:31:22.261235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
19 123
24.6%
20 87
17.4%
14 61
12.2%
21 58
11.6%
2 50
10.0%
13 30
 
6.0%
1 26
 
5.2%
6 21
 
4.2%
27 18
 
3.6%
10 9
 
1.8%
Other values (6) 17
 
3.4%
ValueCountFrequency (%)
1 26
5.2%
2 50
10.0%
3 1
 
0.2%
4 2
 
0.4%
5 3
 
0.6%
6 21
 
4.2%
7 2
 
0.4%
10 9
 
1.8%
13 30
6.0%
14 61
12.2%
ValueCountFrequency (%)
27 18
 
3.6%
22 8
 
1.6%
21 58
11.6%
20 87
17.4%
19 123
24.6%
15 1
 
0.2%
14 61
12.2%
13 30
 
6.0%
10 9
 
1.8%
7 2
 
0.4%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
382 
2
118 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 382
76.4%
2 118
 
23.6%

Length

2023-12-13T07:31:22.598739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:22.675947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 382
76.4%
2 118
 
23.6%

접수금액
Real number (ℝ)

Distinct172
Distinct (%)34.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1492768 × 108
Minimum0
Maximum5.4 × 109
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:31:22.769130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9500000
Q119750000
median1.15875 × 108
Q32.97 × 108
95-th percentile1.425663 × 109
Maximum5.4 × 109
Range5.4 × 109
Interquartile range (IQR)2.7725 × 108

Descriptive statistics

Standard deviation6.2180333 × 108
Coefficient of variation (CV)1.9744321
Kurtosis24.748729
Mean3.1492768 × 108
Median Absolute Deviation (MAD)96875000
Skewness4.4848936
Sum1.5746384 × 1011
Variance3.8663938 × 1017
MonotonicityNot monotonic
2023-12-13T07:31:22.904289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19000000 86
 
17.2%
9500000 27
 
5.4%
285000000 22
 
4.4%
50000000 22
 
4.4%
100000000 15
 
3.0%
190000000 14
 
2.8%
90000000 13
 
2.6%
95000000 13
 
2.6%
297000000 12
 
2.4%
180000000 12
 
2.4%
Other values (162) 264
52.8%
ValueCountFrequency (%)
0 1
 
0.2%
8800000 1
 
0.2%
9500000 27
 
5.4%
11050000 1
 
0.2%
14250000 4
 
0.8%
15300000 2
 
0.4%
17000000 1
 
0.2%
17850000 1
 
0.2%
18700000 1
 
0.2%
19000000 86
17.2%
ValueCountFrequency (%)
5400000000 1
0.2%
5000000000 1
0.2%
4500000000 1
0.2%
4000000000 1
0.2%
3000000000 2
0.4%
2960000000 1
0.2%
2850000000 1
0.2%
2800000000 1
0.2%
2700000000 1
0.2%
2500000000 1
0.2%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
342 
153 
2
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 342
68.4%
153
30.6%
2 5
 
1.0%

Length

2023-12-13T07:31:23.017257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:23.095005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 342
98.6%
2 5
 
1.4%

신청기한년수
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.238
Minimum0
Maximum12
Zeros153
Zeros (%)30.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:31:23.175100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile5
Maximum12
Range12
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.6561527
Coefficient of variation (CV)1.3377647
Kurtosis9.2067214
Mean1.238
Median Absolute Deviation (MAD)0
Skewness2.7236114
Sum619
Variance2.7428417
MonotonicityNot monotonic
2023-12-13T07:31:23.264957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 265
53.0%
0 153
30.6%
5 35
 
7.0%
3 23
 
4.6%
2 15
 
3.0%
8 6
 
1.2%
10 2
 
0.4%
12 1
 
0.2%
ValueCountFrequency (%)
0 153
30.6%
1 265
53.0%
2 15
 
3.0%
3 23
 
4.6%
5 35
 
7.0%
8 6
 
1.2%
10 2
 
0.4%
12 1
 
0.2%
ValueCountFrequency (%)
12 1
 
0.2%
10 2
 
0.4%
8 6
 
1.2%
5 35
 
7.0%
3 23
 
4.6%
2 15
 
3.0%
1 265
53.0%
0 153
30.6%

신청기한월수
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-13T07:31:23.367746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:23.454895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%
Distinct53
Distinct (%)11.0%
Missing19
Missing (%)3.8%
Memory size4.0 KiB
2023-12-13T07:31:23.616012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length5
Mean length6.014553
Min length2

Characters and Unicode

Total characters2893
Distinct characters47
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)6.2%

Sample

1st row발급후5년
2nd row발급후 5년
3rd row발급후1년
4th row발급후1년
5th row발급후1년
ValueCountFrequency (%)
발급후1년 171
23.6%
발급후 137
18.9%
5년 127
17.5%
1년 70
9.7%
발급일로부터 34
 
4.7%
보증서 33
 
4.6%
발급후5년 25
 
3.4%
취급후 19
 
2.6%
발급후2년 15
 
2.1%
발급후3년 15
 
2.1%
Other values (36) 79
10.9%
2023-12-13T07:31:23.926350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
476
16.5%
444
15.3%
415
14.3%
409
14.1%
1 276
9.5%
272
9.4%
5 153
 
5.3%
44
 
1.5%
39
 
1.3%
39
 
1.3%
Other values (37) 326
11.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2094
72.4%
Decimal Number 523
 
18.1%
Space Separator 274
 
9.5%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
476
22.7%
444
21.2%
415
19.8%
409
19.5%
44
 
2.1%
39
 
1.9%
39
 
1.9%
39
 
1.9%
38
 
1.8%
38
 
1.8%
Other values (21) 113
 
5.4%
Decimal Number
ValueCountFrequency (%)
1 276
52.8%
5 153
29.3%
2 29
 
5.5%
3 26
 
5.0%
0 14
 
2.7%
10
 
1.9%
8 7
 
1.3%
9 2
 
0.4%
4 2
 
0.4%
6 2
 
0.4%
Other values (2) 2
 
0.4%
Space Separator
ValueCountFrequency (%)
272
99.3%
  2
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2094
72.4%
Common 799
 
27.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
476
22.7%
444
21.2%
415
19.8%
409
19.5%
44
 
2.1%
39
 
1.9%
39
 
1.9%
39
 
1.9%
38
 
1.8%
38
 
1.8%
Other values (21) 113
 
5.4%
Common
ValueCountFrequency (%)
1 276
34.5%
272
34.0%
5 153
19.1%
2 29
 
3.6%
3 26
 
3.3%
0 14
 
1.8%
10
 
1.3%
8 7
 
0.9%
  2
 
0.3%
9 2
 
0.3%
Other values (6) 8
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2094
72.4%
ASCII 786
 
27.2%
None 13
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
476
22.7%
444
21.2%
415
19.8%
409
19.5%
44
 
2.1%
39
 
1.9%
39
 
1.9%
39
 
1.9%
38
 
1.8%
38
 
1.8%
Other values (21) 113
 
5.4%
ASCII
ValueCountFrequency (%)
1 276
35.1%
272
34.6%
5 153
19.5%
2 29
 
3.7%
3 26
 
3.3%
0 14
 
1.8%
8 7
 
0.9%
9 2
 
0.3%
4 2
 
0.3%
6 2
 
0.3%
Other values (3) 3
 
0.4%
None
ValueCountFrequency (%)
10
76.9%
  2
 
15.4%
1
 
7.7%

개별한도거래구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
10
493 
20
 
7

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10
2nd row10
3rd row10
4th row10
5th row10

Common Values

ValueCountFrequency (%)
10 493
98.6%
20 7
 
1.4%

Length

2023-12-13T07:31:24.037267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:24.113204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 493
98.6%
20 7
 
1.4%

거래방법코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
461 
2
 
25
4
 
7
21
 
7

Length

Max length2
Median length1
Mean length1.014
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 461
92.2%
2 25
 
5.0%
4 7
 
1.4%
21 7
 
1.4%

Length

2023-12-13T07:31:24.221556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:24.344216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 461
92.2%
2 25
 
5.0%
4 7
 
1.4%
21 7
 
1.4%

건별구분코드
Real number (ℝ)

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.786
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:31:24.479328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum22
Range21
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.5379295
Coefficient of variation (CV)1.4210132
Kurtosis45.400598
Mean1.786
Median Absolute Deviation (MAD)0
Skewness6.3828083
Sum893
Variance6.4410862
MonotonicityNot monotonic
2023-12-13T07:31:24.635336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 381
76.2%
3 98
 
19.6%
7 7
 
1.4%
21 6
 
1.2%
2 4
 
0.8%
4 2
 
0.4%
5 1
 
0.2%
22 1
 
0.2%
ValueCountFrequency (%)
1 381
76.2%
2 4
 
0.8%
3 98
 
19.6%
4 2
 
0.4%
5 1
 
0.2%
7 7
 
1.4%
21 6
 
1.2%
22 1
 
0.2%
ValueCountFrequency (%)
22 1
 
0.2%
21 6
 
1.2%
7 7
 
1.4%
5 1
 
0.2%
4 2
 
0.4%
3 98
 
19.6%
2 4
 
0.8%
1 381
76.2%

일반특별구분코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
488 
2
 
11
7
 
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 (%)
1 488
97.6%
2 11
 
2.2%
7 1
 
0.2%

Length

2023-12-13T07:31:24.849687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:25.021390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 488
97.6%
2 11
 
2.2%
7 1
 
0.2%

취급종류코드
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
462 
6
 
12
42
 
11
 
7
10
 
6

Length

Max length2
Median length1
Mean length1.034
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 462
92.4%
6 12
 
2.4%
42 11
 
2.2%
7
 
1.4%
10 6
 
1.2%
2 2
 
0.4%

Length

2023-12-13T07:31:25.200840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:25.391007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 462
93.7%
6 12
 
2.4%
42 11
 
2.2%
10 6
 
1.2%
2 2
 
0.4%

취급방법코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
413 
2
70 
 
17

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 (%)
1 413
82.6%
2 70
 
14.0%
17
 
3.4%

Length

2023-12-13T07:31:25.583972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:25.766887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 413
85.5%
2 70
 
14.5%
Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
242 
2
141 
3
92 
 
17
99
 
8

Length

Max length2
Median length1
Mean length1.016
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row3
5th row2

Common Values

ValueCountFrequency (%)
1 242
48.4%
2 141
28.2%
3 92
 
18.4%
17
 
3.4%
99 8
 
1.6%

Length

2023-12-13T07:31:25.970979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:26.137804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 242
50.1%
2 141
29.2%
3 92
 
19.0%
99 8
 
1.7%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
252 
2
248 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 252
50.4%
2 248
49.6%

Length

2023-12-13T07:31:26.370651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:26.597015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 252
50.4%
2 248
49.6%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
289 
195 
2
 
16

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 289
57.8%
195
39.0%
2 16
 
3.2%

Length

2023-12-13T07:31:26.750745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:26.876637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 289
94.8%
2 16
 
5.2%

자금용도코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
463 
2
 
26
 
11

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 (%)
1 463
92.6%
2 26
 
5.2%
11
 
2.2%

Length

2023-12-13T07:31:26.979760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:27.084062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 463
94.7%
2 26
 
5.3%

보증비율
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.75
Minimum0
Maximum100
Zeros16
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:31:27.206926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile80
Q185
median95
Q395
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)10

Descriptive statistics

Standard deviation17.183657
Coefficient of variation (CV)0.19361867
Kurtosis20.116057
Mean88.75
Median Absolute Deviation (MAD)5
Skewness-4.3959519
Sum44375
Variance295.27806
MonotonicityNot monotonic
2023-12-13T07:31:27.314772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
95 196
39.2%
90 104
20.8%
85 71
 
14.2%
100 67
 
13.4%
80 43
 
8.6%
0 16
 
3.2%
75 2
 
0.4%
70 1
 
0.2%
ValueCountFrequency (%)
0 16
 
3.2%
70 1
 
0.2%
75 2
 
0.4%
80 43
 
8.6%
85 71
 
14.2%
90 104
20.8%
95 196
39.2%
100 67
 
13.4%
ValueCountFrequency (%)
100 67
 
13.4%
95 196
39.2%
90 104
20.8%
85 71
 
14.2%
80 43
 
8.6%
75 2
 
0.4%
70 1
 
0.2%
0 16
 
3.2%
Distinct23
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
183 
8
89 
30
56 
90
52 
45
25 
Other values (18)
95 

Length

Max length2
Median length1
Mean length1.406
Min length1

Unique

Unique4 ?
Unique (%)0.8%

Sample

1st row45
2nd row
3rd row
4th row8
5th row30

Common Values

ValueCountFrequency (%)
183
36.6%
8 89
17.8%
30 56
 
11.2%
90 52
 
10.4%
45 25
 
5.0%
11 21
 
4.2%
3 20
 
4.0%
91 10
 
2.0%
63 8
 
1.6%
50 6
 
1.2%
Other values (13) 30
 
6.0%

Length

2023-12-13T07:31:27.452017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
8 89
28.1%
30 56
17.7%
90 52
16.4%
45 25
 
7.9%
11 21
 
6.6%
3 20
 
6.3%
91 10
 
3.2%
63 8
 
2.5%
50 6
 
1.9%
31 6
 
1.9%
Other values (12) 24
 
7.6%
Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
175 
11
164 
7
142 
5
 
11
28
 
5
Other values (2)
 
3

Length

Max length2
Median length1
Mean length1.344
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
175
35.0%
11 164
32.8%
7 142
28.4%
5 11
 
2.2%
28 5
 
1.0%
19 2
 
0.4%
36 1
 
0.2%

Length

2023-12-13T07:31:27.598711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:27.740915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 164
50.5%
7 142
43.7%
5 11
 
3.4%
28 5
 
1.5%
19 2
 
0.6%
36 1
 
0.3%

승인일자
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
422 
0001-01-01 00:00:00.000000
78 

Length

Max length26
Median length7
Mean length9.964
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row0001-01-01 00:00:00.000000
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 422
84.4%
0001-01-01 00:00:00.000000 78
 
15.6%

Length

2023-12-13T07:31:27.872367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:27.974443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 422
73.0%
0001-01-01 78
 
13.5%
00:00:00.000000 78
 
13.5%

승인구분코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
419 
78 
2
 
2
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
1 419
83.8%
78
 
15.6%
2 2
 
0.4%
3 1
 
0.2%

Length

2023-12-13T07:31:28.104882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:28.224564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 419
99.3%
2 2
 
0.5%
3 1
 
0.2%

승인금액
Real number (ℝ)

ZEROS 

Distinct156
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4838698 × 108
Minimum0
Maximum4.5 × 109
Zeros80
Zeros (%)16.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:31:28.371771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119000000
median87500000
Q32.7 × 108
95-th percentile1.082 × 109
Maximum4.5 × 109
Range4.5 × 109
Interquartile range (IQR)2.51 × 108

Descriptive statistics

Standard deviation5.102969 × 108
Coefficient of variation (CV)2.054443
Kurtosis21.419812
Mean2.4838698 × 108
Median Absolute Deviation (MAD)87500000
Skewness4.2109314
Sum1.2419349 × 1011
Variance2.6040292 × 1017
MonotonicityNot monotonic
2023-12-13T07:31:28.507370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 80
 
16.0%
19000000 71
 
14.2%
9500000 24
 
4.8%
50000000 22
 
4.4%
285000000 19
 
3.8%
190000000 14
 
2.8%
100000000 13
 
2.6%
180000000 10
 
2.0%
95000000 10
 
2.0%
297000000 10
 
2.0%
Other values (146) 227
45.4%
ValueCountFrequency (%)
0 80
16.0%
8800000 1
 
0.2%
9500000 24
 
4.8%
11050000 1
 
0.2%
14250000 2
 
0.4%
15300000 2
 
0.4%
17000000 1
 
0.2%
17850000 1
 
0.2%
19000000 71
14.2%
20000000 1
 
0.2%
ValueCountFrequency (%)
4500000000 1
0.2%
3500000000 1
0.2%
3000000000 1
0.2%
2960000000 1
0.2%
2850000000 1
0.2%
2800000000 1
0.2%
2700000000 1
0.2%
2500000000 1
0.2%
2320000000 1
0.2%
2304000000 1
0.2%

승인잔액
Real number (ℝ)

ZEROS 

Distinct156
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4834898 × 108
Minimum0
Maximum4.5 × 109
Zeros81
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:31:28.648070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119000000
median87500000
Q32.7 × 108
95-th percentile1.082 × 109
Maximum4.5 × 109
Range4.5 × 109
Interquartile range (IQR)2.51 × 108

Descriptive statistics

Standard deviation5.1031472 × 108
Coefficient of variation (CV)2.0548291
Kurtosis21.417693
Mean2.4834898 × 108
Median Absolute Deviation (MAD)87500000
Skewness4.2106652
Sum1.2417449 × 1011
Variance2.6042112 × 1017
MonotonicityNot monotonic
2023-12-13T07:31:28.782698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 81
 
16.2%
19000000 70
 
14.0%
9500000 24
 
4.8%
50000000 22
 
4.4%
285000000 19
 
3.8%
190000000 14
 
2.8%
100000000 13
 
2.6%
180000000 10
 
2.0%
95000000 10
 
2.0%
297000000 10
 
2.0%
Other values (146) 227
45.4%
ValueCountFrequency (%)
0 81
16.2%
8800000 1
 
0.2%
9500000 24
 
4.8%
11050000 1
 
0.2%
14250000 2
 
0.4%
15300000 2
 
0.4%
17000000 1
 
0.2%
17850000 1
 
0.2%
19000000 70
14.0%
20000000 1
 
0.2%
ValueCountFrequency (%)
4500000000 1
0.2%
3500000000 1
0.2%
3000000000 1
0.2%
2960000000 1
0.2%
2850000000 1
0.2%
2800000000 1
0.2%
2700000000 1
0.2%
2500000000 1
0.2%
2320000000 1
0.2%
2304000000 1
0.2%
Distinct3
Distinct (%)100.0%
Missing497
Missing (%)99.4%
Memory size4.0 KiB
2023-12-13T07:31:28.940797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length23
Min length19

Characters and Unicode

Total characters69
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row업종 및 신용등급별 포트폴리오 조정
2nd row□ 업종 및 등급별 포트폴리오 조정 등
3rd row 차입금 과다 및 업종별, 등급별 포트폴리오 조정 등
ValueCountFrequency (%)
3
15.0%
포트폴리오 3
15.0%
조정 3
15.0%
업종 2
10.0%
등급별 2
10.0%
2
10.0%
신용등급별 1
 
5.0%
1
 
5.0%
차입금 1
 
5.0%
과다 1
 
5.0%
2023-12-13T07:31:29.236764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
26.1%
5
 
7.2%
4
 
5.8%
3
 
4.3%
3
 
4.3%
3
 
4.3%
3
 
4.3%
3
 
4.3%
3
 
4.3%
3
 
4.3%
Other values (13) 21
30.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49
71.0%
Space Separator 18
 
26.1%
Other Symbol 1
 
1.4%
Other Punctuation 1
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
 
10.2%
4
 
8.2%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
Other values (10) 16
32.7%
Space Separator
ValueCountFrequency (%)
18
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49
71.0%
Common 20
29.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
 
10.2%
4
 
8.2%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
Other values (10) 16
32.7%
Common
ValueCountFrequency (%)
18
90.0%
1
 
5.0%
, 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49
71.0%
ASCII 19
 
27.5%
Geometric Shapes 1
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
94.7%
, 1
 
5.3%
Hangul
ValueCountFrequency (%)
5
 
10.2%
4
 
8.2%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
3
 
6.1%
Other values (10) 16
32.7%
Geometric Shapes
ValueCountFrequency (%)
1
100.0%

한도방법건별발급기한
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
495 
00:00.0
 
5

Length

Max length26
Median length26
Mean length25.81
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 495
99.0%
00:00.0 5
 
1.0%

Length

2023-12-13T07:31:29.380101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:29.505949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 495
49.7%
00:00:00.000000 495
49.7%
00:00.0 5
 
0.5%

한도방법건별취급기한
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
495 
00:00.0
 
5

Length

Max length26
Median length26
Mean length25.81
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 495
99.0%
00:00.0 5
 
1.0%

Length

2023-12-13T07:31:29.621088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:29.739090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 495
49.7%
00:00:00.000000 495
49.7%
00:00.0 5
 
0.5%

실행일자
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
361 
0001-01-01 00:00:00.000000
139 

Length

Max length26
Median length7
Mean length12.282
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row0001-01-01 00:00:00.000000
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 361
72.2%
0001-01-01 00:00:00.000000 139
 
27.8%

Length

2023-12-13T07:31:29.860537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:29.976232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 361
56.5%
0001-01-01 139
 
21.8%
00:00:00.000000 139
 
21.8%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
362 
0001-01-01 00:00:00.000000
138 

Length

Max length26
Median length7
Mean length12.244
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row0001-01-01 00:00:00.000000
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 362
72.4%
0001-01-01 00:00:00.000000 138
 
27.6%

Length

2023-12-13T07:31:30.093938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:30.185803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 362
56.7%
0001-01-01 138
 
21.6%
00:00:00.000000 138
 
21.6%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
365 
0001-01-01 00:00:00.000000
135 

Length

Max length26
Median length7
Mean length12.13
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row0001-01-01 00:00:00.000000
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 365
73.0%
0001-01-01 00:00:00.000000 135
 
27.0%

Length

2023-12-13T07:31:30.303402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:30.395943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 365
57.5%
0001-01-01 135
 
21.3%
00:00:00.000000 135
 
21.3%

보증금액
Real number (ℝ)

ZEROS 

Distinct139
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7852839 × 108
Minimum0
Maximum2.96 × 109
Zeros140
Zeros (%)28.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:31:30.490791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median50000000
Q32 × 108
95-th percentile6.67875 × 108
Maximum2.96 × 109
Range2.96 × 109
Interquartile range (IQR)2 × 108

Descriptive statistics

Standard deviation3.6333535 × 108
Coefficient of variation (CV)2.0351685
Kurtosis26.475537
Mean1.7852839 × 108
Median Absolute Deviation (MAD)50000000
Skewness4.6489174
Sum8.9264194 × 1010
Variance1.3201258 × 1017
MonotonicityNot monotonic
2023-12-13T07:31:30.918391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 140
28.0%
19000000 45
 
9.0%
50000000 22
 
4.4%
9500000 19
 
3.8%
285000000 18
 
3.6%
190000000 14
 
2.8%
100000000 12
 
2.4%
180000000 10
 
2.0%
297000000 10
 
2.0%
90000000 9
 
1.8%
Other values (129) 201
40.2%
ValueCountFrequency (%)
0 140
28.0%
8800000 1
 
0.2%
9500000 19
 
3.8%
14250000 1
 
0.2%
15300000 2
 
0.4%
17000000 1
 
0.2%
17850000 1
 
0.2%
19000000 45
 
9.0%
20000000 1
 
0.2%
20800000 1
 
0.2%
ValueCountFrequency (%)
2960000000 1
0.2%
2850000000 1
0.2%
2700000000 1
0.2%
2500000000 1
0.2%
2320000000 1
0.2%
2304000000 1
0.2%
2160000000 1
0.2%
1494000000 1
0.2%
1437223840 1
0.2%
1422540000 1
0.2%

보증잔액
Real number (ℝ)

ZEROS 

Distinct151
Distinct (%)30.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1620611 × 108
Minimum0
Maximum2.85 × 109
Zeros208
Zeros (%)41.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:31:31.043206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median19000000
Q31.35 × 108
95-th percentile4.759 × 108
Maximum2.85 × 109
Range2.85 × 109
Interquartile range (IQR)1.35 × 108

Descriptive statistics

Standard deviation2.6422965 × 108
Coefficient of variation (CV)2.2738017
Kurtosis39.921662
Mean1.1620611 × 108
Median Absolute Deviation (MAD)19000000
Skewness5.4326988
Sum5.8103056 × 1010
Variance6.9817309 × 1016
MonotonicityNot monotonic
2023-12-13T07:31:31.187284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 208
41.6%
19000000 35
 
7.0%
50000000 18
 
3.6%
285000000 17
 
3.4%
9500000 15
 
3.0%
190000000 12
 
2.4%
90000000 7
 
1.4%
100000000 6
 
1.2%
95000000 6
 
1.2%
135000000 6
 
1.2%
Other values (141) 170
34.0%
ValueCountFrequency (%)
0 208
41.6%
4750000 1
 
0.2%
5890000 1
 
0.2%
8800000 1
 
0.2%
9500000 15
 
3.0%
12000000 1
 
0.2%
13205000 1
 
0.2%
13832008 1
 
0.2%
14250000 1
 
0.2%
15300000 1
 
0.2%
ValueCountFrequency (%)
2850000000 1
0.2%
2242051417 1
0.2%
2000000000 1
0.2%
1488201600 1
0.2%
1370880000 1
0.2%
1350000000 2
0.4%
1080000000 1
0.2%
1000000000 2
0.4%
800000000 1
0.2%
793730000 1
0.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
361 
0001-01-01 00:00:00.000000
139 

Length

Max length26
Median length7
Mean length12.282
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row0001-01-01 00:00:00.000000
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 361
72.2%
0001-01-01 00:00:00.000000 139
 
27.8%

Length

2023-12-13T07:31:31.322208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:31.426462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 361
56.5%
0001-01-01 139
 
21.8%
00:00:00.000000 139
 
21.8%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
432 
00:00.0
68 

Length

Max length26
Median length26
Mean length23.416
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 432
86.4%
00:00.0 68
 
13.6%

Length

2023-12-13T07:31:31.526197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:31.610216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 432
46.4%
00:00:00.000000 432
46.4%
00:00.0 68
 
7.3%
Distinct303
Distinct (%)60.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:31:31.935811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.302
Min length3

Characters and Unicode

Total characters2151
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

Unique239 ?
Unique (%)47.8%

Sample

1st row5632
2nd row99006
3rd row5820
4th row6169
5th row4110
ValueCountFrequency (%)
99006 24
 
4.8%
99001 22
 
4.4%
99016 20
 
4.0%
99002 17
 
3.4%
99007 17
 
3.4%
99023 15
 
3.0%
3639 8
 
1.6%
360 7
 
1.4%
4046 5
 
1.0%
3592 5
 
1.0%
Other values (293) 360
72.0%
2023-12-13T07:31:32.427631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 395
18.4%
0 321
14.9%
5 238
11.1%
4 229
10.6%
6 205
9.5%
3 194
9.0%
2 161
7.5%
1 148
 
6.9%
7 117
 
5.4%
8 115
 
5.3%
Other values (3) 28
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2123
98.7%
Uppercase Letter 28
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 395
18.6%
0 321
15.1%
5 238
11.2%
4 229
10.8%
6 205
9.7%
3 194
9.1%
2 161
7.6%
1 148
 
7.0%
7 117
 
5.5%
8 115
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
C 17
60.7%
B 8
28.6%
A 3
 
10.7%

Most occurring scripts

ValueCountFrequency (%)
Common 2123
98.7%
Latin 28
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
9 395
18.6%
0 321
15.1%
5 238
11.2%
4 229
10.8%
6 205
9.7%
3 194
9.1%
2 161
7.6%
1 148
 
7.0%
7 117
 
5.5%
8 115
 
5.4%
Latin
ValueCountFrequency (%)
C 17
60.7%
B 8
28.6%
A 3
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2151
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 395
18.4%
0 321
14.9%
5 238
11.1%
4 229
10.6%
6 205
9.5%
3 194
9.0%
2 161
7.5%
1 148
 
6.9%
7 117
 
5.4%
8 115
 
5.3%
Other values (3) 28
 
1.3%

접수팀코드
Categorical

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
158 
2
136 
118 
3
50 
4
23 
Other values (3)
 
15

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 158
31.6%
2 136
27.2%
118
23.6%
3 50
 
10.0%
4 23
 
4.6%
N 7
 
1.4%
9 4
 
0.8%
A 4
 
0.8%

Length

2023-12-13T07:31:32.567103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:32.661515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 158
41.4%
2 136
35.6%
3 50
 
13.1%
4 23
 
6.0%
n 7
 
1.8%
9 4
 
1.0%
a 4
 
1.0%

담당팀코드
Categorical

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
180 
2
123 
96 
3
71 
4
28 
Other values (2)
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row1
2nd row
3rd row2
4th row2
5th row3

Common Values

ValueCountFrequency (%)
1 180
36.0%
2 123
24.6%
96
19.2%
3 71
 
14.2%
4 28
 
5.6%
A 1
 
0.2%
9 1
 
0.2%

Length

2023-12-13T07:31:32.763256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:32.869461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 180
44.6%
2 123
30.4%
3 71
 
17.6%
4 28
 
6.9%
a 1
 
0.2%
9 1
 
0.2%
Distinct264
Distinct (%)52.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:31:33.179290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.194
Min length4

Characters and Unicode

Total characters2097
Distinct characters11
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

Unique187 ?
Unique (%)37.4%

Sample

1st row5325
2nd row99016
3rd row5820
4th row5463
5th row5064
ValueCountFrequency (%)
4562 42
 
8.4%
99006 20
 
4.0%
99001 18
 
3.6%
99007 17
 
3.4%
99023 13
 
2.6%
99016 12
 
2.4%
99002 11
 
2.2%
5069 9
 
1.8%
4630 5
 
1.0%
4492 5
 
1.0%
Other values (253) 347
69.5%
2023-12-13T07:31:33.595093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 315
15.0%
9 309
14.7%
5 300
14.3%
4 262
12.5%
6 244
11.6%
2 169
8.1%
1 146
7.0%
3 141
6.7%
7 108
 
5.2%
8 98
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2092
99.8%
Space Separator 5
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 315
15.1%
9 309
14.8%
5 300
14.3%
4 262
12.5%
6 244
11.7%
2 169
8.1%
1 146
7.0%
3 141
6.7%
7 108
 
5.2%
8 98
 
4.7%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2097
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 315
15.0%
9 309
14.7%
5 300
14.3%
4 262
12.5%
6 244
11.6%
2 169
8.1%
1 146
7.0%
3 141
6.7%
7 108
 
5.2%
8 98
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2097
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 315
15.0%
9 309
14.7%
5 300
14.3%
4 262
12.5%
6 244
11.6%
2 169
8.1%
1 146
7.0%
3 141
6.7%
7 108
 
5.2%
8 98
 
4.7%
Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
11
333 
95 
99
41 
8
 
24
5
 
6

Length

Max length2
Median length2
Mean length1.748
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
11 333
66.6%
95
 
19.0%
99 41
 
8.2%
8 24
 
4.8%
5 6
 
1.2%
6 1
 
0.2%

Length

2023-12-13T07:31:33.719846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:33.806499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 333
82.2%
99 41
 
10.1%
8 24
 
5.9%
5 6
 
1.5%
6 1
 
0.2%
Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
실행/해지에 의한 잔액 및 진행상태코드 갱신
217 
실행에 의한 변경
116 
<NA>
72 
이수관(팀변경)에 의한 관할점 변경
28 
23 
Other values (7)
44 

Length

Max length30
Median length24
Mean length15.438
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row실행/해지에 의한 잔액 및 진행상태코드 갱신
2nd row 실행에 의한 변경
3rd row
4th row 실행에 의한 변경
5th row실행/해지에 의한 잔액 및 진행상태코드 갱신

Common Values

ValueCountFrequency (%)
실행/해지에 의한 잔액 및 진행상태코드 갱신 217
43.4%
실행에 의한 변경 116
23.2%
<NA> 72
 
14.4%
이수관(팀변경)에 의한 관할점 변경 28
 
5.6%
23
 
4.6%
승인입력에 의한 변경 17
 
3.4%
접수에 의한 변경 12
 
2.4%
승인입력에 의한 변경 7
 
1.4%
조건변경실행에 의한 변경 4
 
0.8%
조건변경에의한 변경 2
 
0.4%
Other values (2) 2
 
0.4%

Length

2023-12-13T07:31:33.904664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
의한 401
20.4%
218
11.1%
실행/해지에 217
11.0%
잔액 217
11.0%
진행상태코드 217
11.0%
갱신 217
11.0%
변경 186
9.5%
실행에 116
 
5.9%
na 72
 
3.7%
관할점 28
 
1.4%
Other values (10) 75
 
3.8%

삭제여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
499 
True
 
1
ValueCountFrequency (%)
False 499
99.8%
True 1
 
0.2%
2023-12-13T07:31:34.007043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Real number (ℝ)

Distinct74
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.82
Minimum1
Maximum126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T07:31:34.112708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median13
Q328
95-th percentile59
Maximum126
Range125
Interquartile range (IQR)22

Descriptive statistics

Standard deviation19.215047
Coefficient of variation (CV)0.96947766
Kurtosis3.1106608
Mean19.82
Median Absolute Deviation (MAD)8
Skewness1.6194892
Sum9910
Variance369.21804
MonotonicityNot monotonic
2023-12-13T07:31:34.231103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 44
 
8.8%
1 33
 
6.6%
2 33
 
6.6%
7 26
 
5.2%
12 20
 
4.0%
15 20
 
4.0%
10 17
 
3.4%
13 16
 
3.2%
20 16
 
3.2%
8 14
 
2.8%
Other values (64) 261
52.2%
ValueCountFrequency (%)
1 33
6.6%
2 33
6.6%
3 6
 
1.2%
4 12
 
2.4%
5 14
 
2.8%
6 44
8.8%
7 26
5.2%
8 14
 
2.8%
9 11
 
2.2%
10 17
 
3.4%
ValueCountFrequency (%)
126 1
0.2%
106 1
0.2%
89 1
0.2%
86 1
0.2%
84 2
0.4%
80 1
0.2%
76 1
0.2%
71 2
0.4%
69 1
0.2%
68 1
0.2%
Distinct426
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:31:34.518911image/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

Unique403 ?
Unique (%)80.6%

Sample

1st row31:46.6
2nd row31:42.0
3rd row31:36.6
4th row31:32.8
5th row31:32.8
ValueCountFrequency (%)
03:36.3 42
 
8.4%
04:20.2 9
 
1.8%
16:06.4 3
 
0.6%
08:27.1 3
 
0.6%
58:57.7 3
 
0.6%
10:12.4 3
 
0.6%
12:18.3 2
 
0.4%
18:54.8 2
 
0.4%
21:51.6 2
 
0.4%
21:41.8 2
 
0.4%
Other values (416) 429
85.8%
2023-12-13T07:31:34.936919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
0 383
10.9%
2 379
10.8%
3 357
10.2%
1 355
10.1%
5 223
6.4%
4 212
6.1%
6 176
 
5.0%
8 157
 
4.5%
Other values (2) 258
7.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 383
15.3%
2 379
15.2%
3 357
14.3%
1 355
14.2%
5 223
8.9%
4 212
8.5%
6 176
7.0%
8 157
6.3%
9 135
 
5.4%
7 123
 
4.9%
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%
0 383
10.9%
2 379
10.8%
3 357
10.2%
1 355
10.1%
5 223
6.4%
4 212
6.1%
6 176
 
5.0%
8 157
 
4.5%
Other values (2) 258
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
0 383
10.9%
2 379
10.8%
3 357
10.2%
1 355
10.1%
5 223
6.4%
4 212
6.1%
6 176
 
5.0%
8 157
 
4.5%
Other values (2) 258
7.4%
Distinct241
Distinct (%)48.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:31:35.265832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.434
Min length4

Characters and Unicode

Total characters2217
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

Unique177 ?
Unique (%)35.4%

Sample

1st row99023
2nd row99006
3rd row5820
4th row4086
5th row5064
ValueCountFrequency (%)
4562 42
 
8.4%
99001 32
 
6.4%
99006 27
 
5.4%
99007 21
 
4.2%
99016 20
 
4.0%
99023 19
 
3.8%
99002 13
 
2.6%
5069 9
 
1.8%
4493 5
 
1.0%
4366 4
 
0.8%
Other values (231) 308
61.6%
2023-12-13T07:31:35.703608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 448
20.2%
0 344
15.5%
6 280
12.6%
4 213
9.6%
5 212
9.6%
2 166
 
7.5%
1 150
 
6.8%
7 132
 
6.0%
3 122
 
5.5%
C 79
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2138
96.4%
Uppercase Letter 79
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 448
21.0%
0 344
16.1%
6 280
13.1%
4 213
10.0%
5 212
9.9%
2 166
 
7.8%
1 150
 
7.0%
7 132
 
6.2%
3 122
 
5.7%
8 71
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
C 79
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2138
96.4%
Latin 79
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
9 448
21.0%
0 344
16.1%
6 280
13.1%
4 213
10.0%
5 212
9.9%
2 166
 
7.8%
1 150
 
7.0%
7 132
 
6.2%
3 122
 
5.7%
8 71
 
3.3%
Latin
ValueCountFrequency (%)
C 79
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2217
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 448
20.2%
0 344
15.5%
6 280
12.6%
4 213
9.6%
5 212
9.6%
2 166
 
7.5%
1 150
 
6.8%
7 132
 
6.0%
3 122
 
5.5%
C 79
 
3.6%
Distinct493
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:31:36.000960image/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 row30:43.0
2nd row39:11.7
3rd row23:20.5
4th row34:19.3
5th row30:38.2
ValueCountFrequency (%)
00:00.0 7
 
1.4%
24:24.9 2
 
0.4%
21:28.8 1
 
0.2%
36:58.6 1
 
0.2%
58:47.7 1
 
0.2%
10:40.8 1
 
0.2%
10:40.4 1
 
0.2%
38:50.2 1
 
0.2%
46:28.9 1
 
0.2%
22:54.8 1
 
0.2%
Other values (483) 483
96.6%
2023-12-13T07:31:36.410531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
0 368
10.5%
1 335
9.6%
2 327
9.3%
4 307
8.8%
3 296
8.5%
5 292
8.3%
7 148
 
4.2%
9 146
 
4.2%
Other values (2) 281
8.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 368
14.7%
1 335
13.4%
2 327
13.1%
4 307
12.3%
3 296
11.8%
5 292
11.7%
7 148
5.9%
9 146
 
5.8%
8 146
 
5.8%
6 135
 
5.4%
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%
0 368
10.5%
1 335
9.6%
2 327
9.3%
4 307
8.8%
3 296
8.5%
5 292
8.3%
7 148
 
4.2%
9 146
 
4.2%
Other values (2) 281
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
0 368
10.5%
1 335
9.6%
2 327
9.3%
4 307
8.8%
3 296
8.5%
5 292
8.3%
7 148
 
4.2%
9 146
 
4.2%
Other values (2) 281
8.0%
Distinct299
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T07:31:36.736100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.326
Min length4

Characters and Unicode

Total characters2163
Distinct characters15
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

Unique230 ?
Unique (%)46.0%

Sample

1st row3734
2nd row99006
3rd row2962
4th row6169
5th row3047
ValueCountFrequency (%)
99006 24
 
4.8%
99001 22
 
4.4%
99016 20
 
4.0%
99007 17
 
3.4%
99002 17
 
3.4%
99023 15
 
3.0%
batch 7
 
1.4%
4046 6
 
1.2%
2564 5
 
1.0%
3639 5
 
1.0%
Other values (289) 362
72.4%
2023-12-13T07:31:37.156776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 385
17.8%
0 316
14.6%
3 253
11.7%
4 223
10.3%
5 196
9.1%
6 181
8.4%
2 180
8.3%
1 137
 
6.3%
7 118
 
5.5%
8 112
 
5.2%
Other values (5) 62
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2101
97.1%
Uppercase Letter 62
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 385
18.3%
0 316
15.0%
3 253
12.0%
4 223
10.6%
5 196
9.3%
6 181
8.6%
2 180
8.6%
1 137
 
6.5%
7 118
 
5.6%
8 112
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
C 23
37.1%
B 16
25.8%
A 9
 
14.5%
T 7
 
11.3%
H 7
 
11.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2101
97.1%
Latin 62
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
9 385
18.3%
0 316
15.0%
3 253
12.0%
4 223
10.6%
5 196
9.3%
6 181
8.6%
2 180
8.6%
1 137
 
6.5%
7 118
 
5.6%
8 112
 
5.3%
Latin
ValueCountFrequency (%)
C 23
37.1%
B 16
25.8%
A 9
 
14.5%
T 7
 
11.3%
H 7
 
11.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2163
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 385
17.8%
0 316
14.6%
3 253
11.7%
4 223
10.3%
5 196
9.1%
6 181
8.4%
2 180
8.3%
1 137
 
6.3%
7 118
 
5.5%
8 112
 
5.2%
Other values (5) 62
 
2.9%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
382 
2
117 
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
382
76.4%
2 117
 
23.4%
5 1
 
0.2%

Length

2023-12-13T07:31:37.269023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:31:37.344182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 117
99.2%
5 1
 
0.8%

Sample

업무구분코드원장ID기업고객ID상담등록일자접수일자원장진행상태코드원장진행상세상태코드직위재구분코드접수금액신청기한구분코드신청기한년수신청기한월수미확정신청기한명개별한도거래구분코드거래방법코드건별구분코드일반특별구분코드취급종류코드취급방법코드보증구분코드기업거래구분코드약정방법코드자금용도코드보증비율심사종류코드전결구분코드승인일자승인구분코드승인금액승인잔액불승인감액승인사유단순내용한도방법건별발급기한한도방법건별취급기한실행일자보증시작일자보증종료일자보증금액보증잔액차기보증료납입일자최종해지일자접수직원번호접수팀코드담당팀코드담당자직원번호원장변경사유코드원장변경사유단순내용삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호원장기타관리코드
0G9dbs7SzXY89a6qgM9dgY00:00.000:00.0620143700000150발급후5년1011111221195451100:00.014370000043700000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.0437000003704553100:00.00001-01-01 00:00:00.000000563211532511실행/해지에 의한 잔액 및 진행상태코드 갱신N2831:46.69902330:43.03734
1G9dnMVAfEv09dicnKm0zj00:00.000:00.06192950000000발급후 5년10111112219500:00.0195000009500000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.09500000950000000:00.00001-01-01 00:00:00.000000990069901611실행에 의한 변경N731:42.09900639:11.7990062
2G9dnAVQQabK9b6FkYxlLn00:00.000:00.0111237500000110발급후1년10111112211950001-01-01 00:00:00.00000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000005820225820N331:36.6582023:20.52962
3G9dnSGQZ1Pp9ccr1r83PJ00:00.000:00.0661114750000110발급후1년101311132118581100:00.01114750000114750000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.011475000011475000000:00.00001-01-01 00:00:00.000000616922546311실행에 의한 변경N1331:32.8408634:19.36169
4G9cEklu6yXZ9bGQRbVsAP00:00.000:00.06201160000000110발급후1년1011111221180301100:00.01160000000160000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.016000000012800000000:00.00001-01-01 00:00:00.000000411013506411실행/해지에 의한 잔액 및 진행상태코드 갱신N4431:32.8506430:38.23047
5G9cRtPJZoss9czInlhe2u00:00.000:00.06201180000000110보증서 발급일로부터 3년101111122119030700:00.01180000000180000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.01800000004798800000:00.00001-01-01 00:00:00.000000494421438611실행/해지에 의한 잔액 및 진행상태코드 갱신N4231:15.89900108:54.33412
6G9c5ApWXGMk9cc7rnRR6h00:00.000:00.0620190000000110발급후1년10111122219030700:00.019000000090000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.0900000007290000000:00.00001-01-01 00:00:00.000000450114476811실행/해지에 의한 잔액 및 진행상태코드 갱신N2531:15.09C76111:52.24501
7G9cEqpG5iXR9a6Wf3vTe400:00.000:00.06201173400000110발급후 1년101311232118581100:00.01173400000173400000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.017340000012750000000:00.00001-01-01 00:00:00.000000398413527811실행/해지에 의한 잔액 및 진행상태코드 갱신N5231:05.2527814:41.13984
8G9bQhdG6ILE9bQhcl81FP00:00.000:00.06191201000000110보증서 발급일로부터 1년1011111111110030700:00.01201000000201000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.020100000020100000000:00.00001-01-01 00:00:00.000000294943502611실행/해지에 의한 잔액 및 진행상태코드 갱신N12631:04.8586352:35.62949
9G9clpAjDvCP9bHjVZqnN800:00.000:00.062013150000001100발급후10년10111112212903700:00.01315000000315000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.031500000015750000000:00.00001-01-01 00:00:00.000000462911570999이수관(팀변경)에 의한 관할점 변경N4531:03.7598752:14.32953
업무구분코드원장ID기업고객ID상담등록일자접수일자원장진행상태코드원장진행상세상태코드직위재구분코드접수금액신청기한구분코드신청기한년수신청기한월수미확정신청기한명개별한도거래구분코드거래방법코드건별구분코드일반특별구분코드취급종류코드취급방법코드보증구분코드기업거래구분코드약정방법코드자금용도코드보증비율심사종류코드전결구분코드승인일자승인구분코드승인금액승인잔액불승인감액승인사유단순내용한도방법건별발급기한한도방법건별취급기한실행일자보증시작일자보증종료일자보증금액보증잔액차기보증료납입일자최종해지일자접수직원번호접수팀코드담당팀코드담당자직원번호원장변경사유코드원장변경사유단순내용삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호원장기타관리코드
490G9dnSO77OE39dnSO3Tu0I00:00.000:00.061921900000000발급후 5년10111111119500:00.011900000019000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.0190000001900000000:00.00001-01-01 00:00:00.000000990029900211실행에 의한 변경N758:58.49900240:41.2990022
491G9de1OWSrNL9cgl2f3BSr00:00.000:00.06211630000000110발급후1년101111211119030700:00.01630000000630000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.0630000000000:00.000:00.0435111435111실행/해지에 의한 잔액 및 진행상태코드 갱신N1558:57.7435135:51.93949
492G9dnSPTmhq99cgl2f3BSr00:00.000:00.061411000000000110발급후1년10141102321110081100:00.0110000000001000000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.01000000000100000000000:00.00001-01-01 00:00:00.000000435111435111실행에 의한 변경N758:57.7435152:24.64351
493G9de1OXsBD29cgl2f3BSr00:00.000:00.06211500000000110발급 후 1년10111102111110030700:00.01500000000500000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.0500000000000:00.000:00.0435111435111실행/해지에 의한 잔액 및 진행상태코드 갱신N1258:57.7435136:00.63949
494G9c85GVCEWV9bGGninYcV00:00.000:00.06201285000000150발급후5년101111122119530700:00.01285000000285000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.028500000024320000000:00.00001-01-01 00:00:00.000000484433484411실행/해지에 의한 잔액 및 진행상태코드 갱신N2058:56.19902318:37.63323
495G9deOiwpM6maaaaabtYTI00:00.000:00.06191285000000110보증서 발급일로부터 1년101111111119530700:00.01285000000285000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.028500000028500000000:00.00001-01-01 00:00:00.000000539911538911실행/해지에 의한 잔액 및 진행상태코드 갱신N2058:52.59C63514:01.45399
496G9cWL55vaZB9cVoSntTYV00:00.000:00.0619190000000110일년1011161111190451100:00.019000000090000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.0900000009000000000:00.00001-01-01 00:00:00.000000209131462511실행/해지에 의한 잔액 및 진행상태코드 갱신N2958:50.99C62826:27.43239
497G9cWZyvCoSQaaaaaamOm900:00.000:00.06141170000000110발급후1년10131102321110081100:00.01170000000170000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.017000000017000000000:00.00001-01-01 00:00:00.0000009A5452251325조건변경실행에 의한 변경N2858:46.7513247:07.89A545
498G9dm0jmvnvA9bwphcfSoa00:00.000:00.06141190000000150발급후5년101111111119530700:00.01190000000190000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.000:00.019000000019000000000:00.00001-01-01 00:00:00.000000606133606111실행에 의한 변경N1758:39.1606135:29.23723
499G9dmVIqYUx0aaaaaaA2E600:00.000:00.01131450000000110보증서 발급일로부터 1년10111122211900001-01-01 00:00:00.00000000<NA>0001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000000001-01-01 00:00:00.0000000001-01-01 00:00:00.000000491033491099접수에 의한 변경N558:34.1491004:59.03723