Overview

Dataset statistics

Number of variables27
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory112.9 KiB
Average record size in memory231.3 B

Variable types

Text5
Categorical15
Numeric6
Boolean1

Dataset

Description해당 파일 데이터는 신용보증기금의 보험상담마스터에 대한 정보를 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092977/fileData.do

Alerts

상담일자 has constant value ""Constant
상담채널구분코드 has constant value ""Constant
일반특별구분코드 has constant value ""Constant
직위재구분코드 has constant value ""Constant
건별구분코드 has constant value ""Constant
상담변경사유코드 has constant value ""Constant
책임종료일자 has constant value ""Constant
업무구분코드 is highly imbalanced (96.2%)Imbalance
거래방법코드 is highly imbalanced (96.2%)Imbalance
취급종류코드 is highly imbalanced (96.2%)Imbalance
신청기한명 is highly imbalanced (96.2%)Imbalance
보험상담결과구분코드 is highly imbalanced (97.9%)Imbalance
삭제여부 is highly imbalanced (77.6%)Imbalance
상담금액 is highly skewed (γ1 = 22.36066853)Skewed
상담ID has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:57:50.421105
Analysis finished2023-12-12 18:57:50.865666
Duration0.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상담ID
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T03:57:51.097165image/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 row9dnS0sGKIU
2nd row9dnS0pEiOe
3rd row9dnS0lO4OS
4th row9dnSZP2WXb
5th row9dnSZGak7j
ValueCountFrequency (%)
9dns0sgkiu 1
 
0.2%
9dnmd5jvap 1
 
0.2%
9dnmb4qif3 1
 
0.2%
9dnmb7tbyv 1
 
0.2%
9dnmcgshe2 1
 
0.2%
9dnmcra43p 1
 
0.2%
9dnmcsoobe 1
 
0.2%
9dnmcbo50j 1
 
0.2%
9dnmcurpxd 1
 
0.2%
9dnmc6f1mc 1
 
0.2%
Other values (490) 490
98.0%
2023-12-13T03:57:51.620059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 546
 
10.9%
9 541
 
10.8%
n 535
 
10.7%
M 189
 
3.8%
L 159
 
3.2%
S 140
 
2.8%
O 136
 
2.7%
K 93
 
1.9%
N 75
 
1.5%
J 64
 
1.3%
Other values (52) 2522
50.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2211
44.2%
Uppercase Letter 1770
35.4%
Decimal Number 1019
20.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 546
24.7%
n 535
24.2%
q 60
 
2.7%
b 57
 
2.6%
m 55
 
2.5%
r 55
 
2.5%
x 54
 
2.4%
a 53
 
2.4%
v 52
 
2.4%
k 50
 
2.3%
Other values (16) 694
31.4%
Uppercase Letter
ValueCountFrequency (%)
M 189
 
10.7%
L 159
 
9.0%
S 140
 
7.9%
O 136
 
7.7%
K 93
 
5.3%
N 75
 
4.2%
J 64
 
3.6%
Y 61
 
3.4%
W 59
 
3.3%
B 58
 
3.3%
Other values (16) 736
41.6%
Decimal Number
ValueCountFrequency (%)
9 541
53.1%
6 58
 
5.7%
4 57
 
5.6%
0 57
 
5.6%
5 56
 
5.5%
2 54
 
5.3%
8 53
 
5.2%
1 49
 
4.8%
3 48
 
4.7%
7 46
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 3981
79.6%
Common 1019
 
20.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 546
 
13.7%
n 535
 
13.4%
M 189
 
4.7%
L 159
 
4.0%
S 140
 
3.5%
O 136
 
3.4%
K 93
 
2.3%
N 75
 
1.9%
J 64
 
1.6%
Y 61
 
1.5%
Other values (42) 1983
49.8%
Common
ValueCountFrequency (%)
9 541
53.1%
6 58
 
5.7%
4 57
 
5.6%
0 57
 
5.6%
5 56
 
5.5%
2 54
 
5.3%
8 53
 
5.2%
1 49
 
4.8%
3 48
 
4.7%
7 46
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 546
 
10.9%
9 541
 
10.8%
n 535
 
10.7%
M 189
 
3.8%
L 159
 
3.2%
S 140
 
2.8%
O 136
 
2.7%
K 93
 
1.9%
N 75
 
1.5%
J 64
 
1.3%
Other values (52) 2522
50.4%

상담기업개요ID
Text

Distinct454
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T03:57:52.013499image/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

Unique426 ?
Unique (%)85.2%

Sample

1st row9dnS0lOzuK
2nd row9dnS0lOzuK
3rd row9dnS0lOzuK
4th row9dnSZP2uAW
5th row9dnSZdo4L8
ValueCountFrequency (%)
9dnsngccyp 8
 
1.6%
9dnoqc2bwk 5
 
1.0%
9dnn65l7zx 4
 
0.8%
9dnsj86hdb 4
 
0.8%
9dns0lozuk 3
 
0.6%
9dnowjapw9 3
 
0.6%
9dnornedt4 3
 
0.6%
9dnobtl2jq 3
 
0.6%
9dnmxtcdx4 3
 
0.6%
9dnsvukn32 2
 
0.4%
Other values (444) 462
92.4%
2023-12-13T03:57:52.547891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 551
 
11.0%
9 550
 
11.0%
n 547
 
10.9%
M 174
 
3.5%
L 151
 
3.0%
S 148
 
3.0%
O 131
 
2.6%
K 84
 
1.7%
N 79
 
1.6%
2 67
 
1.3%
Other values (52) 2518
50.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2248
45.0%
Uppercase Letter 1727
34.5%
Decimal Number 1025
20.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 551
24.5%
n 547
24.3%
c 64
 
2.8%
l 58
 
2.6%
j 58
 
2.6%
p 57
 
2.5%
b 56
 
2.5%
a 54
 
2.4%
q 54
 
2.4%
u 52
 
2.3%
Other values (16) 697
31.0%
Uppercase Letter
ValueCountFrequency (%)
M 174
 
10.1%
L 151
 
8.7%
S 148
 
8.6%
O 131
 
7.6%
K 84
 
4.9%
N 79
 
4.6%
J 66
 
3.8%
V 64
 
3.7%
W 60
 
3.5%
D 56
 
3.2%
Other values (16) 714
41.3%
Decimal Number
ValueCountFrequency (%)
9 550
53.7%
2 67
 
6.5%
6 60
 
5.9%
4 59
 
5.8%
0 58
 
5.7%
5 50
 
4.9%
3 48
 
4.7%
8 47
 
4.6%
7 47
 
4.6%
1 39
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 3975
79.5%
Common 1025
 
20.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 551
 
13.9%
n 547
 
13.8%
M 174
 
4.4%
L 151
 
3.8%
S 148
 
3.7%
O 131
 
3.3%
K 84
 
2.1%
N 79
 
2.0%
J 66
 
1.7%
V 64
 
1.6%
Other values (42) 1980
49.8%
Common
ValueCountFrequency (%)
9 550
53.7%
2 67
 
6.5%
6 60
 
5.9%
4 59
 
5.8%
0 58
 
5.7%
5 50
 
4.9%
3 48
 
4.7%
8 47
 
4.6%
7 47
 
4.6%
1 39
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 551
 
11.0%
9 550
 
11.0%
n 547
 
10.9%
M 174
 
3.5%
L 151
 
3.0%
S 148
 
3.0%
O 131
 
2.6%
K 84
 
1.7%
N 79
 
1.6%
2 67
 
1.3%
Other values (52) 2518
50.4%

신청기업고객ID
Text

Distinct451
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T03:57:52.910084image/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

Unique420 ?
Unique (%)84.0%

Sample

1st row9dnMMcH1t5
2nd row9dnMMcH1t5
3rd row9dnMMcH1t5
4th row9dmUffZf7u
5th row9dlZByBuRc
ValueCountFrequency (%)
9bbnkrsvx6 8
 
1.6%
9dihqbu7y1 5
 
1.0%
9cozbdrx2m 4
 
0.8%
9cv6su02cj 4
 
0.8%
9buymb8iqe 3
 
0.6%
9cxjf47puf 3
 
0.6%
9c4tmlv6kv 3
 
0.6%
9deplgogu9 3
 
0.6%
9dnmmch1t5 3
 
0.6%
9damuekdig 2
 
0.4%
Other values (441) 462
92.4%
2023-12-13T03:57:53.951774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 485
 
9.7%
a 432
 
8.6%
c 287
 
5.7%
d 202
 
4.0%
b 179
 
3.6%
k 81
 
1.6%
o 80
 
1.6%
S 76
 
1.5%
m 72
 
1.4%
n 72
 
1.4%
Other values (52) 3034
60.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2441
48.8%
Uppercase Letter 1550
31.0%
Decimal Number 1009
20.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 432
17.7%
c 287
 
11.8%
d 202
 
8.3%
b 179
 
7.3%
k 81
 
3.3%
o 80
 
3.3%
m 72
 
2.9%
n 72
 
2.9%
u 69
 
2.8%
j 68
 
2.8%
Other values (16) 899
36.8%
Uppercase Letter
ValueCountFrequency (%)
S 76
 
4.9%
V 71
 
4.6%
M 71
 
4.6%
H 68
 
4.4%
D 67
 
4.3%
Q 65
 
4.2%
B 64
 
4.1%
A 64
 
4.1%
I 63
 
4.1%
G 62
 
4.0%
Other values (16) 879
56.7%
Decimal Number
ValueCountFrequency (%)
9 485
48.1%
2 69
 
6.8%
5 69
 
6.8%
8 61
 
6.0%
4 61
 
6.0%
0 60
 
5.9%
7 56
 
5.6%
6 54
 
5.4%
1 53
 
5.3%
3 41
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 3991
79.8%
Common 1009
 
20.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 432
 
10.8%
c 287
 
7.2%
d 202
 
5.1%
b 179
 
4.5%
k 81
 
2.0%
o 80
 
2.0%
S 76
 
1.9%
m 72
 
1.8%
n 72
 
1.8%
V 71
 
1.8%
Other values (42) 2439
61.1%
Common
ValueCountFrequency (%)
9 485
48.1%
2 69
 
6.8%
5 69
 
6.8%
8 61
 
6.0%
4 61
 
6.0%
0 60
 
5.9%
7 56
 
5.6%
6 54
 
5.4%
1 53
 
5.3%
3 41
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 485
 
9.7%
a 432
 
8.6%
c 287
 
5.7%
d 202
 
4.0%
b 179
 
3.6%
k 81
 
1.6%
o 80
 
1.6%
S 76
 
1.5%
m 72
 
1.4%
n 72
 
1.4%
Other values (52) 3034
60.7%

업무구분코드
Categorical

IMBALANCE 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
A 498
99.6%
N 2
 
0.4%

Length

2023-12-13T03:57:54.186798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:54.357520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 498
99.6%
n 2
 
0.4%

상담일자
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

2023-12-13T03:57:54.566116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:54.734293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

상담일련번호
Real number (ℝ)

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.168
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T03:57:54.875268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum8
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.67578797
Coefficient of variation (CV)0.57858559
Kurtosis42.536101
Mean1.168
Median Absolute Deviation (MAD)0
Skewness5.8855576
Sum584
Variance0.45668938
MonotonicityNot monotonic
2023-12-13T03:57:55.065413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 454
90.8%
2 28
 
5.6%
3 9
 
1.8%
4 4
 
0.8%
5 2
 
0.4%
8 1
 
0.2%
7 1
 
0.2%
6 1
 
0.2%
ValueCountFrequency (%)
1 454
90.8%
2 28
 
5.6%
3 9
 
1.8%
4 4
 
0.8%
5 2
 
0.4%
6 1
 
0.2%
7 1
 
0.2%
8 1
 
0.2%
ValueCountFrequency (%)
8 1
 
0.2%
7 1
 
0.2%
6 1
 
0.2%
5 2
 
0.4%
4 4
 
0.8%
3 9
 
1.8%
2 28
 
5.6%
1 454
90.8%

상담팀코드
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
197 
2
168 
3
83 
4
52 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 197
39.4%
2 168
33.6%
3 83
16.6%
4 52
 
10.4%

Length

2023-12-13T03:57:55.278555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:55.449157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 197
39.4%
2 168
33.6%
3 83
16.6%
4 52
 
10.4%

상담직원번호
Real number (ℝ)

Distinct244
Distinct (%)48.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5197.128
Minimum3071
Maximum6200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T03:57:55.650642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3071
5-th percentile3620
Q14850.75
median5362
Q35723.25
95-th percentile6115.25
Maximum6200
Range3129
Interquartile range (IQR)872.5

Descriptive statistics

Standard deviation712.35215
Coefficient of variation (CV)0.1370665
Kurtosis0.21817434
Mean5197.128
Median Absolute Deviation (MAD)401.5
Skewness-0.89308749
Sum2598564
Variance507445.58
MonotonicityNot monotonic
2023-12-13T03:57:55.901366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3620 18
 
3.6%
5173 16
 
3.2%
5495 12
 
2.4%
5074 10
 
2.0%
5076 8
 
1.6%
6147 8
 
1.6%
5684 8
 
1.6%
5190 7
 
1.4%
4561 6
 
1.2%
5608 6
 
1.2%
Other values (234) 401
80.2%
ValueCountFrequency (%)
3071 2
 
0.4%
3283 2
 
0.4%
3447 2
 
0.4%
3548 2
 
0.4%
3555 1
 
0.2%
3590 6
1.2%
3593 2
 
0.4%
3608 1
 
0.2%
3611 1
 
0.2%
3613 2
 
0.4%
ValueCountFrequency (%)
6200 1
 
0.2%
6197 1
 
0.2%
6194 1
 
0.2%
6192 1
 
0.2%
6185 1
 
0.2%
6179 4
0.8%
6175 2
 
0.4%
6147 8
1.6%
6139 1
 
0.2%
6137 1
 
0.2%

상담채널구분코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2023-12-13T03:57:56.124002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:56.265794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

일반특별구분코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2023-12-13T03:57:56.437190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:56.614196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

직위재구분코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2023-12-13T03:57:56.785919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:56.950188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

상담금액
Real number (ℝ)

SKEWED 

Distinct285
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2312776 × 1011
Minimum2376318
Maximum1.11 × 1014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T03:57:57.115047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2376318
5-th percentile20000000
Q175000000
median1.8144564 × 108
Q39.525 × 108
95-th percentile5.018 × 109
Maximum1.11 × 1014
Range1.11 × 1014
Interquartile range (IQR)8.775 × 108

Descriptive statistics

Standard deviation4.9640212 × 1012
Coefficient of variation (CV)22.247439
Kurtosis499.99966
Mean2.2312776 × 1011
Median Absolute Deviation (MAD)1.3644564 × 108
Skewness22.360669
Sum1.1156388 × 1014
Variance2.4641507 × 1025
MonotonicityNot monotonic
2023-12-13T03:57:57.373187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000000 25
 
5.0%
80000000 16
 
3.2%
60000000 15
 
3.0%
30000000 12
 
2.4%
50000000 12
 
2.4%
185000000 9
 
1.8%
10000000 8
 
1.6%
110000000 7
 
1.4%
200000000 7
 
1.4%
120000000 6
 
1.2%
Other values (275) 383
76.6%
ValueCountFrequency (%)
2376318 1
 
0.2%
4000000 1
 
0.2%
5000000 1
 
0.2%
5200000 1
 
0.2%
8000000 1
 
0.2%
10000000 8
1.6%
12000000 4
0.8%
15000000 3
 
0.6%
16600000 1
 
0.2%
17000000 1
 
0.2%
ValueCountFrequency (%)
111000000000000 1
0.2%
28734000000 1
0.2%
24757000000 1
0.2%
20000000000 1
0.2%
19302000000 1
0.2%
19134000000 1
0.2%
12690000000 1
0.2%
12000000000 1
0.2%
11762000000 1
0.2%
11720000000 1
0.2%

거래방법코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
498 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
498
99.6%
1 2
 
0.4%

Length

2023-12-13T03:57:57.585436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:57.765191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2
100.0%

건별구분코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2023-12-13T03:57:57.961684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:58.135557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

취급종류코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
52
498 
51
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row52
2nd row52
3rd row52
4th row52
5th row52

Common Values

ValueCountFrequency (%)
52 498
99.6%
51 2
 
0.4%

Length

2023-12-13T03:57:58.322407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:58.505824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
52 498
99.6%
51 2
 
0.4%

취급방법코드
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
52
377 
53
118 
51
 
5

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row52
2nd row52
3rd row52
4th row53
5th row52

Common Values

ValueCountFrequency (%)
52 377
75.4%
53 118
 
23.6%
51 5
 
1.0%

Length

2023-12-13T03:57:58.706106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:58.889207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
52 377
75.4%
53 118
 
23.6%
51 5
 
1.0%

기업거래구분코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
360 
2
140 

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 (%)
1 360
72.0%
2 140
 
28.0%

Length

2023-12-13T03:57:59.069794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:59.232752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 360
72.0%
2 140
 
28.0%

신청기한명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
발급후 1년
498 
<NA>
 
2

Length

Max length6
Median length6
Mean length5.992
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row발급후 1년
2nd row발급후 1년
3rd row발급후 1년
4th row발급후 1년
5th row발급후 1년

Common Values

ValueCountFrequency (%)
발급후 1년 498
99.6%
<NA> 2
 
0.4%

Length

2023-12-13T03:57:59.413023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:59.583222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
발급후 498
49.9%
1년 498
49.9%
na 2
 
0.2%

보험상담결과구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
499 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
1 499
99.8%
3 1
 
0.2%

Length

2023-12-13T03:57:59.746024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:57:59.899783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 499
99.8%
3 1
 
0.2%

상담변경사유코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
500
100.0%

Length

2023-12-13T03:58:00.114564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:58:00.284126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

책임종료일자
Categorical

CONSTANT 

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

Length

Max length26
Median length26
Mean length26
Min length26

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

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

Length

2023-12-13T03:58:00.477449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:58:00.645763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 500
50.0%
00:00:00.000000 500
50.0%

삭제여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
482 
True
 
18
ValueCountFrequency (%)
False 482
96.4%
True 18
 
3.6%
2023-12-13T03:58:00.775968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Real number (ℝ)

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.386
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T03:58:00.882750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile3
Maximum10
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.82605613
Coefficient of variation (CV)0.5960001
Kurtosis25.6624
Mean1.386
Median Absolute Deviation (MAD)0
Skewness3.7620827
Sum693
Variance0.68236874
MonotonicityNot monotonic
2023-12-13T03:58:01.072819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 373
74.6%
2 83
 
16.6%
3 30
 
6.0%
4 11
 
2.2%
5 2
 
0.4%
10 1
 
0.2%
ValueCountFrequency (%)
1 373
74.6%
2 83
 
16.6%
3 30
 
6.0%
4 11
 
2.2%
5 2
 
0.4%
10 1
 
0.2%
ValueCountFrequency (%)
10 1
 
0.2%
5 2
 
0.4%
4 11
 
2.2%
3 30
 
6.0%
2 83
 
16.6%
1 373
74.6%

처리시각
Text

Distinct498
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T03:58:01.545228image/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

Unique496 ?
Unique (%)99.2%

Sample

1st row33:49.3
2nd row33:04.5
3rd row32:07.9
4th row24:18.3
5th row21:52.3
ValueCountFrequency (%)
23:56.9 2
 
0.4%
52:38.1 2
 
0.4%
52:00.3 1
 
0.2%
41:28.4 1
 
0.2%
33:49.3 1
 
0.2%
11:39.7 1
 
0.2%
42:13.6 1
 
0.2%
44:20.1 1
 
0.2%
47:04.6 1
 
0.2%
47:16.3 1
 
0.2%
Other values (488) 488
97.6%
2023-12-13T03:58:02.233569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
3 336
9.6%
0 322
9.2%
2 317
9.1%
5 317
9.1%
1 307
8.8%
4 288
8.2%
7 174
 
5.0%
9 155
 
4.4%
Other values (2) 284
8.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 336
13.4%
0 322
12.9%
2 317
12.7%
5 317
12.7%
1 307
12.3%
4 288
11.5%
7 174
7.0%
9 155
6.2%
6 147
5.9%
8 137
5.5%
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%
3 336
9.6%
0 322
9.2%
2 317
9.1%
5 317
9.1%
1 307
8.8%
4 288
8.2%
7 174
 
5.0%
9 155
 
4.4%
Other values (2) 284
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
3 336
9.6%
0 322
9.2%
2 317
9.1%
5 317
9.1%
1 307
8.8%
4 288
8.2%
7 174
 
5.0%
9 155
 
4.4%
Other values (2) 284
8.1%

처리직원번호
Real number (ℝ)

Distinct243
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5214.176
Minimum3071
Maximum6200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T03:58:02.427583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3071
5-th percentile3620
Q14910.5
median5376
Q35743.25
95-th percentile6120.05
Maximum6200
Range3129
Interquartile range (IQR)832.75

Descriptive statistics

Standard deviation707.89774
Coefficient of variation (CV)0.13576407
Kurtosis0.37738808
Mean5214.176
Median Absolute Deviation (MAD)390
Skewness-0.9386896
Sum2607088
Variance501119.2
MonotonicityNot monotonic
2023-12-13T03:58:02.632009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3620 18
 
3.6%
5173 16
 
3.2%
5495 12
 
2.4%
5074 10
 
2.0%
5076 8
 
1.6%
6147 8
 
1.6%
5684 8
 
1.6%
5190 7
 
1.4%
4561 6
 
1.2%
5608 6
 
1.2%
Other values (233) 401
80.2%
ValueCountFrequency (%)
3071 2
 
0.4%
3283 2
 
0.4%
3290 1
 
0.2%
3447 2
 
0.4%
3548 2
 
0.4%
3555 1
 
0.2%
3590 6
1.2%
3593 2
 
0.4%
3608 1
 
0.2%
3611 1
 
0.2%
ValueCountFrequency (%)
6200 1
 
0.2%
6197 1
 
0.2%
6194 1
 
0.2%
6192 1
 
0.2%
6185 1
 
0.2%
6179 4
0.8%
6175 2
 
0.4%
6147 8
1.6%
6139 1
 
0.2%
6137 1
 
0.2%

최초처리시각
Text

Distinct497
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T03:58:03.076580image/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

Unique494 ?
Unique (%)98.8%

Sample

1st row33:49.3
2nd row33:04.5
3rd row32:07.9
4th row24:18.3
5th row21:52.3
ValueCountFrequency (%)
34:19.5 2
 
0.4%
14:08.5 2
 
0.4%
52:38.1 2
 
0.4%
21:47.9 1
 
0.2%
17:18.7 1
 
0.2%
56:42.7 1
 
0.2%
07:05.1 1
 
0.2%
35:51.3 1
 
0.2%
07:09.1 1
 
0.2%
05:19.0 1
 
0.2%
Other values (487) 487
97.4%
2023-12-13T03:58:03.573074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
3 347
9.9%
5 320
9.1%
2 318
9.1%
0 312
8.9%
1 298
8.5%
4 296
8.5%
7 159
 
4.5%
9 157
 
4.5%
Other values (2) 293
8.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 347
13.9%
5 320
12.8%
2 318
12.7%
0 312
12.5%
1 298
11.9%
4 296
11.8%
7 159
6.4%
9 157
6.3%
6 147
5.9%
8 146
5.8%
Other Punctuation
ValueCountFrequency (%)
: 500
50.0%
. 500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
3 347
9.9%
5 320
9.1%
2 318
9.1%
0 312
8.9%
1 298
8.5%
4 296
8.5%
7 159
 
4.5%
9 157
 
4.5%
Other values (2) 293
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
3 347
9.9%
5 320
9.1%
2 318
9.1%
0 312
8.9%
1 298
8.5%
4 296
8.5%
7 159
 
4.5%
9 157
 
4.5%
Other values (2) 293
8.4%

최초처리직원번호
Real number (ℝ)

Distinct243
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5212.688
Minimum3071
Maximum6200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T03:58:03.742403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3071
5-th percentile3620
Q14910.5
median5376
Q35738.25
95-th percentile6120.05
Maximum6200
Range3129
Interquartile range (IQR)827.75

Descriptive statistics

Standard deviation706.77093
Coefficient of variation (CV)0.13558665
Kurtosis0.38561126
Mean5212.688
Median Absolute Deviation (MAD)390
Skewness-0.94105666
Sum2606344
Variance499525.14
MonotonicityNot monotonic
2023-12-13T03:58:03.928210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3620 18
 
3.6%
5173 16
 
3.2%
5495 12
 
2.4%
5074 10
 
2.0%
5076 8
 
1.6%
6147 8
 
1.6%
5684 8
 
1.6%
5190 7
 
1.4%
5617 6
 
1.2%
3590 6
 
1.2%
Other values (233) 401
80.2%
ValueCountFrequency (%)
3071 2
 
0.4%
3283 2
 
0.4%
3290 1
 
0.2%
3447 2
 
0.4%
3548 2
 
0.4%
3555 1
 
0.2%
3590 6
1.2%
3593 2
 
0.4%
3608 1
 
0.2%
3611 1
 
0.2%
ValueCountFrequency (%)
6200 1
 
0.2%
6197 1
 
0.2%
6194 1
 
0.2%
6192 1
 
0.2%
6185 1
 
0.2%
6179 4
0.8%
6175 2
 
0.4%
6147 8
1.6%
6139 1
 
0.2%
6137 1
 
0.2%

Sample

상담ID상담기업개요ID신청기업고객ID업무구분코드상담일자상담일련번호상담팀코드상담직원번호상담채널구분코드일반특별구분코드직위재구분코드상담금액거래방법코드건별구분코드취급종류코드취급방법코드기업거래구분코드신청기한명보험상담결과구분코드상담변경사유코드책임종료일자삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
09dnS0sGKIU9dnS0lOzuK9dnMMcH1t5A00:00.032561711165000000152521발급후 1년10001-01-01 00:00:00.000000N133:49.3561733:49.35617
19dnS0pEiOe9dnS0lOzuK9dnMMcH1t5A00:00.022561711165000000152521발급후 1년10001-01-01 00:00:00.000000N133:04.5561733:04.55617
29dnS0lO4OS9dnS0lOzuK9dnMMcH1t5A00:00.0125617111185000000152521발급후 1년10001-01-01 00:00:00.000000N132:07.9561732:07.95617
39dnSZP2WXb9dnSZP2uAW9dmUffZf7uA00:00.01157631113702000000152531발급후 1년10001-01-01 00:00:00.000000N124:18.3576324:18.35763
49dnSZGak7j9dnSZdo4L89dlZByBuRcA00:00.02250761111500000000152521발급후 1년10001-01-01 00:00:00.000000N121:52.3507621:52.35076
59dnSYJaCEp9dnSYI99A69cDUgAt7xXA00:00.014607211165000000152521발급후 1년10001-01-01 00:00:00.000000N317:53.2607207:20.76072
69dnSZdpCTa9dnSZdo4L89dlZByBuRcA00:00.01250761111500000000152521발급후 1년10001-01-01 00:00:00.000000Y216:28.3507614:47.45076
79dnSYaPV2i9dnSYaPBgC9dnMME92VcA00:00.0125621111960000000152521발급후 1년10001-01-01 00:00:00.000000N203:08.1562158:53.45621
89dnSX6Zels9dnSX6YSQt9c1C5QIKZFA00:00.0125464111351000000152531발급후 1년10001-01-01 00:00:00.000000N157:56.5546457:56.55464
99dnSXWjO4A9dnSVUKN329dgIFHzQfjA00:00.0244992111100000000152521발급후 1년10001-01-01 00:00:00.000000N155:18.8499255:18.84992
상담ID상담기업개요ID신청기업고객ID업무구분코드상담일자상담일련번호상담팀코드상담직원번호상담채널구분코드일반특별구분코드직위재구분코드상담금액거래방법코드건별구분코드취급종류코드취급방법코드기업거래구분코드신청기한명보험상담결과구분코드상담변경사유코드책임종료일자삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
4909dnJ9aj1qG9dnJ9ajFXo9cEkp9LMtkA00:00.01154401113600000000152531발급후 1년10001-01-01 00:00:00.000000N146:41.0544046:41.05440
4919dnJ8Vp3BQ9dnJ8VpDKSaaaaacc5zZA00:00.013507411119302000000152532발급후 1년10001-01-01 00:00:00.000000N143:00.9507443:00.95074
4929dnJ6W7rSB9dnJ6W65PP9cyPHMbgPmA00:00.014613111116600000152521발급후 1년10001-01-01 00:00:00.000000N112:53.7613112:53.76131
4939dnJ58ADzf9dnJ58AcXd9cCvE2brVMA00:00.0125190111100000000152521발급후 1년10001-01-01 00:00:00.000000Y202:19.6519000:27.05190
4949dnJ56xySf9dnJ56xaAZ9cUChk45FiA00:00.01135901111300000000152531발급후 1년10001-01-01 00:00:00.000000N159:56.8359059:56.83590
4959dnJ54Xvhf9dnJ54W8nu9cSFUDC1gnA00:00.0144043111550000000152522발급후 1년10001-01-01 00:00:00.000000N159:33.4425959:33.44259
4969dnDOBmZSx9dnDOBmEt2aaaaaaoG5FA00:00.0125411111120000000152521발급후 1년10001-01-01 00:00:00.000000N1057:15.6541152:40.65411
4979dnJ41qXZr9dnJ41qtjt9dnAzlhwU2A00:00.0123447111580000000152531발급후 1년10001-01-01 00:00:00.000000N143:25.1344743:25.13447
4989dnJWKiHfQ9dnJWKiiHu9btQWDPG4UA00:00.013361311130000000152521발급후 1년10001-01-01 00:00:00.000000N332:52.2361337:02.93613
4999dnJ39ug1C9dnJ39tHyo9chNHQCaUQA00:00.0125038111100000000152521발급후 1년10001-01-01 00:00:00.000000N130:08.0503830:08.05038