Overview

Dataset statistics

Number of variables21
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory86.6 KiB
Average record size in memory177.3 B

Variable types

Text7
DateTime2
Categorical5
Numeric6
Boolean1

Dataset

Description해당 파일 데이터는 신용보증기금의 보험상담기업마스터에 대한 정보를 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092982/fileData.do

Alerts

상담일자 has constant value ""Constant
설립일자 has constant value ""Constant
보험상담업종구분코드 has constant value ""Constant
사업장소유구분코드 has constant value ""Constant
삭제여부 has constant value ""Constant
최종업종차수 is highly imbalanced (97.9%)Imbalance
상담기업개요ID has unique valuesUnique
상시직원수 has 81 (16.2%) zerosZeros

Reproduction

Analysis started2023-12-12 19:38:20.501013
Analysis finished2023-12-12 19:38:21.041249
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상담기업개요ID
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T04:38:21.288931image/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 row9dnS0lOzuK
2nd row9dnSZP2uAW
3rd row9dnSZdo4L8
4th row9dnSYI99A6
5th row9dnSYaPBgC
ValueCountFrequency (%)
9dns0lozuk 1
 
0.2%
9dnb3ynsnl 1
 
0.2%
9dnlr2dhty 1
 
0.2%
9dnlte5dig 1
 
0.2%
9dnltxkrwd 1
 
0.2%
9dnltwtcpt 1
 
0.2%
9dnltekgp9 1
 
0.2%
9dnlucw2po 1
 
0.2%
9dnlvgomig 1
 
0.2%
9dnlvqq8w8 1
 
0.2%
Other values (490) 490
98.0%
2023-12-13T04:38:21.716198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 554
 
11.1%
d 549
 
11.0%
n 541
 
10.8%
M 166
 
3.3%
L 150
 
3.0%
S 136
 
2.7%
O 122
 
2.4%
J 104
 
2.1%
K 85
 
1.7%
V 68
 
1.4%
Other values (52) 2525
50.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2234
44.7%
Uppercase Letter 1740
34.8%
Decimal Number 1026
20.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 549
24.6%
n 541
24.2%
p 56
 
2.5%
g 55
 
2.5%
a 55
 
2.5%
j 55
 
2.5%
z 54
 
2.4%
q 53
 
2.4%
x 53
 
2.4%
l 52
 
2.3%
Other values (16) 711
31.8%
Uppercase Letter
ValueCountFrequency (%)
M 166
 
9.5%
L 150
 
8.6%
S 136
 
7.8%
O 122
 
7.0%
J 104
 
6.0%
K 85
 
4.9%
V 68
 
3.9%
N 67
 
3.9%
W 61
 
3.5%
P 60
 
3.4%
Other values (16) 721
41.4%
Decimal Number
ValueCountFrequency (%)
9 554
54.0%
2 60
 
5.8%
0 59
 
5.8%
4 58
 
5.7%
6 56
 
5.5%
3 52
 
5.1%
5 50
 
4.9%
1 48
 
4.7%
7 45
 
4.4%
8 44
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 3974
79.5%
Common 1026
 
20.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 549
 
13.8%
n 541
 
13.6%
M 166
 
4.2%
L 150
 
3.8%
S 136
 
3.4%
O 122
 
3.1%
J 104
 
2.6%
K 85
 
2.1%
V 68
 
1.7%
N 67
 
1.7%
Other values (42) 1986
50.0%
Common
ValueCountFrequency (%)
9 554
54.0%
2 60
 
5.8%
0 59
 
5.8%
4 58
 
5.7%
6 56
 
5.5%
3 52
 
5.1%
5 50
 
4.9%
1 48
 
4.7%
7 45
 
4.4%
8 44
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 554
 
11.1%
d 549
 
11.0%
n 541
 
10.8%
M 166
 
3.3%
L 150
 
3.0%
S 136
 
2.7%
O 122
 
2.4%
J 104
 
2.1%
K 85
 
1.7%
V 68
 
1.4%
Other values (52) 2525
50.5%

신청기업고객ID
Text

Distinct496
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T04:38:21.990735image/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

Unique492 ?
Unique (%)98.4%

Sample

1st row9dnMMcH1t5
2nd row9dmUffZf7u
3rd row9dlZByBuRc
4th row9cDUgAt7xX
5th row9dnMME92Vc
ValueCountFrequency (%)
9a8hhcf9lv 2
 
0.4%
9dhzrbccae 2
 
0.4%
9bqapjnvv8 2
 
0.4%
9baxs3vttm 2
 
0.4%
9czoifvmzx 1
 
0.2%
9ddtc1gdjq 1
 
0.2%
9dl4zcbwtw 1
 
0.2%
9cmpu9n10x 1
 
0.2%
9cyz08a2co 1
 
0.2%
9cpagwigas 1
 
0.2%
Other values (486) 486
97.2%
2023-12-13T04:38:22.398668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 478
 
9.6%
a 473
 
9.5%
c 281
 
5.6%
d 201
 
4.0%
b 170
 
3.4%
m 76
 
1.5%
k 75
 
1.5%
o 74
 
1.5%
5 71
 
1.4%
n 71
 
1.4%
Other values (52) 3030
60.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2474
49.5%
Uppercase Letter 1530
30.6%
Decimal Number 996
19.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 473
19.1%
c 281
 
11.4%
d 201
 
8.1%
b 170
 
6.9%
m 76
 
3.1%
k 75
 
3.0%
o 74
 
3.0%
n 71
 
2.9%
z 67
 
2.7%
l 67
 
2.7%
Other values (16) 919
37.1%
Uppercase Letter
ValueCountFrequency (%)
U 70
 
4.6%
A 68
 
4.4%
S 67
 
4.4%
D 67
 
4.4%
Q 65
 
4.2%
C 64
 
4.2%
I 62
 
4.1%
B 62
 
4.1%
H 62
 
4.1%
V 62
 
4.1%
Other values (16) 881
57.6%
Decimal Number
ValueCountFrequency (%)
9 478
48.0%
5 71
 
7.1%
2 69
 
6.9%
8 66
 
6.6%
4 62
 
6.2%
0 59
 
5.9%
7 56
 
5.6%
1 49
 
4.9%
6 43
 
4.3%
3 43
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 4004
80.1%
Common 996
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 473
 
11.8%
c 281
 
7.0%
d 201
 
5.0%
b 170
 
4.2%
m 76
 
1.9%
k 75
 
1.9%
o 74
 
1.8%
n 71
 
1.8%
U 70
 
1.7%
A 68
 
1.7%
Other values (42) 2445
61.1%
Common
ValueCountFrequency (%)
9 478
48.0%
5 71
 
7.1%
2 69
 
6.9%
8 66
 
6.6%
4 62
 
6.2%
0 59
 
5.9%
7 56
 
5.6%
1 49
 
4.9%
6 43
 
4.3%
3 43
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 478
 
9.6%
a 473
 
9.5%
c 281
 
5.6%
d 201
 
4.0%
b 170
 
3.4%
m 76
 
1.5%
k 75
 
1.5%
o 74
 
1.5%
5 71
 
1.4%
n 71
 
1.4%
Other values (52) 3030
60.6%

상담일자
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
2023-12-13T04:38:22.562599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:38:22.655752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

기업거래구분코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
362 
2
138 

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 (%)
1 362
72.4%
2 138
 
27.6%

Length

2023-12-13T04:38:22.792385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:38:22.893874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 362
72.4%
2 138
 
27.6%

상담의뢰인회사관계코드
Real number (ℝ)

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.364
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T04:38:22.983157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile5
Maximum99
Range98
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.782127
Coefficient of variation (CV)3.7149438
Kurtosis115.92602
Mean2.364
Median Absolute Deviation (MAD)0
Skewness10.722775
Sum1182
Variance77.125756
MonotonicityNot monotonic
2023-12-13T04:38:23.104158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 403
80.6%
5 46
 
9.2%
4 20
 
4.0%
3 19
 
3.8%
2 8
 
1.6%
99 4
 
0.8%
ValueCountFrequency (%)
1 403
80.6%
2 8
 
1.6%
3 19
 
3.8%
4 20
 
4.0%
5 46
 
9.2%
99 4
 
0.8%
ValueCountFrequency (%)
99 4
 
0.8%
5 46
 
9.2%
4 20
 
4.0%
3 19
 
3.8%
2 8
 
1.6%
1 403
80.6%

보험상담동기코드
Real number (ℝ)

Distinct9
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.638
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T04:38:23.225170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q15
median7
Q37
95-th percentile7
Maximum99
Range98
Interquartile range (IQR)2

Descriptive statistics

Standard deviation7.2999682
Coefficient of variation (CV)1.099724
Kurtosis152.92294
Mean6.638
Median Absolute Deviation (MAD)0
Skewness12.20913
Sum3319
Variance53.289535
MonotonicityNot monotonic
2023-12-13T04:38:23.360952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
7 299
59.8%
5 168
33.6%
1 11
 
2.2%
4 8
 
1.6%
3 6
 
1.2%
6 3
 
0.6%
99 3
 
0.6%
8 1
 
0.2%
2 1
 
0.2%
ValueCountFrequency (%)
1 11
 
2.2%
2 1
 
0.2%
3 6
 
1.2%
4 8
 
1.6%
5 168
33.6%
6 3
 
0.6%
7 299
59.8%
8 1
 
0.2%
99 3
 
0.6%
ValueCountFrequency (%)
99 3
 
0.6%
8 1
 
0.2%
7 299
59.8%
6 3
 
0.6%
5 168
33.6%
4 8
 
1.6%
3 6
 
1.2%
2 1
 
0.2%
1 11
 
2.2%

설립일자
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
2023-12-13T04:38:23.470223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:38:23.581792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

최종업종차수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
10
499 
9
 
1

Length

Max length2
Median length2
Mean length1.998
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
10 499
99.8%
9 1
 
0.2%

Length

2023-12-13T04:38:23.716221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:38:23.836014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 499
99.8%
9 1
 
0.2%

업종코드
Text

Distinct243
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T04:38:24.145055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters3000
Distinct characters19
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

Unique143 ?
Unique (%)28.6%

Sample

1st rowC10309
2nd rowC33999
3rd rowC22213
4th rowG46332
5th rowH49301
ValueCountFrequency (%)
g46721 30
 
6.0%
g46699 14
 
2.8%
h52992 12
 
2.4%
g47912 12
 
2.4%
g46510 9
 
1.8%
c30399 8
 
1.6%
g46739 8
 
1.6%
c25929 7
 
1.4%
g46599 6
 
1.2%
c10129 6
 
1.2%
Other values (233) 388
77.6%
2023-12-13T04:38:24.704330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 535
17.8%
1 415
13.8%
9 337
11.2%
4 333
11.1%
6 245
8.2%
C 237
7.9%
3 222
7.4%
G 210
 
7.0%
0 151
 
5.0%
5 120
 
4.0%
Other values (9) 195
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2500
83.3%
Uppercase Letter 500
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 535
21.4%
1 415
16.6%
9 337
13.5%
4 333
13.3%
6 245
9.8%
3 222
8.9%
0 151
 
6.0%
5 120
 
4.8%
7 112
 
4.5%
8 30
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
C 237
47.4%
G 210
42.0%
H 19
 
3.8%
M 9
 
1.8%
E 8
 
1.6%
N 7
 
1.4%
J 7
 
1.4%
S 2
 
0.4%
A 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2500
83.3%
Latin 500
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 535
21.4%
1 415
16.6%
9 337
13.5%
4 333
13.3%
6 245
9.8%
3 222
8.9%
0 151
 
6.0%
5 120
 
4.8%
7 112
 
4.5%
8 30
 
1.2%
Latin
ValueCountFrequency (%)
C 237
47.4%
G 210
42.0%
H 19
 
3.8%
M 9
 
1.8%
E 8
 
1.6%
N 7
 
1.4%
J 7
 
1.4%
S 2
 
0.4%
A 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 535
17.8%
1 415
13.8%
9 337
11.2%
4 333
11.1%
6 245
8.2%
C 237
7.9%
3 222
7.4%
G 210
 
7.0%
0 151
 
5.0%
5 120
 
4.0%
Other values (9) 195
 
6.5%

보험상담업종구분코드
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

2023-12-13T04:38:24.883862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:38:24.987072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

주요제품명
Text

Distinct438
Distinct (%)87.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T04:38:25.232338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length6.428
Min length1

Characters and Unicode

Total characters3214
Distinct characters345
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique399 ?
Unique (%)79.8%

Sample

1st row과실
2nd row소상장제
3rd row플라스틱시트
4th row수소수
5th row운송업 외
ValueCountFrequency (%)
등 69
 
8.5%
외 33
 
4.1%
및 21
 
2.6%
자동차부품 10
 
1.2%
건축자재 9
 
1.1%
철강재 8
 
1.0%
철강 8
 
1.0%
가구 7
 
0.9%
도매 6
 
0.7%
화공약품 6
 
0.7%
Other values (494) 636
78.2%
2023-12-13T04:38:25.703308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
348
 
10.8%
품 110
 
3.4%
기 95
 
3.0%
등 76
 
2.4%
, 73
 
2.3%
자 60
 
1.9%
스 53
 
1.6%
재 52
 
1.6%
제 48
 
1.5%
가 47
 
1.5%
Other values (335) 2252
70.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2711
84.3%
Space Separator 348
 
10.8%
Other Punctuation 75
 
2.3%
Uppercase Letter 26
 
0.8%
Close Punctuation 23
 
0.7%
Open Punctuation 23
 
0.7%
Lowercase Letter 6
 
0.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 110
 
4.1%
기 95
 
3.5%
등 76
 
2.8%
자 60
 
2.2%
스 53
 
2.0%
재 52
 
1.9%
제 48
 
1.8%
가 47
 
1.7%
철 46
 
1.7%
용 46
 
1.7%
Other values (313) 2078
76.7%
Uppercase Letter
ValueCountFrequency (%)
C 7
26.9%
D 5
19.2%
P 4
15.4%
S 2
 
7.7%
E 2
 
7.7%
L 2
 
7.7%
O 1
 
3.8%
B 1
 
3.8%
V 1
 
3.8%
U 1
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
p 1
16.7%
r 1
16.7%
e 1
16.7%
i 1
16.7%
l 1
16.7%
a 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 73
97.3%
. 2
 
2.7%
Space Separator
ValueCountFrequency (%)
348
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2704
84.1%
Common 471
 
14.7%
Latin 32
 
1.0%
Han 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 110
 
4.1%
기 95
 
3.5%
등 76
 
2.8%
자 60
 
2.2%
스 53
 
2.0%
재 52
 
1.9%
제 48
 
1.8%
가 47
 
1.7%
철 46
 
1.7%
용 46
 
1.7%
Other values (312) 2071
76.6%
Latin
ValueCountFrequency (%)
C 7
21.9%
D 5
15.6%
P 4
12.5%
S 2
 
6.2%
E 2
 
6.2%
L 2
 
6.2%
p 1
 
3.1%
r 1
 
3.1%
e 1
 
3.1%
i 1
 
3.1%
Other values (6) 6
18.8%
Common
ValueCountFrequency (%)
348
73.9%
, 73
 
15.5%
) 23
 
4.9%
( 23
 
4.9%
- 2
 
0.4%
. 2
 
0.4%
Han
ValueCountFrequency (%)
外 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2701
84.0%
ASCII 503
 
15.7%
CJK 7
 
0.2%
Compat Jamo 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
348
69.2%
, 73
 
14.5%
) 23
 
4.6%
( 23
 
4.6%
C 7
 
1.4%
D 5
 
1.0%
P 4
 
0.8%
S 2
 
0.4%
- 2
 
0.4%
. 2
 
0.4%
Other values (12) 14
 
2.8%
Hangul
ValueCountFrequency (%)
품 110
 
4.1%
기 95
 
3.5%
등 76
 
2.8%
자 60
 
2.2%
스 53
 
2.0%
재 52
 
1.9%
제 48
 
1.8%
가 47
 
1.7%
철 46
 
1.7%
용 46
 
1.7%
Other values (310) 2068
76.6%
CJK
ValueCountFrequency (%)
外 7
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄹ 2
66.7%
ㄴ 1
33.3%

상시직원수
Real number (ℝ)

ZEROS 

Distinct61
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.184
Minimum0
Maximum172
Zeros81
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T04:38:26.176883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6
Q313
95-th percentile40
Maximum172
Range172
Interquartile range (IQR)11

Descriptive statistics

Standard deviation16.607521
Coefficient of variation (CV)1.4849357
Kurtosis23.638146
Mean11.184
Median Absolute Deviation (MAD)5
Skewness3.8873259
Sum5592
Variance275.80976
MonotonicityNot monotonic
2023-12-13T04:38:26.379091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 81
16.2%
3 39
 
7.8%
5 35
 
7.0%
2 33
 
6.6%
4 29
 
5.8%
1 26
 
5.2%
9 21
 
4.2%
6 21
 
4.2%
7 20
 
4.0%
8 20
 
4.0%
Other values (51) 175
35.0%
ValueCountFrequency (%)
0 81
16.2%
1 26
 
5.2%
2 33
6.6%
3 39
7.8%
4 29
 
5.8%
5 35
7.0%
6 21
 
4.2%
7 20
 
4.0%
8 20
 
4.0%
9 21
 
4.2%
ValueCountFrequency (%)
172 1
0.2%
105 1
0.2%
99 1
0.2%
94 1
0.2%
89 1
0.2%
74 1
0.2%
72 1
0.2%
71 1
0.2%
66 1
0.2%
65 1
0.2%

기업규모코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
4
441 
3
59 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
4 441
88.2%
3 59
 
11.8%

Length

2023-12-13T04:38:26.555902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:38:26.656006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 441
88.2%
3 59
 
11.8%

사업장주소통합ID
Text

Distinct496
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T04:38:26.970390image/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

Unique492 ?
Unique (%)98.4%

Sample

1st row9dnMMcH2HM
2nd row9dmUffZjwb
3rd row9dlZByCf93
4th row9j2WgPBcjt
5th row9dnMME94cY
ValueCountFrequency (%)
9j2wgnv3ib 2
 
0.4%
9dl4xkatei 2
 
0.4%
9j2wgpc8um 2
 
0.4%
9j2wgorhcq 2
 
0.4%
9j2wgt65vo 1
 
0.2%
9deq2rd9t3 1
 
0.2%
9dmpqjr2fn 1
 
0.2%
9c5bxpy0sb 1
 
0.2%
9j2wgt6nrn 1
 
0.2%
9dndujhmqk 1
 
0.2%
Other values (486) 486
97.2%
2023-12-13T04:38:27.449157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 557
 
11.1%
d 320
 
6.4%
2 266
 
5.3%
j 243
 
4.9%
W 237
 
4.7%
g 232
 
4.6%
c 120
 
2.4%
n 111
 
2.2%
T 102
 
2.0%
O 93
 
1.9%
Other values (52) 2719
54.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2107
42.1%
Uppercase Letter 1641
32.8%
Decimal Number 1252
25.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 320
15.2%
j 243
 
11.5%
g 232
 
11.0%
c 120
 
5.7%
n 111
 
5.3%
m 83
 
3.9%
e 68
 
3.2%
b 66
 
3.1%
i 66
 
3.1%
l 59
 
2.8%
Other values (16) 739
35.1%
Uppercase Letter
ValueCountFrequency (%)
W 237
 
14.4%
T 102
 
6.2%
O 93
 
5.7%
P 78
 
4.8%
A 72
 
4.4%
B 68
 
4.1%
V 67
 
4.1%
H 63
 
3.8%
N 60
 
3.7%
J 58
 
3.5%
Other values (16) 743
45.3%
Decimal Number
ValueCountFrequency (%)
9 557
44.5%
2 266
21.2%
5 68
 
5.4%
7 56
 
4.5%
3 54
 
4.3%
8 54
 
4.3%
1 52
 
4.2%
4 51
 
4.1%
6 50
 
4.0%
0 44
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 3748
75.0%
Common 1252
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 320
 
8.5%
j 243
 
6.5%
W 237
 
6.3%
g 232
 
6.2%
c 120
 
3.2%
n 111
 
3.0%
T 102
 
2.7%
O 93
 
2.5%
m 83
 
2.2%
P 78
 
2.1%
Other values (42) 2129
56.8%
Common
ValueCountFrequency (%)
9 557
44.5%
2 266
21.2%
5 68
 
5.4%
7 56
 
4.5%
3 54
 
4.3%
8 54
 
4.3%
1 52
 
4.2%
4 51
 
4.1%
6 50
 
4.0%
0 44
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 557
 
11.1%
d 320
 
6.4%
2 266
 
5.3%
j 243
 
4.9%
W 237
 
4.7%
g 232
 
4.6%
c 120
 
2.4%
n 111
 
2.2%
T 102
 
2.0%
O 93
 
1.9%
Other values (52) 2719
54.4%

사업장소유구분코드
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

2023-12-13T04:38:27.630615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:38:27.723015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
500 
ValueCountFrequency (%)
False 500
100.0%
2023-12-13T04:38:27.798488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Real number (ℝ)

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.508
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T04:38:27.901876image/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 deviation1.0715561
Coefficient of variation (CV)0.71058096
Kurtosis17.43966
Mean1.508
Median Absolute Deviation (MAD)0
Skewness3.5113789
Sum754
Variance1.1482325
MonotonicityNot monotonic
2023-12-13T04:38:28.045706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 356
71.2%
2 85
 
17.0%
3 35
 
7.0%
4 13
 
2.6%
5 5
 
1.0%
6 2
 
0.4%
8 1
 
0.2%
7 1
 
0.2%
10 1
 
0.2%
9 1
 
0.2%
ValueCountFrequency (%)
1 356
71.2%
2 85
 
17.0%
3 35
 
7.0%
4 13
 
2.6%
5 5
 
1.0%
6 2
 
0.4%
7 1
 
0.2%
8 1
 
0.2%
9 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
10 1
 
0.2%
9 1
 
0.2%
8 1
 
0.2%
7 1
 
0.2%
6 2
 
0.4%
5 5
 
1.0%
4 13
 
2.6%
3 35
 
7.0%
2 85
 
17.0%
1 356
71.2%

처리시각
Text

Distinct497
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T04:38:28.443424image/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 row24:18.3
3rd row21:52.3
4th row17:53.2
5th row03:08.1
ValueCountFrequency (%)
23:56.9 2
 
0.4%
52:38.1 2
 
0.4%
15:25.8 2
 
0.4%
52:47.0 1
 
0.2%
37:27.3 1
 
0.2%
34:49.5 1
 
0.2%
39:54.5 1
 
0.2%
44:30.2 1
 
0.2%
50:41.7 1
 
0.2%
53:14.2 1
 
0.2%
Other values (487) 487
97.4%
2023-12-13T04:38:29.001647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
5 335
9.6%
3 328
9.4%
0 320
9.1%
1 306
8.7%
2 302
8.6%
4 289
8.3%
7 179
 
5.1%
9 157
 
4.5%
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 (%)
5 335
13.4%
3 328
13.1%
0 320
12.8%
1 306
12.2%
2 302
12.1%
4 289
11.6%
7 179
7.2%
9 157
6.3%
6 143
5.7%
8 141
5.6%
Other Punctuation
ValueCountFrequency (%)
: 500
50.0%
. 500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
5 335
9.6%
3 328
9.4%
0 320
9.1%
1 306
8.7%
2 302
8.6%
4 289
8.3%
7 179
 
5.1%
9 157
 
4.5%
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%
5 335
9.6%
3 328
9.4%
0 320
9.1%
1 306
8.7%
2 302
8.6%
4 289
8.3%
7 179
 
5.1%
9 157
 
4.5%
Other values (2) 284
8.1%

처리직원번호
Real number (ℝ)

Distinct261
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5222.242
Minimum3071
Maximum6200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T04:38:29.187853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3071
5-th percentile3613
Q14950.25
median5378
Q35762.25
95-th percentile6098.25
Maximum6200
Range3129
Interquartile range (IQR)812

Descriptive statistics

Standard deviation704.69448
Coefficient of variation (CV)0.13494098
Kurtosis0.42540095
Mean5222.242
Median Absolute Deviation (MAD)391.5
Skewness-0.96186432
Sum2611121
Variance496594.3
MonotonicityNot monotonic
2023-12-13T04:38:29.353362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3620 11
 
2.2%
4561 9
 
1.8%
5074 9
 
1.8%
5684 8
 
1.6%
5495 8
 
1.6%
5076 7
 
1.4%
5190 7
 
1.4%
5040 7
 
1.4%
5173 7
 
1.4%
3590 6
 
1.2%
Other values (251) 421
84.2%
ValueCountFrequency (%)
3071 2
 
0.4%
3283 2
 
0.4%
3290 1
 
0.2%
3447 2
 
0.4%
3548 4
0.8%
3555 1
 
0.2%
3590 6
1.2%
3593 2
 
0.4%
3594 1
 
0.2%
3598 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 3
0.6%
6175 1
 
0.2%
6147 6
1.2%
6139 1
 
0.2%
6137 1
 
0.2%

최초처리시각
Text

Distinct495
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T04:38:29.757115image/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

Unique490 ?
Unique (%)98.0%

Sample

1st row32:07.9
2nd row24:18.3
3rd row14:47.4
4th row07:20.7
5th row58:53.4
ValueCountFrequency (%)
15:25.8 2
 
0.4%
34:19.5 2
 
0.4%
52:38.1 2
 
0.4%
59:34.3 2
 
0.4%
14:08.5 2
 
0.4%
13:14.5 1
 
0.2%
18:55.9 1
 
0.2%
18:40.4 1
 
0.2%
14:58.4 1
 
0.2%
38:30.2 1
 
0.2%
Other values (485) 485
97.0%
2023-12-13T04:38:30.350455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
3 349
10.0%
5 331
9.5%
0 307
8.8%
4 302
8.6%
1 301
8.6%
2 300
8.6%
7 165
 
4.7%
9 156
 
4.5%
Other values (2) 289
8.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 349
14.0%
5 331
13.2%
0 307
12.3%
4 302
12.1%
1 301
12.0%
2 300
12.0%
7 165
6.6%
9 156
6.2%
8 146
5.8%
6 143
5.7%
Other Punctuation
ValueCountFrequency (%)
: 500
50.0%
. 500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
3 349
10.0%
5 331
9.5%
0 307
8.8%
4 302
8.6%
1 301
8.6%
2 300
8.6%
7 165
 
4.7%
9 156
 
4.5%
Other values (2) 289
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
3 349
10.0%
5 331
9.5%
0 307
8.8%
4 302
8.6%
1 301
8.6%
2 300
8.6%
7 165
 
4.7%
9 156
 
4.5%
Other values (2) 289
8.3%

최초처리직원번호
Real number (ℝ)

Distinct261
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5222.242
Minimum3071
Maximum6200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T04:38:30.585312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3071
5-th percentile3613
Q14950.25
median5378
Q35762.25
95-th percentile6098.25
Maximum6200
Range3129
Interquartile range (IQR)812

Descriptive statistics

Standard deviation704.69448
Coefficient of variation (CV)0.13494098
Kurtosis0.42540095
Mean5222.242
Median Absolute Deviation (MAD)391.5
Skewness-0.96186432
Sum2611121
Variance496594.3
MonotonicityNot monotonic
2023-12-13T04:38:30.827076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3620 11
 
2.2%
4561 9
 
1.8%
5074 9
 
1.8%
5684 8
 
1.6%
5495 8
 
1.6%
5076 7
 
1.4%
5190 7
 
1.4%
5040 7
 
1.4%
5173 7
 
1.4%
3590 6
 
1.2%
Other values (251) 421
84.2%
ValueCountFrequency (%)
3071 2
 
0.4%
3283 2
 
0.4%
3290 1
 
0.2%
3447 2
 
0.4%
3548 4
0.8%
3555 1
 
0.2%
3590 6
1.2%
3593 2
 
0.4%
3594 1
 
0.2%
3598 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 3
0.6%
6175 1
 
0.2%
6147 6
1.2%
6139 1
 
0.2%
6137 1
 
0.2%

Sample

상담기업개요ID신청기업고객ID상담일자기업거래구분코드상담의뢰인회사관계코드보험상담동기코드설립일자최종업종차수업종코드보험상담업종구분코드주요제품명상시직원수기업규모코드사업장주소통합ID사업장소유구분코드삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
09dnS0lOzuK9dnMMcH1t500:00.011300:00.010C10309과실049dnMMcH2HMN333:49.3561732:07.95617
19dnSZP2uAW9dmUffZf7u00:00.012700:00.010C33999소상장제049dmUffZjwbN124:18.3576324:18.35763
29dnSZdo4L89dlZByBuRc00:00.011500:00.010C22213플라스틱시트549dlZByCf93N221:52.3507614:47.45076
39dnSYI99A69cDUgAt7xX00:00.011500:00.010G46332수소수749j2WgPBcjtN317:53.2607207:20.76072
49dnSYaPBgC9dnMME92Vc00:00.011600:00.010H49301운송업 외049dnMME94cYN203:08.1562158:53.45621
59dnSX6YSQt9c1C5QIKZF00:00.011500:00.010G46599선용품749dnOrRatvmN157:56.5546457:56.55464
69dnSVUKN329dgIFHzQfj00:00.011400:00.010G46733플라스틱물질 및 합성고무 도매업049dgIFHzRPbN255:18.8499224:23.64992
79dnSXeEyzl9czWrobW9v00:00.011500:00.010C30399자동차부품1549j2WgT6TxxN254:28.8564244:33.65642
89dnSXKk8Cmaaaaadkt1J00:00.011700:00.010G46539시험장비, 계측기 등149ddYAVvmzeN152:21.9498852:21.94988
99dnJFwQWxiaaaaaauSaG00:00.023700:00.010G46621밸브2039j2WgV3gf1N242:46.8462114:10.14621
상담기업개요ID신청기업고객ID상담일자기업거래구분코드상담의뢰인회사관계코드보험상담동기코드설립일자최종업종차수업종코드보험상담업종구분코드주요제품명상시직원수기업규모코드사업장주소통합ID사업장소유구분코드삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
4909dnJOt1b4z9dnAtKZiUT00:00.011300:00.010C25929자동차 종합 수리 서비스049dnJQjHJOJN229:52.7588130:53.45881
4919dnJw5pm8y9c4l5hDC3P00:00.021500:00.010G46321가공식품449dnADwmWMNN322:39.3377305:15.43773
4929dnJRCjMxg9cRcZzySCG00:00.011100:00.010C25922표면처리549dnoyj01fZN118:44.5466818:44.54668
4939dnJRwKvOhaaaaada8qV00:00.013500:00.010C30391차량용 강관 등039de1SPZYsxN117:22.2564217:22.25642
4949dnJRqaE1jaaaaabl4JA00:00.011700:00.010G46329수산물349dmH6u1ikRN115:45.0609415:45.06094
4959dnJRoSpTB9b0KwOzdJS00:00.014700:00.010C25112스틸그레이팅, 맨홀뚜껑 등1449j2WgNZLa0N115:25.8583215:25.85832
4969dnJQ2kREgaaaaadhvzm00:00.013700:00.010C25112철구조물 제작,설치3739j2Wha8lI7N109:52.7354809:52.73548
4979dnJPLPz9g9cg2sKVN7Y00:00.011500:00.010C28114에너지 저장장치1249dnoDkETaGN209:21.4456150:32.84561
4989dnJQEGHZq9cuaIz8yUJ00:00.015500:00.010C10212냉동꽃새우 등3939dm0fnTBQNN104:03.4572304:03.45723
4999dnJPyHhvQ9cl4JzoELQ00:00.011500:00.010G46599백신 충진기 외749j2WgTXycWN303:15.1495747:18.84957