Overview

Dataset statistics

Number of variables26
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory217.4 B

Variable types

Categorical18
Numeric2
Text5
DateTime1

Dataset

Description샘플 데이터
Author경기신용보증재단
URLhttps://www.bigdata-region.kr/#/dataset/cd317662-a65c-4feb-899d-a92bde31cae1

Alerts

기준년월 has constant value ""Constant
시도명 has constant value ""Constant
상담구분명 has constant value ""Constant
순번 is highly imbalanced (73.5%)Imbalance
누적보증수 is highly imbalanced (78.9%)Imbalance
거래구분명 is highly imbalanced (57.4%)Imbalance
보증방법명 is highly imbalanced (53.1%)Imbalance
자금용도명 is highly imbalanced (53.1%)Imbalance
반송사유명 is highly imbalanced (73.5%)Imbalance
관리번호 has unique valuesUnique
기업번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 14:17:41.556518
Analysis finished2023-12-10 14:17:42.166299
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-04
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-04
2nd row2023-04
3rd row2023-04
4th row2023-04
5th row2023-04

Common Values

ValueCountFrequency (%)
2023-04 30
100.0%

Length

2023-12-10T23:17:42.279920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:42.454567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-04 30
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5813.8333
Minimum4722
Maximum6947
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:42.655519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4722
5-th percentile5004.75
Q15365.25
median5699.5
Q36271.5
95-th percentile6821
Maximum6947
Range2225
Interquartile range (IQR)906.25

Descriptive statistics

Standard deviation606.50975
Coefficient of variation (CV)0.10432183
Kurtosis-0.81644071
Mean5813.8333
Median Absolute Deviation (MAD)410.5
Skewness0.32567604
Sum174415
Variance367854.07
MonotonicityStrictly increasing
2023-12-10T23:17:42.887622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4722 1
 
3.3%
5748 1
 
3.3%
6947 1
 
3.3%
6839 1
 
3.3%
6799 1
 
3.3%
6717 1
 
3.3%
6600 1
 
3.3%
6531 1
 
3.3%
6324 1
 
3.3%
6298 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
4722 1
3.3%
4899 1
3.3%
5134 1
3.3%
5159 1
3.3%
5267 1
3.3%
5273 1
3.3%
5305 1
3.3%
5363 1
3.3%
5372 1
3.3%
5447 1
3.3%
ValueCountFrequency (%)
6947 1
3.3%
6839 1
3.3%
6799 1
3.3%
6717 1
3.3%
6600 1
3.3%
6531 1
3.3%
6324 1
3.3%
6298 1
3.3%
6192 1
3.3%
6045 1
3.3%

순번
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
28 
2
 
1
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
1 28
93.3%
2 1
 
3.3%
5 1
 
3.3%

Length

2023-12-10T23:17:43.111100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:43.279322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 28
93.3%
2 1
 
3.3%
5 1
 
3.3%

성별코드
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
M
24 
F
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 24
80.0%
F 6
 
20.0%

Length

2023-12-10T23:17:43.457068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:43.629969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 24
80.0%
f 6
 
20.0%

연령대코드
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
60
12 
50
11 
80
3 
70
3 
40
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row60
2nd row60
3rd row80
4th row80
5th row60

Common Values

ValueCountFrequency (%)
60 12
40.0%
50 11
36.7%
80 3
 
10.0%
70 3
 
10.0%
40 1
 
3.3%

Length

2023-12-10T23:17:44.091909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:44.642339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
60 12
40.0%
50 11
36.7%
80 3
 
10.0%
70 3
 
10.0%
40 1
 
3.3%

사업자등록번호
Text

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:17:45.272835image/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

Unique24 ?
Unique (%)80.0%

Sample

1st row12607*****
2nd row13506*****
3rd row12801*****
4th row12781*****
5th row13811*****
ValueCountFrequency (%)
12781 2
 
6.7%
12810 2
 
6.7%
13506 2
 
6.7%
12990 1
 
3.3%
12607 1
 
3.3%
13210 1
 
3.3%
12581 1
 
3.3%
12815 1
 
3.3%
12404 1
 
3.3%
13507 1
 
3.3%
Other values (17) 17
56.7%
2023-12-10T23:17:45.836472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 150
50.0%
1 49
 
16.3%
0 20
 
6.7%
2 19
 
6.3%
3 14
 
4.7%
8 12
 
4.0%
5 9
 
3.0%
4 8
 
2.7%
6 7
 
2.3%
7 6
 
2.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 49
32.7%
0 20
13.3%
2 19
 
12.7%
3 14
 
9.3%
8 12
 
8.0%
5 9
 
6.0%
4 8
 
5.3%
6 7
 
4.7%
7 6
 
4.0%
9 6
 
4.0%
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 49
 
16.3%
0 20
 
6.7%
2 19
 
6.3%
3 14
 
4.7%
8 12
 
4.0%
5 9
 
3.0%
4 8
 
2.7%
6 7
 
2.3%
7 6
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 150
50.0%
1 49
 
16.3%
0 20
 
6.7%
2 19
 
6.3%
3 14
 
4.7%
8 12
 
4.0%
5 9
 
3.0%
4 8
 
2.7%
6 7
 
2.3%
7 6
 
2.0%

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

2023-12-10T23:17:46.054378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:46.214332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:17:46.435026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length4.5333333
Min length3

Characters and Unicode

Total characters136
Distinct characters39
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 row광주시
2nd row수원시 장안구
3rd row파주시
4th row의정부시
5th row화성시
ValueCountFrequency (%)
수원시 5
 
12.2%
파주시 3
 
7.3%
장안구 3
 
7.3%
부천시 3
 
7.3%
안산시 2
 
4.9%
단원구 2
 
4.9%
성남시 2
 
4.9%
팔달구 1
 
2.4%
양주시 1
 
2.4%
시흥시 1
 
2.4%
Other values (18) 18
43.9%
2023-12-10T23:17:46.946367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 30
22.1%
11
 
8.1%
구 11
 
8.1%
원 8
 
5.9%
수 7
 
5.1%
주 6
 
4.4%
안 6
 
4.4%
천 6
 
4.4%
성 4
 
2.9%
양 4
 
2.9%
Other values (29) 43
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
91.9%
Space Separator 11
 
8.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 30
24.0%
구 11
 
8.8%
원 8
 
6.4%
수 7
 
5.6%
주 6
 
4.8%
안 6
 
4.8%
천 6
 
4.8%
성 4
 
3.2%
양 4
 
3.2%
부 4
 
3.2%
Other values (28) 39
31.2%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
91.9%
Common 11
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 30
24.0%
구 11
 
8.8%
원 8
 
6.4%
수 7
 
5.6%
주 6
 
4.8%
안 6
 
4.8%
천 6
 
4.8%
성 4
 
3.2%
양 4
 
3.2%
부 4
 
3.2%
Other values (28) 39
31.2%
Common
ValueCountFrequency (%)
11
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
91.9%
ASCII 11
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 30
24.0%
구 11
 
8.8%
원 8
 
6.4%
수 7
 
5.6%
주 6
 
4.8%
안 6
 
4.8%
천 6
 
4.8%
성 4
 
3.2%
양 4
 
3.2%
부 4
 
3.2%
Other values (28) 39
31.2%
ASCII
ValueCountFrequency (%)
11
100.0%

행정동명
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:17:47.229556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.1333333
Min length2

Characters and Unicode

Total characters94
Distinct characters46
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

Unique28 ?
Unique (%)93.3%

Sample

1st row송정동
2nd row송죽동
3rd row광탄면
4th row장암동
5th row남양읍
ValueCountFrequency (%)
송죽동 2
 
6.7%
송정동 1
 
3.3%
화도읍 1
 
3.3%
대덕면 1
 
3.3%
토당동 1
 
3.3%
매교동 1
 
3.3%
정왕동 1
 
3.3%
파장동 1
 
3.3%
파평면 1
 
3.3%
회암동 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T23:17:47.722509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 22
23.4%
읍 5
 
5.3%
곡 5
 
5.3%
송 4
 
4.3%
면 4
 
4.3%
정 3
 
3.2%
장 3
 
3.2%
상 3
 
3.2%
파 2
 
2.1%
원 2
 
2.1%
Other values (36) 41
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 22
23.4%
읍 5
 
5.3%
곡 5
 
5.3%
송 4
 
4.3%
면 4
 
4.3%
정 3
 
3.2%
장 3
 
3.2%
상 3
 
3.2%
파 2
 
2.1%
원 2
 
2.1%
Other values (36) 41
43.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 94
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 22
23.4%
읍 5
 
5.3%
곡 5
 
5.3%
송 4
 
4.3%
면 4
 
4.3%
정 3
 
3.2%
장 3
 
3.2%
상 3
 
3.2%
파 2
 
2.1%
원 2
 
2.1%
Other values (36) 41
43.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 94
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 22
23.4%
읍 5
 
5.3%
곡 5
 
5.3%
송 4
 
4.3%
면 4
 
4.3%
정 3
 
3.2%
장 3
 
3.2%
상 3
 
3.2%
파 2
 
2.1%
원 2
 
2.1%
Other values (36) 41
43.6%

업종명
Text

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:17:48.126429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length10.566667
Min length2

Characters and Unicode

Total characters317
Distinct characters119
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

Unique24 ?
Unique (%)80.0%

Sample

1st row기타목재가구제조업
2nd row피자;햄버거;샌드위치및유사음식점업
3rd row한식일반음식점업
4th row모직물직조업
5th row자동차차체용신품부품제조업
ValueCountFrequency (%)
기타목재가구제조업 2
 
6.7%
한식일반음식점업 2
 
6.7%
피자;햄버거;샌드위치및유사음식점업 2
 
6.7%
택시운송업 1
 
3.3%
곡물도정업 1
 
3.3%
혼성및재생플라스틱소재물질제조업 1
 
3.3%
문구용품;회화용품;사무용품도매업 1
 
3.3%
남자용겉옷소매업 1
 
3.3%
계면활성제제조업 1
 
3.3%
인테리어디자인업 1
 
3.3%
Other values (17) 17
56.7%
2023-12-10T23:17:48.747054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 28
 
8.8%
조 15
 
4.7%
제 14
 
4.4%
기 13
 
4.1%
; 10
 
3.2%
자 9
 
2.8%
및 9
 
2.8%
타 8
 
2.5%
용 8
 
2.5%
품 7
 
2.2%
Other values (109) 196
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 307
96.8%
Other Punctuation 10
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 28
 
9.1%
조 15
 
4.9%
제 14
 
4.6%
기 13
 
4.2%
자 9
 
2.9%
및 9
 
2.9%
타 8
 
2.6%
용 8
 
2.6%
품 7
 
2.3%
식 6
 
2.0%
Other values (108) 190
61.9%
Other Punctuation
ValueCountFrequency (%)
; 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 307
96.8%
Common 10
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 28
 
9.1%
조 15
 
4.9%
제 14
 
4.6%
기 13
 
4.2%
자 9
 
2.9%
및 9
 
2.9%
타 8
 
2.6%
용 8
 
2.6%
품 7
 
2.3%
식 6
 
2.0%
Other values (108) 190
61.9%
Common
ValueCountFrequency (%)
; 10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 307
96.8%
ASCII 10
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 28
 
9.1%
조 15
 
4.9%
제 14
 
4.6%
기 13
 
4.2%
자 9
 
2.9%
및 9
 
2.9%
타 8
 
2.6%
용 8
 
2.6%
품 7
 
2.3%
식 6
 
2.0%
Other values (108) 190
61.9%
ASCII
ValueCountFrequency (%)
; 10
100.0%

상담구분명
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 30
100.0%

Length

2023-12-10T23:17:48.979598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:49.453874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 30
100.0%

접수일자
Date

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2000-01-17 00:00:00
Maximum2000-08-05 00:00:00
2023-12-10T23:17:49.613256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:49.865288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

접수구분명
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
소상공인
21 
중기업
6 
구조조정용
3 

Length

Max length5
Median length4
Mean length3.9
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소상공인
2nd row소상공인
3rd row소상공인
4th row중기업
5th row구조조정용

Common Values

ValueCountFrequency (%)
소상공인 21
70.0%
중기업 6
 
20.0%
구조조정용 3
 
10.0%

Length

2023-12-10T23:17:50.102684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:50.313194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소상공인 21
70.0%
중기업 6
 
20.0%
구조조정용 3
 
10.0%

자금종류대분류명
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
정부자금
20 
기타
6 
일반자금
3 
시군자금
 
1

Length

Max length4
Median length4
Mean length3.6
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
정부자금 20
66.7%
기타 6
 
20.0%
일반자금 3
 
10.0%
시군자금 1
 
3.3%

Length

2023-12-10T23:17:50.559002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:50.749922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정부자금 20
66.7%
기타 6
 
20.0%
일반자금 3
 
10.0%
시군자금 1
 
3.3%

자금종류중분류명
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
소상공인일반자금
20 
창경자금-일반기업
3 
운전자금-일반기업
3 
일반자금
 
2
소상공인지원자금
 
1

Length

Max length9
Median length8
Mean length7.9333333
Min length4

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row소상공인일반자금
2nd row소상공인일반자금
3rd row소상공인일반자금
4th row일반자금
5th row창경자금-일반기업

Common Values

ValueCountFrequency (%)
소상공인일반자금 20
66.7%
창경자금-일반기업 3
 
10.0%
운전자금-일반기업 3
 
10.0%
일반자금 2
 
6.7%
소상공인지원자금 1
 
3.3%
중소기업육성자금 1
 
3.3%

Length

2023-12-10T23:17:50.972086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:51.162782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소상공인일반자금 20
66.7%
창경자금-일반기업 3
 
10.0%
운전자금-일반기업 3
 
10.0%
일반자금 2
 
6.7%
소상공인지원자금 1
 
3.3%
중소기업육성자금 1
 
3.3%

보증신청금액
Real number (ℝ)

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79144933
Minimum8000000
Maximum9.44 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:51.328513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8000000
5-th percentile8900000
Q110000000
median20000000
Q367500000
95-th percentile3 × 108
Maximum9.44 × 108
Range9.36 × 108
Interquartile range (IQR)57500000

Descriptive statistics

Standard deviation1.7954884 × 108
Coefficient of variation (CV)2.2686081
Kurtosis19.707054
Mean79144933
Median Absolute Deviation (MAD)10000000
Skewness4.2309136
Sum2.374348 × 109
Variance3.2237786 × 1016
MonotonicityNot monotonic
2023-12-10T23:17:51.519414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
20000000 8
26.7%
10000000 7
23.3%
8000000 2
 
6.7%
300000000 2
 
6.7%
100000000 2
 
6.7%
25500000 2
 
6.7%
944000000 1
 
3.3%
80000000 1
 
3.3%
17000000 1
 
3.3%
15000000 1
 
3.3%
Other values (3) 3
 
10.0%
ValueCountFrequency (%)
8000000 2
 
6.7%
10000000 7
23.3%
15000000 1
 
3.3%
17000000 1
 
3.3%
20000000 8
26.7%
25500000 2
 
6.7%
30000000 1
 
3.3%
80000000 1
 
3.3%
85000000 1
 
3.3%
100000000 2
 
6.7%
ValueCountFrequency (%)
944000000 1
 
3.3%
300000000 2
 
6.7%
106348000 1
 
3.3%
100000000 2
 
6.7%
85000000 1
 
3.3%
80000000 1
 
3.3%
30000000 1
 
3.3%
25500000 2
 
6.7%
20000000 8
26.7%
17000000 1
 
3.3%

누적보증수
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
29 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
1 29
96.7%
2 1
 
3.3%

Length

2023-12-10T23:17:51.827646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:52.045038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 29
96.7%
2 1
 
3.3%

기업규모명
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
소상공인
24 
중기업
6 

Length

Max length4
Median length4
Mean length3.8
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소상공인
2nd row소상공인
3rd row소상공인
4th row중기업
5th row소상공인

Common Values

ValueCountFrequency (%)
소상공인 24
80.0%
중기업 6
 
20.0%

Length

2023-12-10T23:17:52.246676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:52.449450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소상공인 24
80.0%
중기업 6
 
20.0%

거래구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
신규
26 
기타
3 
회생지원보증
 
1

Length

Max length6
Median length2
Mean length2.1333333
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row신규
2nd row신규
3rd row신규
4th row회생지원보증
5th row기타

Common Values

ValueCountFrequency (%)
신규 26
86.7%
기타 3
 
10.0%
회생지원보증 1
 
3.3%

Length

2023-12-10T23:17:52.637850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:52.809901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 26
86.7%
기타 3
 
10.0%
회생지원보증 1
 
3.3%

보증종류명
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
대출보증
21 
비은행대출보증
6 
기타
3 

Length

Max length7
Median length4
Mean length4.4
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대출보증 21
70.0%
비은행대출보증 6
 
20.0%
기타 3
 
10.0%

Length

2023-12-10T23:17:52.994647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:53.182713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대출보증 21
70.0%
비은행대출보증 6
 
20.0%
기타 3
 
10.0%

보증방법명
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
개별보증
27 
기타
3 

Length

Max length4
Median length4
Mean length3.8
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개별보증 27
90.0%
기타 3
 
10.0%

Length

2023-12-10T23:17:53.378698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:53.600337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개별보증 27
90.0%
기타 3
 
10.0%

자금용도명
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
운전
27 
기타
3 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운전 27
90.0%
기타 3
 
10.0%

Length

2023-12-10T23:17:53.836719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:54.104447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운전 27
90.0%
기타 3
 
10.0%

상세용도명
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
창업
17 
기타
6 
경영개선
4 
시설개선
3 

Length

Max length4
Median length2
Mean length2.4666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row창업
2nd row창업
3rd row창업
4th row경영개선
5th row기타

Common Values

ValueCountFrequency (%)
창업 17
56.7%
기타 6
 
20.0%
경영개선 4
 
13.3%
시설개선 3
 
10.0%

Length

2023-12-10T23:17:54.344973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:54.582215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
창업 17
56.7%
기타 6
 
20.0%
경영개선 4
 
13.3%
시설개선 3
 
10.0%

반송사유명
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
기타
28 
재보증제한
 
1
불량거래기업
 
1

Length

Max length6
Median length2
Mean length2.2333333
Min length2

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
기타 28
93.3%
재보증제한 1
 
3.3%
불량거래기업 1
 
3.3%

Length

2023-12-10T23:17:54.827441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:55.063179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 28
93.3%
재보증제한 1
 
3.3%
불량거래기업 1
 
3.3%

은행명
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
한국씨티은행
8 
국민은행
7 
중소기업은행
6 
농협은행
5 
기타
3 

Length

Max length6
Median length5
Mean length4.7666667
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row국민은행
2nd row국민은행
3rd row국민은행
4th row한국씨티은행
5th row기타

Common Values

ValueCountFrequency (%)
한국씨티은행 8
26.7%
국민은행 7
23.3%
중소기업은행 6
20.0%
농협은행 5
16.7%
기타 3
 
10.0%
지역농축협 1
 
3.3%

Length

2023-12-10T23:17:55.330340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:55.659152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국씨티은행 8
26.7%
국민은행 7
23.3%
중소기업은행 6
20.0%
농협은행 5
16.7%
기타 3
 
10.0%
지역농축협 1
 
3.3%

기업번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:17:55.997792image/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 rowYgU8s+bt4XXbK4lC+/ZHmQ==
2nd rowj0IpHRpBK3AsKAfSVVnzxw==
3rd row9vlN6iH+wyK/hP8bauRxiQ==
4th rowZEke7ZYMBXicVDex4jxURA==
5th rowhi8hjlK8US71arOKqLg94A==
ValueCountFrequency (%)
ygu8s+bt4xxbk4lc+/zhmq 1
 
3.3%
j0iphrpbk3askafsvvnzxw 1
 
3.3%
vttnbwfcu76fxdbgc1qqrq 1
 
3.3%
ekhhlqrngfbyhbiue4k1nq 1
 
3.3%
4ivgzmcwicmzqgvmb1rp8g 1
 
3.3%
soc1qly0nuy+tzlutgwwla 1
 
3.3%
pazhgzksule+5ujykbd2cq 1
 
3.3%
2/kieedomhfjazbx0hglow 1
 
3.3%
ws/jq70tfrjbdln99y0bxa 1
 
3.3%
yrcgxcbknggpmydiunmliw 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:17:56.505287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
= 60
 
8.3%
K 20
 
2.8%
i 20
 
2.8%
Q 18
 
2.5%
C 18
 
2.5%
g 16
 
2.2%
l 15
 
2.1%
z 15
 
2.1%
q 15
 
2.1%
w 14
 
1.9%
Other values (55) 509
70.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 281
39.0%
Uppercase Letter 268
37.2%
Decimal Number 93
 
12.9%
Math Symbol 70
 
9.7%
Other Punctuation 8
 
1.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 20
 
7.5%
Q 18
 
6.7%
C 18
 
6.7%
N 13
 
4.9%
A 13
 
4.9%
G 12
 
4.5%
V 12
 
4.5%
R 12
 
4.5%
B 12
 
4.5%
U 11
 
4.1%
Other values (16) 127
47.4%
Lowercase Letter
ValueCountFrequency (%)
i 20
 
7.1%
g 16
 
5.7%
l 15
 
5.3%
z 15
 
5.3%
q 15
 
5.3%
w 14
 
5.0%
t 13
 
4.6%
x 13
 
4.6%
y 12
 
4.3%
b 12
 
4.3%
Other values (16) 136
48.4%
Decimal Number
ValueCountFrequency (%)
0 13
14.0%
3 11
11.8%
4 11
11.8%
5 11
11.8%
1 10
10.8%
8 10
10.8%
9 10
10.8%
6 7
7.5%
7 5
 
5.4%
2 5
 
5.4%
Math Symbol
ValueCountFrequency (%)
= 60
85.7%
+ 10
 
14.3%
Other Punctuation
ValueCountFrequency (%)
/ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 549
76.2%
Common 171
 
23.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 20
 
3.6%
i 20
 
3.6%
Q 18
 
3.3%
C 18
 
3.3%
g 16
 
2.9%
l 15
 
2.7%
z 15
 
2.7%
q 15
 
2.7%
w 14
 
2.6%
t 13
 
2.4%
Other values (42) 385
70.1%
Common
ValueCountFrequency (%)
= 60
35.1%
0 13
 
7.6%
3 11
 
6.4%
4 11
 
6.4%
5 11
 
6.4%
+ 10
 
5.8%
1 10
 
5.8%
8 10
 
5.8%
9 10
 
5.8%
/ 8
 
4.7%
Other values (3) 17
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
= 60
 
8.3%
K 20
 
2.8%
i 20
 
2.8%
Q 18
 
2.5%
C 18
 
2.5%
g 16
 
2.2%
l 15
 
2.1%
z 15
 
2.1%
q 15
 
2.1%
w 14
 
1.9%
Other values (55) 509
70.7%

Sample

기준년월관리번호순번성별코드연령대코드사업자등록번호시도명시군구명행정동명업종명상담구분명접수일자접수구분명자금종류대분류명자금종류중분류명보증신청금액누적보증수기업규모명거래구분명보증종류명보증방법명자금용도명상세용도명반송사유명은행명기업번호
02023-0447221M6012607*****경기도광주시송정동기타목재가구제조업기타2000-01-17소상공인정부자금소상공인일반자금100000001소상공인신규대출보증개별보증운전창업기타국민은행YgU8s+bt4XXbK4lC+/ZHmQ==
12023-0448991M6013506*****경기도수원시 장안구송죽동피자;햄버거;샌드위치및유사음식점업기타2000-01-28소상공인정부자금소상공인일반자금80000001소상공인신규대출보증개별보증운전창업기타국민은행j0IpHRpBK3AsKAfSVVnzxw==
22023-0451341F8012801*****경기도파주시광탄면한식일반음식점업기타2000-02-21소상공인정부자금소상공인일반자금200000001소상공인신규대출보증개별보증운전창업기타국민은행9vlN6iH+wyK/hP8bauRxiQ==
32023-0451592M8012781*****경기도의정부시장암동모직물직조업기타2000-02-17중기업일반자금일반자금200000001중기업회생지원보증대출보증개별보증운전경영개선기타한국씨티은행ZEke7ZYMBXicVDex4jxURA==
42023-0452671M6013811*****경기도화성시남양읍자동차차체용신품부품제조업기타2000-03-10구조조정용기타창경자금-일반기업3000000001소상공인기타기타기타기타기타기타기타hi8hjlK8US71arOKqLg94A==
52023-0452731M7012681*****경기도이천시마장면김치류제조업기타2000-03-10구조조정용기타창경자금-일반기업9440000002소상공인기타기타기타기타기타기타기타2tWGij0J43vKD4VQilu5CA==
62023-0453051M7012618*****경기도하남시상산곡동전자코일;변성기및기타전자유도자제조업기타2000-03-21중기업기타운전자금-일반기업800000001중기업신규대출보증개별보증운전경영개선기타중소기업은행zQBTk3nJ8CE5t9piqIKzJA==
72023-0453631F5013007*****경기도부천시상동피자;햄버거;샌드위치및유사음식점업기타2000-03-22소상공인정부자금소상공인일반자금80000001소상공인신규대출보증개별보증운전시설개선기타한국씨티은행Tcr3nKKohNlXubgC1ZZNFw==
82023-0453721M4012715*****경기도연천군전곡읍컴퓨터및주변장치;소프트웨어소매업기타2000-06-21소상공인정부자금소상공인일반자금170000001소상공인신규대출보증개별보증운전창업기타한국씨티은행5V/ayPM2vFeU865zsmWR9w==
92023-0454471M6012914*****경기도성남시 수정구신흥동편조의복제조업기타2000-04-04소상공인정부자금소상공인일반자금150000001소상공인신규비은행대출보증개별보증운전창업기타농협은행KqDyKnZzi8DkNGTiG99CQg==
기준년월관리번호순번성별코드연령대코드사업자등록번호시도명시군구명행정동명업종명상담구분명접수일자접수구분명자금종류대분류명자금종류중분류명보증신청금액누적보증수기업규모명거래구분명보증종류명보증방법명자금용도명상세용도명반송사유명은행명기업번호
202023-0460451F5012412*****경기도수원시 권선구곡반정동기타미용업기타2000-05-08소상공인정부자금소상공인일반자금100000001소상공인신규대출보증개별보증운전창업기타한국씨티은행nm/3QL+LfxpFcgqLizjCWg==
212023-0461925M6012781*****경기도양주시회암동직물;편조원단및의복류염색가공업기타2000-05-18중기업일반자금일반자금1000000001중기업신규대출보증개별보증운전기타기타한국씨티은행YRcGXCbkNgGPMyDiuNMliw==
222023-0462981M5012810*****경기도파주시파평면기타기타2000-08-05소상공인일반자금소상공인지원자금255000001소상공인신규비은행대출보증개별보증운전창업재보증제한지역농축협ws/JQ70TfrJBdln99Y0BXA==
232023-0463241M6013506*****경기도수원시 장안구파장동인테리어디자인업기타2000-05-22소상공인정부자금소상공인일반자금200000001소상공인신규비은행대출보증개별보증운전창업기타농협은행2/kieEDomHfjazbx0HGlow==
242023-0465311M6013381*****경기도시흥시정왕동계면활성제제조업기타2000-05-10구조조정용기타창경자금-일반기업1063480001소상공인기타기타기타기타기타기타기타pAZhgzKsuLE+5ujYKBD2CQ==
252023-0466001F6013507*****경기도수원시 장안구송죽동남자용겉옷소매업기타2000-06-09소상공인정부자금소상공인일반자금200000001소상공인신규대출보증개별보증운전창업기타한국씨티은행SoC1QLy0NUy+tzluTgwWlA==
262023-0467171M5012404*****경기도수원시 팔달구매교동문구용품;회화용품;사무용품도매업기타2000-06-23소상공인정부자금소상공인일반자금200000001소상공인신규대출보증개별보증운전창업기타중소기업은행4iVGzmCWiCmzqGvMb1Rp8g==
272023-0467991M5012815*****경기도고양시 덕양구토당동기타목재가구제조업기타2000-07-03중기업기타운전자금-일반기업1000000001중기업신규비은행대출보증개별보증운전기타기타농협은행EkhHlQrNgfbyHBIUe4k1nQ==
282023-0468391M5012581*****경기도안성시대덕면혼성및재생플라스틱소재물질제조업기타2000-07-28중기업시군자금중소기업육성자금850000001중기업신규비은행대출보증개별보증운전경영개선기타농협은행VttnBwFcU76FXDbgC1qqrQ==
292023-0469471M5012406*****경기도포천시소흘읍감광재료및관련화학제품제조업기타2000-07-10소상공인정부자금소상공인일반자금255000001소상공인신규대출보증개별보증운전창업불량거래기업국민은행BKofcWpyyCF+7Z+PtSaVCw==