Overview

Dataset statistics

Number of variables38
Number of observations30
Missing cells14
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 KiB
Average record size in memory319.4 B

Variable types

DateTime9
Categorical16
Text8
Numeric5

Dataset

Description샘플 데이터
Author경기신용보증재단
URLhttps://www.bigdata-region.kr/#/dataset/bd63b317-d316-4e16-841f-742168ed2d76

Alerts

기준년월 has constant value ""Constant
시도명 has constant value ""Constant
순번 has constant value ""Constant
보증방법명 has constant value ""Constant
품의문서번호 is highly imbalanced (73.5%)Imbalance
자금용도명 is highly imbalanced (78.9%)Imbalance
조사일자 has 1 (3.3%) missing valuesMissing
대출금리적용일자 has 13 (43.3%) missing valuesMissing
관리번호 has unique valuesUnique
접수일자 has unique valuesUnique
주채무실행일자 has unique valuesUnique
보증기한일자 has unique valuesUnique
최초보증일자 has unique valuesUnique
보증일자 has unique valuesUnique
보증번호 has unique valuesUnique
보증잔액 has 21 (70.0%) zerosZeros
대출금리 has 13 (43.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:07:49.405188
Analysis finished2023-12-10 14:07:50.149090
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2023-04-01 00:00:00
Maximum2023-04-01 00:00:00
2023-12-10T23:07:50.208223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:50.335652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

성별코드
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
M
18 
F
12 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowM
3rd rowF
4th rowF
5th rowM

Common Values

ValueCountFrequency (%)
M 18
60.0%
F 12
40.0%

Length

2023-12-10T23:07:50.515244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:07:50.659793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 18
60.0%
f 12
40.0%

연령대코드
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
50
12 
40
9 
60
5 
30
4 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row60
2nd row50
3rd row60
4th row30
5th row50

Common Values

ValueCountFrequency (%)
50 12
40.0%
40 9
30.0%
60 5
16.7%
30 4
 
13.3%

Length

2023-12-10T23:07:50.916683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:07:51.085859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50 12
40.0%
40 9
30.0%
60 5
16.7%
30 4
 
13.3%

사업자등록번호
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:07:51.351121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters300
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

Unique28 ?
Unique (%)93.3%

Sample

1st row12722*****
2nd row12490*****
3rd row13427*****
4th row69368*****
5th row59111*****
ValueCountFrequency (%)
10815 2
 
6.7%
12722 1
 
3.3%
55851 1
 
3.3%
82514 1
 
3.3%
12514 1
 
3.3%
61030 1
 
3.3%
12381 1
 
3.3%
13426 1
 
3.3%
31210 1
 
3.3%
12744 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T23:07:51.917703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 150
50.0%
1 36
 
12.0%
2 23
 
7.7%
3 18
 
6.0%
5 14
 
4.7%
4 13
 
4.3%
0 10
 
3.3%
8 10
 
3.3%
7 10
 
3.3%
6 9
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 150
50.0%
Decimal Number 150
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 36
24.0%
2 23
15.3%
3 18
12.0%
5 14
 
9.3%
4 13
 
8.7%
0 10
 
6.7%
8 10
 
6.7%
7 10
 
6.7%
6 9
 
6.0%
9 7
 
4.7%
Other Punctuation
ValueCountFrequency (%)
* 150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 150
50.0%
1 36
 
12.0%
2 23
 
7.7%
3 18
 
6.0%
5 14
 
4.7%
4 13
 
4.3%
0 10
 
3.3%
8 10
 
3.3%
7 10
 
3.3%
6 9
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 150
50.0%
1 36
 
12.0%
2 23
 
7.7%
3 18
 
6.0%
5 14
 
4.7%
4 13
 
4.3%
0 10
 
3.3%
8 10
 
3.3%
7 10
 
3.3%
6 9
 
3.0%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 30
100.0%

Length

2023-12-10T23:07:52.125196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:07:52.286586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Text

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:07:52.548423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.0333333
Min length3

Characters and Unicode

Total characters151
Distinct characters37
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)26.7%

Sample

1st row의정부시
2nd row수원시 권선구
3rd row안산시 상록구
4th row파주시
5th row구리시
ValueCountFrequency (%)
안산시 4
 
9.1%
의정부시 3
 
6.8%
단원구 3
 
6.8%
화성시 3
 
6.8%
파주시 3
 
6.8%
고양시 3
 
6.8%
평택시 2
 
4.5%
용인시 2
 
4.5%
부천시 2
 
4.5%
구리시 2
 
4.5%
Other values (13) 17
38.6%
2023-12-10T23:07:53.142008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 31
20.5%
구 16
 
10.6%
14
 
9.3%
안 8
 
5.3%
산 6
 
4.0%
양 6
 
4.0%
부 5
 
3.3%
원 5
 
3.3%
성 4
 
2.6%
의 3
 
2.0%
Other values (27) 53
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
90.7%
Space Separator 14
 
9.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 31
22.6%
구 16
 
11.7%
안 8
 
5.8%
산 6
 
4.4%
양 6
 
4.4%
부 5
 
3.6%
원 5
 
3.6%
성 4
 
2.9%
의 3
 
2.2%
수 3
 
2.2%
Other values (26) 50
36.5%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137
90.7%
Common 14
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 31
22.6%
구 16
 
11.7%
안 8
 
5.8%
산 6
 
4.4%
양 6
 
4.4%
부 5
 
3.6%
원 5
 
3.6%
성 4
 
2.9%
의 3
 
2.2%
수 3
 
2.2%
Other values (26) 50
36.5%
Common
ValueCountFrequency (%)
14
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137
90.7%
ASCII 14
 
9.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 31
22.6%
구 16
 
11.7%
안 8
 
5.8%
산 6
 
4.4%
양 6
 
4.4%
부 5
 
3.6%
원 5
 
3.6%
성 4
 
2.9%
의 3
 
2.2%
수 3
 
2.2%
Other values (26) 50
36.5%
ASCII
ValueCountFrequency (%)
14
100.0%

행정동명
Text

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:07:53.434369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0666667
Min length2

Characters and Unicode

Total characters92
Distinct characters47
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)80.0%

Sample

1st row의정부동
2nd row오목천동
3rd row사동
4th row다율동
5th row갈매동
ValueCountFrequency (%)
고잔동 2
 
6.7%
호원동 2
 
6.7%
호계동 2
 
6.7%
신원동 1
 
3.3%
의정부동 1
 
3.3%
조리읍 1
 
3.3%
여월동 1
 
3.3%
세교동 1
 
3.3%
풍덕천동 1
 
3.3%
송산면 1
 
3.3%
Other values (17) 17
56.7%
2023-12-10T23:07:53.961948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 26
28.3%
호 4
 
4.3%
원 3
 
3.3%
읍 3
 
3.3%
정 3
 
3.3%
고 2
 
2.2%
선 2
 
2.2%
교 2
 
2.2%
면 2
 
2.2%
잔 2
 
2.2%
Other values (37) 43
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 26
28.3%
호 4
 
4.3%
원 3
 
3.3%
읍 3
 
3.3%
정 3
 
3.3%
고 2
 
2.2%
선 2
 
2.2%
교 2
 
2.2%
면 2
 
2.2%
잔 2
 
2.2%
Other values (37) 43
46.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 26
28.3%
호 4
 
4.3%
원 3
 
3.3%
읍 3
 
3.3%
정 3
 
3.3%
고 2
 
2.2%
선 2
 
2.2%
교 2
 
2.2%
면 2
 
2.2%
잔 2
 
2.2%
Other values (37) 43
46.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 26
28.3%
호 4
 
4.3%
원 3
 
3.3%
읍 3
 
3.3%
정 3
 
3.3%
고 2
 
2.2%
선 2
 
2.2%
교 2
 
2.2%
면 2
 
2.2%
잔 2
 
2.2%
Other values (37) 43
46.7%

관리번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3271992 × 108
Minimum10437
Maximum2.30021 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:07:54.180758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10437
5-th percentile19041063
Q182527533
median1.4502697 × 108
Q31.9007968 × 108
95-th percentile2.2010727 × 108
Maximum2.30021 × 108
Range2.3001057 × 108
Interquartile range (IQR)1.0755214 × 108

Descriptive statistics

Standard deviation69779953
Coefficient of variation (CV)0.52576851
Kurtosis-1.1604932
Mean1.3271992 × 108
Median Absolute Deviation (MAD)55008100
Skewness-0.3724335
Sum3.9815975 × 109
Variance4.8692419 × 1015
MonotonicityNot monotonic
2023-12-10T23:07:54.384421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
30055995 1
 
3.3%
210046833 1
 
3.3%
200120115 1
 
3.3%
170060333 1
 
3.3%
50088862 1
 
3.3%
200050451 1
 
3.3%
30056802 1
 
3.3%
90089482 1
 
3.3%
150052915 1
 
3.3%
140001023 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10437 1
3.3%
10028845 1
3.3%
30055995 1
3.3%
30056802 1
3.3%
50088862 1
3.3%
60102885 1
3.3%
70117428 1
3.3%
80025294 1
3.3%
90034250 1
3.3%
90089482 1
3.3%
ValueCountFrequency (%)
230021003 1
3.3%
220130688 1
3.3%
220078643 1
3.3%
210046833 1
3.3%
200120115 1
3.3%
200056079 1
3.3%
200050451 1
3.3%
190083654 1
3.3%
190067750 1
3.3%
190041537 1
3.3%

품의문서번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
28 
9
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
1 28
93.3%
9 1
 
3.3%
2 1
 
3.3%

Length

2023-12-10T23:07:55.063356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:07:55.335593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 28
93.3%
9 1
 
3.3%
2 1
 
3.3%

순번
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
30 

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 30
100.0%

Length

2023-12-10T23:07:55.635104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:07:55.787803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 30
100.0%

품의일자
Date

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2000-11-10 00:00:00
Maximum2023-03-08 00:00:00
2023-12-10T23:07:55.936950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:56.140870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

조사일자
Date

MISSING 

Distinct29
Distinct (%)100.0%
Missing1
Missing (%)3.3%
Memory size372.0 B
Minimum2000-11-04 00:00:00
Maximum2023-02-23 00:00:00
2023-12-10T23:07:56.327988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:56.596015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

접수일자
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2000-10-05 00:00:00
Maximum2023-02-23 00:00:00
2023-12-10T23:07:56.804948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:57.003260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

보증금액
Real number (ℝ)

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24916667
Minimum5000000
Maximum1.7 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:07:57.203038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5000000
5-th percentile6575000
Q110000000
median20000000
Q326775000
95-th percentile47750000
Maximum1.7 × 108
Range1.65 × 108
Interquartile range (IQR)16775000

Descriptive statistics

Standard deviation29408140
Coefficient of variation (CV)1.1802598
Kurtosis21.864377
Mean24916667
Median Absolute Deviation (MAD)10000000
Skewness4.4071166
Sum7.475 × 108
Variance8.6483868 × 1014
MonotonicityNot monotonic
2023-12-10T23:07:57.379633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
20000000 6
20.0%
10000000 5
16.7%
30000000 4
13.3%
17000000 3
10.0%
25500000 2
 
6.7%
5000000 2
 
6.7%
8500000 2
 
6.7%
27200000 1
 
3.3%
50000000 1
 
3.3%
170000000 1
 
3.3%
Other values (3) 3
10.0%
ValueCountFrequency (%)
5000000 2
 
6.7%
8500000 2
 
6.7%
10000000 5
16.7%
15000000 1
 
3.3%
17000000 3
10.0%
20000000 6
20.0%
21300000 1
 
3.3%
25500000 2
 
6.7%
27200000 1
 
3.3%
30000000 4
13.3%
ValueCountFrequency (%)
170000000 1
 
3.3%
50000000 1
 
3.3%
45000000 1
 
3.3%
30000000 4
13.3%
27200000 1
 
3.3%
25500000 2
 
6.7%
21300000 1
 
3.3%
20000000 6
20.0%
17000000 3
10.0%
15000000 1
 
3.3%

주채무실행일자
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2000-11-25 00:00:00
Maximum2023-03-10 00:00:00
2023-12-10T23:07:57.573234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:57.764065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

주채무실행금액
Real number (ℝ)

Distinct9
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27066667
Minimum5000000
Maximum2 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:07:57.956866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5000000
5-th percentile7250000
Q110000000
median20000000
Q330000000
95-th percentile50000000
Maximum2 × 108
Range1.95 × 108
Interquartile range (IQR)20000000

Descriptive statistics

Standard deviation34564216
Coefficient of variation (CV)1.2770031
Kurtosis23.293202
Mean27066667
Median Absolute Deviation (MAD)10000000
Skewness4.5942748
Sum8.12 × 108
Variance1.1946851 × 1015
MonotonicityNot monotonic
2023-12-10T23:07:58.134321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
20000000 9
30.0%
10000000 7
23.3%
30000000 6
20.0%
50000000 2
 
6.7%
5000000 2
 
6.7%
32000000 1
 
3.3%
200000000 1
 
3.3%
25000000 1
 
3.3%
15000000 1
 
3.3%
ValueCountFrequency (%)
5000000 2
 
6.7%
10000000 7
23.3%
15000000 1
 
3.3%
20000000 9
30.0%
25000000 1
 
3.3%
30000000 6
20.0%
32000000 1
 
3.3%
50000000 2
 
6.7%
200000000 1
 
3.3%
ValueCountFrequency (%)
200000000 1
 
3.3%
50000000 2
 
6.7%
32000000 1
 
3.3%
30000000 6
20.0%
25000000 1
 
3.3%
20000000 9
30.0%
15000000 1
 
3.3%
10000000 7
23.3%
5000000 2
 
6.7%

보증잔액
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4302516.1
Minimum0
Maximum30000000
Zeros21
Zeros (%)70.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:07:58.377030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37192721
95-th percentile18987500
Maximum30000000
Range30000000
Interquartile range (IQR)7192721

Descriptive statistics

Standard deviation7885953
Coefficient of variation (CV)1.8328701
Kurtosis2.8671846
Mean4302516.1
Median Absolute Deviation (MAD)0
Skewness1.8479112
Sum1.2907548 × 108
Variance6.2188255 × 1013
MonotonicityNot monotonic
2023-12-10T23:07:58.738590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 21
70.0%
10000000 1
 
3.3%
9000000 1
 
3.3%
11046599 1
 
3.3%
30000000 1
 
3.3%
1770884 1
 
3.3%
13700000 1
 
3.3%
17750000 1
 
3.3%
15808000 1
 
3.3%
20000000 1
 
3.3%
ValueCountFrequency (%)
0 21
70.0%
1770884 1
 
3.3%
9000000 1
 
3.3%
10000000 1
 
3.3%
11046599 1
 
3.3%
13700000 1
 
3.3%
15808000 1
 
3.3%
17750000 1
 
3.3%
20000000 1
 
3.3%
30000000 1
 
3.3%
ValueCountFrequency (%)
30000000 1
 
3.3%
20000000 1
 
3.3%
17750000 1
 
3.3%
15808000 1
 
3.3%
13700000 1
 
3.3%
11046599 1
 
3.3%
10000000 1
 
3.3%
9000000 1
 
3.3%
1770884 1
 
3.3%
0 21
70.0%

보증기한일자
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2004-11-20 00:00:00
Maximum2028-03-10 00:00:00
2023-12-10T23:07:58.963567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:59.205686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

업종코드
Text

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:07:59.499779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters180
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

Unique20 ?
Unique (%)66.7%

Sample

1st rowR91222
2nd rowP85501
3rd rowI56111
4th rowS96113
5th rowN75999
ValueCountFrequency (%)
i56111 4
 
13.3%
c15121 2
 
6.7%
r91222 2
 
6.7%
g47911 2
 
6.7%
i56193 1
 
3.3%
c25999 1
 
3.3%
g45120 1
 
3.3%
c26410 1
 
3.3%
g47993 1
 
3.3%
h49301 1
 
3.3%
Other values (14) 14
46.7%
2023-12-10T23:07:59.995779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 41
22.8%
9 24
13.3%
2 21
11.7%
5 17
9.4%
6 14
 
7.8%
3 8
 
4.4%
4 8
 
4.4%
0 7
 
3.9%
I 7
 
3.9%
7 7
 
3.9%
Other values (9) 26
14.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150
83.3%
Uppercase Letter 30
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 41
27.3%
9 24
16.0%
2 21
14.0%
5 17
11.3%
6 14
 
9.3%
3 8
 
5.3%
4 8
 
5.3%
0 7
 
4.7%
7 7
 
4.7%
8 3
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
I 7
23.3%
C 6
20.0%
G 5
16.7%
P 3
10.0%
S 3
10.0%
R 2
 
6.7%
M 2
 
6.7%
N 1
 
3.3%
H 1
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 150
83.3%
Latin 30
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 41
27.3%
9 24
16.0%
2 21
14.0%
5 17
11.3%
6 14
 
9.3%
3 8
 
5.3%
4 8
 
5.3%
0 7
 
4.7%
7 7
 
4.7%
8 3
 
2.0%
Latin
ValueCountFrequency (%)
I 7
23.3%
C 6
20.0%
G 5
16.7%
P 3
10.0%
S 3
10.0%
R 2
 
6.7%
M 2
 
6.7%
N 1
 
3.3%
H 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 41
22.8%
9 24
13.3%
2 21
11.7%
5 17
9.4%
6 14
 
7.8%
3 8
 
4.4%
4 8
 
4.4%
0 7
 
3.9%
I 7
 
3.9%
7 7
 
3.9%
Other values (9) 26
14.4%

업종대분류명
Categorical

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
I숙박및음식점업(55~56)
7 
C제조업(10~33)
5 
G도매및소매업(45~47)
4 
R예술;스포츠및여가관련서비스업(90~91)
3 
P교육서비스업(85)
3 
Other values (6)
8 

Length

Max length25
Median length23
Mean length16.1
Min length11

Unique

Unique5 ?
Unique (%)16.7%

Sample

1st rowR예술;스포츠및여가관련서비스업(90~91)
2nd rowP교육서비스업(85)
3rd rowI숙박및음식점업(55~56)
4th rowS협회및단체;수리및기타개인서비스업(94~96)
5th rowN사업시설관리및사업지원서비스업(74~76)

Common Values

ValueCountFrequency (%)
I숙박및음식점업(55~56) 7
23.3%
C제조업(10~33) 5
16.7%
G도매및소매업(45~47) 4
13.3%
R예술;스포츠및여가관련서비스업(90~91) 3
10.0%
P교육서비스업(85) 3
10.0%
S협회및단체;수리및기타개인서비스업(94~96) 3
10.0%
N사업시설관리및사업지원서비스업(74~76) 1
 
3.3%
M전문;과학및기술서비스업(70~73) 1
 
3.3%
J출판;영상;방송통신및정보서비스업(58~63) 1
 
3.3%
C제조업(10~34) 1
 
3.3%

Length

2023-12-10T23:08:00.258126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
i숙박및음식점업(55~56 7
23.3%
c제조업(10~33 5
16.7%
g도매및소매업(45~47 4
13.3%
r예술;스포츠및여가관련서비스업(90~91 3
10.0%
p교육서비스업(85 3
10.0%
s협회및단체;수리및기타개인서비스업(94~96 3
10.0%
n사업시설관리및사업지원서비스업(74~76 1
 
3.3%
m전문;과학및기술서비스업(70~73 1
 
3.3%
j출판;영상;방송통신및정보서비스업(58~63 1
 
3.3%
c제조업(10~34 1
 
3.3%

업종중분류명
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:08:00.569613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length8.7
Min length4

Characters and Unicode

Total characters261
Distinct characters83
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)63.3%

Sample

1st row유원지및기타오락관련서비스업
2nd row기타교육기관
3rd row음식점업
4th row미용;욕탕및유사서비스업
5th row기타사업지원서비스업
ValueCountFrequency (%)
음식점업 5
 
16.7%
기타교육기관 2
 
6.7%
미용;욕탕및유사서비스업 2
 
6.7%
가죽;가방및유사제품제조업 2
 
6.7%
창작;예술및여가관련서비스업 1
 
3.3%
유원지및기타오락관련서비스업 1
 
3.3%
무점포소매업 1
 
3.3%
도매및상품중개업 1
 
3.3%
자동차판매업 1
 
3.3%
음식점및주점업 1
 
3.3%
Other values (13) 13
43.3%
2023-12-10T23:08:01.129784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 28
 
10.7%
및 14
 
5.4%
제 11
 
4.2%
점 10
 
3.8%
비 10
 
3.8%
기 9
 
3.4%
음 8
 
3.1%
스 8
 
3.1%
서 7
 
2.7%
; 7
 
2.7%
Other values (73) 149
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 254
97.3%
Other Punctuation 7
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 28
 
11.0%
및 14
 
5.5%
제 11
 
4.3%
점 10
 
3.9%
비 10
 
3.9%
기 9
 
3.5%
음 8
 
3.1%
스 8
 
3.1%
서 7
 
2.8%
가 7
 
2.8%
Other values (72) 142
55.9%
Other Punctuation
ValueCountFrequency (%)
; 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 254
97.3%
Common 7
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 28
 
11.0%
및 14
 
5.5%
제 11
 
4.3%
점 10
 
3.9%
비 10
 
3.9%
기 9
 
3.5%
음 8
 
3.1%
스 8
 
3.1%
서 7
 
2.8%
가 7
 
2.8%
Other values (72) 142
55.9%
Common
ValueCountFrequency (%)
; 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 254
97.3%
ASCII 7
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 28
 
11.0%
및 14
 
5.5%
제 11
 
4.3%
점 10
 
3.9%
비 10
 
3.9%
기 9
 
3.5%
음 8
 
3.1%
스 8
 
3.1%
서 7
 
2.8%
가 7
 
2.8%
Other values (72) 142
55.9%
ASCII
ValueCountFrequency (%)
; 7
100.0%

자금종류대분류명
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
일반자금
17 
정부자금
9 
경기도자금
4 

Length

Max length5
Median length4
Mean length4.1333333
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정부자금
2nd row일반자금
3rd row일반자금
4th row경기도자금
5th row일반자금

Common Values

ValueCountFrequency (%)
일반자금 17
56.7%
정부자금 9
30.0%
경기도자금 4
 
13.3%

Length

2023-12-10T23:08:01.341337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:08:01.504025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반자금 17
56.7%
정부자금 9
30.0%
경기도자금 4
 
13.3%

자금종류중분류명
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
소상공인지원자금
19 
소상공인일반자금
6 
소진공 경영안정자금(일반)
2 
가계자금
 
1
특별경영자금
 
1

Length

Max length15
Median length8
Mean length8.4333333
Min length4

Unique

Unique3 ?
Unique (%)10.0%

Sample

1st row소상공인일반자금
2nd row소상공인지원자금
3rd row소상공인지원자금
4th row소상공인지원자금
5th row소상공인지원자금

Common Values

ValueCountFrequency (%)
소상공인지원자금 19
63.3%
소상공인일반자금 6
 
20.0%
소진공 경영안정자금(일반) 2
 
6.7%
가계자금 1
 
3.3%
특별경영자금 1
 
3.3%
소상공인경영안정자금(코로나) 1
 
3.3%

Length

2023-12-10T23:08:01.669708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:08:01.890035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소상공인지원자금 19
59.4%
소상공인일반자금 6
 
18.8%
소진공 2
 
6.2%
경영안정자금(일반 2
 
6.2%
가계자금 1
 
3.1%
특별경영자금 1
 
3.1%
소상공인경영안정자금(코로나 1
 
3.1%

자금용도명
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
운전
29 
가계
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
운전 29
96.7%
가계 1
 
3.3%

Length

2023-12-10T23:08:02.132733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:08:02.306427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운전 29
96.7%
가계 1
 
3.3%

보증종류명
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
대출보증
20 
비은행대출보증
10 

Length

Max length7
Median length4
Mean length5
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대출보증
2nd row대출보증
3rd row비은행대출보증
4th row대출보증
5th row대출보증

Common Values

ValueCountFrequency (%)
대출보증 20
66.7%
비은행대출보증 10
33.3%

Length

2023-12-10T23:08:02.513026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:08:02.663608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대출보증 20
66.7%
비은행대출보증 10
33.3%

보증방법명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
개별보증
30 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개별보증 30
100.0%

Length

2023-12-10T23:08:02.810781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:08:02.949698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개별보증 30
100.0%

은행명
Categorical

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
농협은행
7 
국민은행
6 
중소기업은행
5 
우리은행
4 
신한은행
3 
Other values (3)
5 

Length

Max length6
Median length4
Mean length4.4333333
Min length4

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row우리은행
2nd row중소기업은행
3rd row농협은행
4th row신한은행
5th row중소기업은행

Common Values

ValueCountFrequency (%)
농협은행 7
23.3%
국민은행 6
20.0%
중소기업은행 5
16.7%
우리은행 4
13.3%
신한은행 3
10.0%
새마을금고 3
10.0%
하나은행 1
 
3.3%
산업은행 1
 
3.3%

Length

2023-12-10T23:08:03.145769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:08:03.374712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농협은행 7
23.3%
국민은행 6
20.0%
중소기업은행 5
16.7%
우리은행 4
13.3%
신한은행 3
10.0%
새마을금고 3
10.0%
하나은행 1
 
3.3%
산업은행 1
 
3.3%

대출과목명
Text

Distinct19
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:08:03.708307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length13
Mean length9.1333333
Min length6

Characters and Unicode

Total characters274
Distinct characters53
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)43.3%

Sample

1st row기운)재정중소기업자금대출
2nd row중소기업자금대출
3rd row일반자금대출
4th row<기운>일반자금대출(분할상환)경기도이차보전(소상공
5th row중소기업자금대출
ValueCountFrequency (%)
일반자금대출 4
13.3%
중소기업자금대출 4
13.3%
기타재정자금대출 3
 
10.0%
일반운전자금 2
 
6.7%
기업일반운전자금대출 2
 
6.7%
진흥기금자금대출 2
 
6.7%
기운)일반자금대출 1
 
3.3%
기운)재정중소기업자금대출 1
 
3.3%
기운)재정중소기업자 1
 
3.3%
정책운영자금대출 1
 
3.3%
Other values (9) 9
30.0%
2023-12-10T23:08:04.303986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 29
 
10.6%
자 27
 
9.9%
대 25
 
9.1%
출 25
 
9.1%
기 22
 
8.0%
일 13
 
4.7%
운 13
 
4.7%
반 13
 
4.7%
업 11
 
4.0%
소 9
 
3.3%
Other values (43) 87
31.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 263
96.0%
Close Punctuation 6
 
2.2%
Open Punctuation 3
 
1.1%
Math Symbol 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 29
 
11.0%
자 27
 
10.3%
대 25
 
9.5%
출 25
 
9.5%
기 22
 
8.4%
일 13
 
4.9%
운 13
 
4.9%
반 13
 
4.9%
업 11
 
4.2%
소 9
 
3.4%
Other values (39) 76
28.9%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 263
96.0%
Common 11
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 29
 
11.0%
자 27
 
10.3%
대 25
 
9.5%
출 25
 
9.5%
기 22
 
8.4%
일 13
 
4.9%
운 13
 
4.9%
반 13
 
4.9%
업 11
 
4.2%
소 9
 
3.4%
Other values (39) 76
28.9%
Common
ValueCountFrequency (%)
) 6
54.5%
( 3
27.3%
> 1
 
9.1%
< 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 263
96.0%
ASCII 11
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 29
 
11.0%
자 27
 
10.3%
대 25
 
9.5%
출 25
 
9.5%
기 22
 
8.4%
일 13
 
4.9%
운 13
 
4.9%
반 13
 
4.9%
업 11
 
4.2%
소 9
 
3.4%
Other values (39) 76
28.9%
ASCII
ValueCountFrequency (%)
) 6
54.5%
( 3
27.3%
> 1
 
9.1%
< 1
 
9.1%

상환방법명
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
분할상환
25 
만기일시 상환
5 

Length

Max length7
Median length4
Mean length4.5
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분할상환 25
83.3%
만기일시 상환 5
 
16.7%

Length

2023-12-10T23:08:04.586365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:08:04.898734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분할상환 25
71.4%
만기일시 5
 
14.3%
상환 5
 
14.3%

거치기간년수
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
12
22 
24
4 
36
 
2
0
 
1
1
 
1

Length

Max length2
Median length2
Mean length1.9333333
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
12 22
73.3%
24 4
 
13.3%
36 2
 
6.7%
0 1
 
3.3%
1 1
 
3.3%

Length

2023-12-10T23:08:05.276017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:08:05.537714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12 22
73.3%
24 4
 
13.3%
36 2
 
6.7%
0 1
 
3.3%
1 1
 
3.3%

상환기간년수
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
48
16 
36
8 
0
5 
35
 
1

Length

Max length2
Median length2
Mean length1.8333333
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row48
2nd row36
3rd row48
4th row48
5th row48

Common Values

ValueCountFrequency (%)
48 16
53.3%
36 8
26.7%
0 5
 
16.7%
35 1
 
3.3%

Length

2023-12-10T23:08:05.889264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:08:06.082313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48 16
53.3%
36 8
26.7%
0 5
 
16.7%
35 1
 
3.3%

상환주기년수
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
16 
3
11 
0
2 
12
 
1

Length

Max length2
Median length1
Mean length1.0333333
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
1 16
53.3%
3 11
36.7%
0 2
 
6.7%
12 1
 
3.3%

Length

2023-12-10T23:08:06.315396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:08:06.574310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 16
53.3%
3 11
36.7%
0 2
 
6.7%
12 1
 
3.3%

최초보증일자
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2000-11-13 00:00:00
Maximum2023-03-10 00:00:00
2023-12-10T23:08:06.832259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:08:07.105900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

보증일자
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2000-11-13 00:00:00
Maximum2023-03-10 00:00:00
2023-12-10T23:08:07.416452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:08:07.715028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

대출금리적용일자
Date

MISSING 

Distinct17
Distinct (%)100.0%
Missing13
Missing (%)43.3%
Memory size372.0 B
Minimum2013-01-11 00:00:00
Maximum2023-03-10 00:00:00
2023-12-10T23:08:07.943003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:08:08.179995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

대출금리
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8526667
Minimum0
Maximum4.34
Zeros13
Zeros (%)43.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:08:08.386788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.61
Q33.835
95-th percentile4.2715
Maximum4.34
Range4.34
Interquartile range (IQR)3.835

Descriptive statistics

Standard deviation1.8269174
Coefficient of variation (CV)0.9861015
Kurtosis-1.8065759
Mean1.8526667
Median Absolute Deviation (MAD)1.61
Skewness0.18109723
Sum55.58
Variance3.3376271
MonotonicityNot monotonic
2023-12-10T23:08:08.966873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 13
43.3%
1.5 2
 
6.7%
4.2 1
 
3.3%
3.75 1
 
3.3%
2.6 1
 
3.3%
4.09 1
 
3.3%
4.33 1
 
3.3%
2.22 1
 
3.3%
4.04 1
 
3.3%
3.85 1
 
3.3%
Other values (7) 7
23.3%
ValueCountFrequency (%)
0.0 13
43.3%
1.5 2
 
6.7%
1.72 1
 
3.3%
2.07 1
 
3.3%
2.22 1
 
3.3%
2.6 1
 
3.3%
3.6 1
 
3.3%
3.75 1
 
3.3%
3.79 1
 
3.3%
3.85 1
 
3.3%
ValueCountFrequency (%)
4.34 1
3.3%
4.33 1
3.3%
4.2 1
3.3%
4.09 1
3.3%
4.05 1
3.3%
4.04 1
3.3%
3.93 1
3.3%
3.85 1
3.3%
3.79 1
3.3%
3.75 1
3.3%

기업번호
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:08:09.338298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters720
Distinct characters65
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)93.3%

Sample

1st row++FPHcFoUeV8h0DBqO75ww==
2nd row++TSchB8FSQqvLrlDN4Cxg==
3rd row++fKBa+8Dlldzgn2SeCULA==
4th row++gMCu8nLgaavRaZ6EqjDg==
5th row++j3ohFoThG54ra6W6LUxQ==
ValueCountFrequency (%)
0/grdb1nmbiaidwsyutwa 2
 
6.7%
fphcfouev8h0dbqo75ww 1
 
3.3%
0pvjqfmlz1zhbltrcigdg 1
 
3.3%
2vqhec/y0kcvgcu9rtx2g 1
 
3.3%
2sjnss4yv6eq14xzepwiw 1
 
3.3%
2jj1hu8qky1w0auw/1v5w 1
 
3.3%
2hm2enky/avlmwaqvkwqq 1
 
3.3%
2wfl7od9vsd1wvfuvv2kq 1
 
3.3%
2vzxcxxw2g71vqx4njacq 1
 
3.3%
2vb5m9r9p4kjk30xprz9g 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T23:08:09.964007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
= 60
 
8.3%
+ 42
 
5.8%
g 22
 
3.1%
w 18
 
2.5%
Q 18
 
2.5%
2 18
 
2.5%
a 17
 
2.4%
0 15
 
2.1%
q 15
 
2.1%
1 15
 
2.1%
Other values (55) 480
66.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 264
36.7%
Uppercase Letter 237
32.9%
Decimal Number 103
 
14.3%
Math Symbol 102
 
14.2%
Other Punctuation 14
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
g 22
 
8.3%
w 18
 
6.8%
a 17
 
6.4%
q 15
 
5.7%
s 14
 
5.3%
j 12
 
4.5%
c 12
 
4.5%
v 12
 
4.5%
h 10
 
3.8%
k 10
 
3.8%
Other values (16) 122
46.2%
Uppercase Letter
ValueCountFrequency (%)
Q 18
 
7.6%
W 14
 
5.9%
A 14
 
5.9%
L 12
 
5.1%
V 12
 
5.1%
P 11
 
4.6%
K 11
 
4.6%
R 10
 
4.2%
Z 10
 
4.2%
D 9
 
3.8%
Other values (16) 116
48.9%
Decimal Number
ValueCountFrequency (%)
2 18
17.5%
0 15
14.6%
1 15
14.6%
3 10
9.7%
9 9
8.7%
8 8
7.8%
6 8
7.8%
7 7
 
6.8%
4 7
 
6.8%
5 6
 
5.8%
Math Symbol
ValueCountFrequency (%)
= 60
58.8%
+ 42
41.2%
Other Punctuation
ValueCountFrequency (%)
/ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 501
69.6%
Common 219
30.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
g 22
 
4.4%
w 18
 
3.6%
Q 18
 
3.6%
a 17
 
3.4%
q 15
 
3.0%
W 14
 
2.8%
s 14
 
2.8%
A 14
 
2.8%
j 12
 
2.4%
c 12
 
2.4%
Other values (42) 345
68.9%
Common
ValueCountFrequency (%)
= 60
27.4%
+ 42
19.2%
2 18
 
8.2%
0 15
 
6.8%
1 15
 
6.8%
/ 14
 
6.4%
3 10
 
4.6%
9 9
 
4.1%
8 8
 
3.7%
6 8
 
3.7%
Other values (3) 20
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
= 60
 
8.3%
+ 42
 
5.8%
g 22
 
3.1%
w 18
 
2.5%
Q 18
 
2.5%
2 18
 
2.5%
a 17
 
2.4%
0 15
 
2.1%
q 15
 
2.1%
1 15
 
2.1%
Other values (55) 480
66.7%

보증번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:08:10.336589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters720
Distinct characters65
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st rowN+auz5t5MmRHQ0hz9GALcw==
2nd rowTyznfBoM9sYsksxoWJ9d/g==
3rd rowuMzQS+KMn0eRqjNRjLsYBw==
4th rowT67a4c0+fSYFKENUrWUhuw==
5th row9WLAJy4EiONIT6A9UynGdg==
ValueCountFrequency (%)
n+auz5t5mmrhq0hz9galcw 1
 
3.3%
tyznfbom9sysksxowj9d/g 1
 
3.3%
kawvkihmyp/f2oqjhhe9iw 1
 
3.3%
lhu8t3l9zbxununlzpzpaa 1
 
3.3%
wp+ggk3p7byeqashwxwzvg 1
 
3.3%
m2ypa3opn1sytrx2z7b5ba 1
 
3.3%
vkoes+/j63xeoz9rqbslva 1
 
3.3%
sj0hx5prg8cdsdfigqswlq 1
 
3.3%
onscytz3344zekpz+fuqa 1
 
3.3%
ok3e2wxyw/bjpighs6ksyg 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:08:10.901345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
= 60
 
8.3%
A 20
 
2.8%
S 17
 
2.4%
g 17
 
2.4%
+ 16
 
2.2%
z 15
 
2.1%
J 14
 
1.9%
9 14
 
1.9%
y 14
 
1.9%
w 14
 
1.9%
Other values (55) 519
72.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 284
39.4%
Lowercase Letter 256
35.6%
Decimal Number 95
 
13.2%
Math Symbol 76
 
10.6%
Other Punctuation 9
 
1.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 20
 
7.0%
S 17
 
6.0%
J 14
 
4.9%
Y 13
 
4.6%
N 13
 
4.6%
M 13
 
4.6%
V 11
 
3.9%
X 11
 
3.9%
K 11
 
3.9%
I 11
 
3.9%
Other values (16) 150
52.8%
Lowercase Letter
ValueCountFrequency (%)
g 17
 
6.6%
z 15
 
5.9%
y 14
 
5.5%
w 14
 
5.5%
h 12
 
4.7%
u 12
 
4.7%
e 11
 
4.3%
s 11
 
4.3%
q 11
 
4.3%
x 11
 
4.3%
Other values (16) 128
50.0%
Decimal Number
ValueCountFrequency (%)
9 14
14.7%
7 12
12.6%
4 11
11.6%
3 11
11.6%
8 10
10.5%
2 8
8.4%
0 8
8.4%
6 8
8.4%
5 8
8.4%
1 5
 
5.3%
Math Symbol
ValueCountFrequency (%)
= 60
78.9%
+ 16
 
21.1%
Other Punctuation
ValueCountFrequency (%)
/ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 540
75.0%
Common 180
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 20
 
3.7%
S 17
 
3.1%
g 17
 
3.1%
z 15
 
2.8%
J 14
 
2.6%
y 14
 
2.6%
w 14
 
2.6%
Y 13
 
2.4%
N 13
 
2.4%
M 13
 
2.4%
Other values (42) 390
72.2%
Common
ValueCountFrequency (%)
= 60
33.3%
+ 16
 
8.9%
9 14
 
7.8%
7 12
 
6.7%
4 11
 
6.1%
3 11
 
6.1%
8 10
 
5.6%
/ 9
 
5.0%
2 8
 
4.4%
0 8
 
4.4%
Other values (3) 21
 
11.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
= 60
 
8.3%
A 20
 
2.8%
S 17
 
2.4%
g 17
 
2.4%
+ 16
 
2.2%
z 15
 
2.1%
J 14
 
1.9%
9 14
 
1.9%
y 14
 
1.9%
w 14
 
1.9%
Other values (55) 519
72.1%

Sample

기준년월성별코드연령대코드사업자등록번호시도명시군구명행정동명관리번호품의문서번호순번품의일자조사일자접수일자보증금액주채무실행일자주채무실행금액보증잔액보증기한일자업종코드업종대분류명업종중분류명자금종류대분류명자금종류중분류명자금용도명보증종류명보증방법명은행명대출과목명상환방법명거치기간년수상환기간년수상환주기년수최초보증일자보증일자대출금리적용일자대출금리기업번호보증번호
02023-04M6012722*****경기도의정부시의정부동30055995112003-05-262003-05-262003-05-15170000002003-05-272000000002008-05-20R91222R예술;스포츠및여가관련서비스업(90~91)유원지및기타오락관련서비스업정부자금소상공인일반자금운전대출보증개별보증우리은행기운)재정중소기업자금대출분할상환124832003-05-272003-05-27<NA>0.0++FPHcFoUeV8h0DBqO75ww==N+auz5t5MmRHQ0hz9GALcw==
12023-04M5012490*****경기도수원시 권선구오목천동10028845112001-11-262001-11-232001-11-14272000002001-11-273200000002005-11-27P85501P교육서비스업(85)기타교육기관일반자금소상공인지원자금운전대출보증개별보증중소기업은행중소기업자금대출분할상환123632001-11-272001-11-27<NA>0.0++TSchB8FSQqvLrlDN4Cxg==TyznfBoM9sYsksxoWJ9d/g==
22023-04F6013427*****경기도안산시 상록구사동100013590112010-04-052010-04-012010-04-01200000002010-04-062000000002015-04-05I56111I숙박및음식점업(55~56)음식점업일반자금소상공인지원자금운전비은행대출보증개별보증농협은행일반자금대출분할상환124812010-04-062010-04-06<NA>0.0++fKBa+8Dlldzgn2SeCULA==uMzQS+KMn0eRqjNRjLsYBw==
32023-04F3069368*****경기도파주시다율동230021003112023-03-082023-02-232023-02-23100000002023-03-1010000000100000002028-03-10S96113S협회및단체;수리및기타개인서비스업(94~96)미용;욕탕및유사서비스업경기도자금소상공인지원자금운전대출보증개별보증신한은행<기운>일반자금대출(분할상환)경기도이차보전(소상공분할상환124812023-03-102023-03-102023-03-104.05++gMCu8nLgaavRaZ6EqjDg==T67a4c0+fSYFKENUrWUhuw==
42023-04M5059111*****경기도구리시갈매동220078643112022-05-042022-05-042022-05-04100000002022-05-041000000090000002027-05-04N75999N사업시설관리및사업지원서비스업(74~76)기타사업지원서비스업일반자금소상공인지원자금운전대출보증개별보증중소기업은행중소기업자금대출분할상환124812022-05-042022-05-042022-05-041.72++j3ohFoThG54ra6W6LUxQ==9WLAJy4EiONIT6A9UynGdg==
52023-04M5067748*****경기도안산시 단원구고잔동190083654112019-12-112019-11-192019-11-04170000002019-12-1720000000110465992024-12-17I56213I숙박및음식점업(55~56)주점및비알콜음료점업정부자금소진공 경영안정자금(일반)운전대출보증개별보증신한은행기운)소상공인시장진분할상환243632019-12-172019-12-172019-12-172.07++qasp8CjWMLSrBwiaRV9Q==T7pKNhI6lICVet0lIIyYgQ==
62023-04M5012934*****경기도성남시 분당구수내동180031284112018-06-212018-06-192018-06-07500000002018-06-215000000002023-06-20M71201M전문;과학및기술서비스업(70~73)회계및세무관련서비스업일반자금소상공인지원자금운전비은행대출보증개별보증농협은행일반자금대출분할상환124812018-06-212018-06-212018-06-213.93+/13m2JeqI2Kl8gN97ecIg==lWx+8whxw9BXREy+7xKD6g==
72023-04F4013425*****경기도안산시 단원구선부동100018496112010-05-032010-05-022010-05-02200000002010-05-042000000002015-05-04C26299C제조업(10~33)전자부품제조업일반자금소상공인지원자금운전비은행대출보증개별보증농협은행일반자금대출분할상환124812010-05-042010-05-04<NA>0.0+/2aLlf6qxe0Ksgpt3ujKQ==SCJb4O+7nVuHiWVb2ccqoA==
82023-04F5013092*****경기도부천시오정동200056079112020-04-162020-04-142020-03-16100000002020-05-251000000002023-05-25P85699P교육서비스업(85)기타교육기관일반자금소상공인지원자금운전대출보증개별보증하나은행기업일반자금대출만기일시 상환36002020-05-252020-05-252020-05-251.5+/XWIWuGLwAp5mqkykOBhQ==mmIQHsMN+m4Tk6JOJ2PxRA==
92023-04F4067926*****경기도수원시 권선구권선동130000332112013-01-092013-01-082013-01-04170000002013-01-112000000002018-01-19G47416J출판;영상;방송통신및정보서비스업(58~63)오디오물출판및원판녹음업정부자금소상공인일반자금운전비은행대출보증개별보증농협은행기타재정운전자금대출분할상환243632013-01-112013-01-112013-01-113.79+/ZRbA3lBUAdjgy1DUS7KQ==5z7j89iAMveu5mIpBHXnDw==
기준년월성별코드연령대코드사업자등록번호시도명시군구명행정동명관리번호품의문서번호순번품의일자조사일자접수일자보증금액주채무실행일자주채무실행금액보증잔액보증기한일자업종코드업종대분류명업종중분류명자금종류대분류명자금종류중분류명자금용도명보증종류명보증방법명은행명대출과목명상환방법명거치기간년수상환기간년수상환주기년수최초보증일자보증일자대출금리적용일자대출금리기업번호보증번호
202023-04F4025821*****경기도화성시향남읍190067750112019-09-252019-09-182019-09-06300000002019-10-0230000000177500002024-10-02G47911G도매및소매업(45~47)무점포소매업정부자금소진공 경영안정자금(일반)운전대출보증개별보증중소기업은행진흥기금자금대출분할상환243632019-10-022019-10-022019-10-022.22+1zskz7bK66m0BsOAy+Y/A==+6CyqVMZSAtPMzCh9udzBQ==
212023-04F5013490*****경기도시흥시정왕동10437212000-11-102000-11-042000-10-05213000002000-11-252500000002004-11-20P85632P교육서비스업(85)일반교습학원정부자금소상공인일반자금운전대출보증개별보증국민은행중소기업자금대출분할상환123612000-11-132000-11-13<NA>0.0+2FeYtHJI4Q9Mz/cgJwcSg==Ok3E2WXYw/bJPiGHS6kSYg==
222023-04F4012744*****경기도파주시와동동140001023112014-01-132014-01-132014-01-13300000002014-01-223000000002019-01-14M73301R예술;스포츠및여가관련서비스업(90~91)창작;예술및여가관련서비스업일반자금소상공인지원자금운전대출보증개별보증산업은행소호운영자금대출분할상환124832014-01-152014-01-152014-01-224.33+2Vb5M9R9P4kjk30XPRZ9g==+OnSCYTz3344zekpz+FUqA==
232023-04M6031210*****경기도화성시송산면150052915112015-10-132015-10-122015-10-0585000002015-10-201000000002020-10-20H49301H운수업(49~52)도로화물운송업일반자금소상공인지원자금운전대출보증개별보증신한은행기운)일반자금대출분할상환124812015-10-202015-10-202015-10-204.09+2VzxcxXW2G71VqX4nJAcQ==sJ0Hx5pRg8cDsdFIgqSWlQ==
242023-04F4013426*****경기도안산시 단원구고잔동90089482112009-11-162009-11-122009-11-12150000002009-11-171500000002012-11-15G47993S협회및단체;수리및기타개인서비스업(94~96)미용;욕탕및유사서비스업일반자금소상공인지원자금운전비은행대출보증개별보증새마을금고정책운영자금대출만기일시 상환36012009-11-172009-11-17<NA>0.0+2WFL7od9vsd1wvfuvV2kQ==vkoES+/J63xeoz9RqbSLvA==
252023-04M6012381*****경기도안양시 동안구호계동30056802112003-07-082003-07-042003-05-19255000002003-07-143000000002008-06-20C26410C제조업(10~33)통신및방송장비제조업정부자금소상공인일반자금운전대출보증개별보증중소기업은행진흥기금자금대출분할상환124832003-07-142003-07-14<NA>0.0+2hm2ENKy/AvlMWAqVKWqQ==m2yPA3oPN1SytRX2Z7B5bA==
262023-04F5061030*****경기도용인시 수지구풍덕천동200050451112020-04-162020-04-162020-04-02200000002020-04-2920000000158080002025-04-29I56111I숙박및음식점업(55~56)음식점및주점업정부자금소상공인경영안정자금(코로나)운전대출보증개별보증우리은행기운)재정중소기업자분할상환243632020-04-292020-04-292020-04-292.6+2jJ1Hu8QKy1w0auw/1V5w==WP+ggk3p7bYeqaShwxwZvg==
272023-04M4012514*****경기도평택시세교동50088862112005-06-032005-05-292005-04-18450000002005-06-105000000002010-06-21G45120G도매및소매업(45~47)자동차판매업정부자금소상공인일반자금운전대출보증개별보증국민은행기타재정자금대출분할상환124832005-06-032005-06-03<NA>0.0+2sjnsS4Yv6EQ14xZEPwIw==LHu8t3L9ZBXunuNlZPZpaA==
282023-04F3082514*****경기도부천시여월동170060333112017-12-112017-12-052017-11-29100000002017-12-131000000002022-12-13G47911G도매및소매업(45~47)도매및상품중개업일반자금소상공인지원자금운전대출보증개별보증우리은행기업운전일반자금대출분할상환124812017-12-132017-12-132017-12-133.75+2vqhEC/Y0KCvgCU9rTx2g==KAWVKIhMYP/f2oQJhHE9iw==
292023-04M5052315*****경기도구리시교문동200120115112020-04-132020-04-132020-04-13200000002020-04-1320000000200000002024-04-11S96112G도매및소매업(45~47)소매업;자동차제외일반자금소상공인지원자금운전대출보증개별보증중소기업은행중소기업자금대출만기일시 상환12002020-04-132020-04-132020-04-131.5+3MRFuL/+jMOLQqaam5GQg==uS389Zy4l4TvyFHnnk8N0w==