Overview

Dataset statistics

Number of variables8
Number of observations87
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory69.5 B

Variable types

Numeric2
Categorical4
Text2

Dataset

Description중소벤처기업진흥공단의 특허담보대출을 지원한 업체 현황으로, 지원한 현황을 파악할 수 있도록 정보를 개방하오니 특허담보대출관련 업무에 참고해주시기바랍니다.
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15073331/fileData.do

Alerts

지원연도 has constant value ""Constant
대여금액(시설)(백만원) has constant value ""Constant
번호 is highly overall correlated with 대여금액(운전)(백만원)High correlation
대여금액(운전)(백만원) is highly overall correlated with 번호High correlation
번호 has unique valuesUnique
주생산품 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:13:51.521855
Analysis finished2023-12-12 00:13:52.530827
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct87
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44
Minimum1
Maximum87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2023-12-12T09:13:52.609294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.3
Q122.5
median44
Q365.5
95-th percentile82.7
Maximum87
Range86
Interquartile range (IQR)43

Descriptive statistics

Standard deviation25.258662
Coefficient of variation (CV)0.5740605
Kurtosis-1.2
Mean44
Median Absolute Deviation (MAD)22
Skewness0
Sum3828
Variance638
MonotonicityStrictly increasing
2023-12-12T09:13:52.763279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
2 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
61 1
 
1.1%
60 1
 
1.1%
59 1
 
1.1%
58 1
 
1.1%
Other values (77) 77
88.5%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%
82 1
1.1%
81 1
1.1%
80 1
1.1%
79 1
1.1%
78 1
1.1%

지원연도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
2021
87 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 87
100.0%

Length

2023-12-12T09:13:52.903801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:13:53.019470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 87
100.0%

지역
Categorical

Distinct16
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Memory size828.0 B
경기
19 
서울
13 
경북
10 
경남
8 
부산
6 
Other values (11)
31 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row경북
2nd row부산
3rd row울산
4th row경북
5th row경기

Common Values

ValueCountFrequency (%)
경기 19
21.8%
서울 13
14.9%
경북 10
11.5%
경남 8
9.2%
부산 6
 
6.9%
대구 4
 
4.6%
충남 4
 
4.6%
충북 4
 
4.6%
울산 3
 
3.4%
인천 3
 
3.4%
Other values (6) 13
14.9%

Length

2023-12-12T09:13:53.120207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 19
21.8%
서울 13
14.9%
경북 10
11.5%
경남 8
9.2%
부산 6
 
6.9%
대구 4
 
4.6%
충남 4
 
4.6%
충북 4
 
4.6%
울산 3
 
3.4%
인천 3
 
3.4%
Other values (6) 13
14.9%

업종
Categorical

Distinct11
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size828.0 B
기계
21 
전자
16 
화공
10 
금속
9 
전기
7 
Other values (6)
24 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row식료
2nd row기계
3rd row화공
4th row화공
5th row화공

Common Values

ValueCountFrequency (%)
기계 21
24.1%
전자 16
18.4%
화공 10
11.5%
금속 9
10.3%
전기 7
 
8.0%
잡화 6
 
6.9%
식료 5
 
5.7%
정보 5
 
5.7%
기타 4
 
4.6%
유통 3
 
3.4%

Length

2023-12-12T09:13:53.239907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기계 21
24.1%
전자 16
18.4%
화공 10
11.5%
금속 9
10.3%
전기 7
 
8.0%
잡화 6
 
6.9%
식료 5
 
5.7%
정보 5
 
5.7%
기타 4
 
4.6%
유통 3
 
3.4%

산업품목코드명
Text

Distinct66
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Memory size828.0 B
2023-12-12T09:13:53.594080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length15.586207
Min length6

Characters and Unicode

Total characters1356
Distinct characters171
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)63.2%

Sample

1st row기타 수산동물 가공 및 저장 처리업
2nd row선박 구성 부분품 제조업
3rd row기타 기초 무기화학 물질 제조업
4th row기타 기초 무기화학 물질 제조업
5th row그 외 기타 플라스틱 제품 제조업
ValueCountFrequency (%)
제조업 72
 
17.3%
및 35
 
8.4%
기타 22
 
5.3%
외 15
 
3.6%
그 14
 
3.4%
부품 11
 
2.7%
신품 8
 
1.9%
기기 8
 
1.9%
자동차용 7
 
1.7%
전기 6
 
1.4%
Other values (151) 217
52.3%
2023-12-12T09:13:54.111553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
328
24.2%
제 90
 
6.6%
업 89
 
6.6%
조 80
 
5.9%
기 68
 
5.0%
품 36
 
2.7%
및 35
 
2.6%
용 31
 
2.3%
장 22
 
1.6%
타 22
 
1.6%
Other values (161) 555
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1016
74.9%
Space Separator 328
 
24.2%
Other Punctuation 12
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 90
 
8.9%
업 89
 
8.8%
조 80
 
7.9%
기 68
 
6.7%
품 36
 
3.5%
및 35
 
3.4%
용 31
 
3.1%
장 22
 
2.2%
타 22
 
2.2%
전 21
 
2.1%
Other values (159) 522
51.4%
Space Separator
ValueCountFrequency (%)
328
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1016
74.9%
Common 340
 
25.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 90
 
8.9%
업 89
 
8.8%
조 80
 
7.9%
기 68
 
6.7%
품 36
 
3.5%
및 35
 
3.4%
용 31
 
3.1%
장 22
 
2.2%
타 22
 
2.2%
전 21
 
2.1%
Other values (159) 522
51.4%
Common
ValueCountFrequency (%)
328
96.5%
, 12
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1014
74.8%
ASCII 340
 
25.1%
Compat Jamo 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
328
96.5%
, 12
 
3.5%
Hangul
ValueCountFrequency (%)
제 90
 
8.9%
업 89
 
8.8%
조 80
 
7.9%
기 68
 
6.7%
품 36
 
3.6%
및 35
 
3.5%
용 31
 
3.1%
장 22
 
2.2%
타 22
 
2.2%
전 21
 
2.1%
Other values (158) 520
51.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%

주생산품
Text

UNIQUE 

Distinct87
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size828.0 B
2023-12-12T09:13:54.447716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length19
Mean length11.62069
Min length3

Characters and Unicode

Total characters1011
Distinct characters258
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)100.0%

Sample

1st row수산물 제조 가공업
2nd row선박 소방관련 기자재
3rd row무기약품, 점착제
4th row탄소복합신소재
5th row가구용 플라스틱 사출
ValueCountFrequency (%)
등 11
 
4.6%
제조 11
 
4.6%
및 8
 
3.4%
개발 4
 
1.7%
소프트웨어 3
 
1.3%
제품 3
 
1.3%
부품 2
 
0.8%
특장차 2
 
0.8%
솔루션 2
 
0.8%
제작 2
 
0.8%
Other values (184) 190
79.8%
2023-12-12T09:13:54.886429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
151
 
14.9%
, 37
 
3.7%
기 30
 
3.0%
제 28
 
2.8%
스 23
 
2.3%
장 23
 
2.3%
조 18
 
1.8%
자 14
 
1.4%
리 13
 
1.3%
용 13
 
1.3%
Other values (248) 661
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 755
74.7%
Space Separator 151
 
14.9%
Uppercase Letter 42
 
4.2%
Other Punctuation 41
 
4.1%
Lowercase Letter 8
 
0.8%
Close Punctuation 7
 
0.7%
Open Punctuation 7
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 30
 
4.0%
제 28
 
3.7%
스 23
 
3.0%
장 23
 
3.0%
조 18
 
2.4%
자 14
 
1.9%
리 13
 
1.7%
용 13
 
1.7%
전 13
 
1.7%
트 13
 
1.7%
Other values (220) 567
75.1%
Uppercase Letter
ValueCountFrequency (%)
S 7
16.7%
E 5
11.9%
P 5
11.9%
D 4
9.5%
L 3
7.1%
I 3
7.1%
T 3
7.1%
C 3
7.1%
V 2
 
4.8%
A 2
 
4.8%
Other values (5) 5
11.9%
Lowercase Letter
ValueCountFrequency (%)
o 2
25.0%
n 1
12.5%
c 1
12.5%
a 1
12.5%
e 1
12.5%
w 1
12.5%
s 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 37
90.2%
/ 3
 
7.3%
. 1
 
2.4%
Space Separator
ValueCountFrequency (%)
151
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 755
74.7%
Common 206
 
20.4%
Latin 50
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 30
 
4.0%
제 28
 
3.7%
스 23
 
3.0%
장 23
 
3.0%
조 18
 
2.4%
자 14
 
1.9%
리 13
 
1.7%
용 13
 
1.7%
전 13
 
1.7%
트 13
 
1.7%
Other values (220) 567
75.1%
Latin
ValueCountFrequency (%)
S 7
14.0%
E 5
 
10.0%
P 5
 
10.0%
D 4
 
8.0%
L 3
 
6.0%
I 3
 
6.0%
T 3
 
6.0%
C 3
 
6.0%
o 2
 
4.0%
V 2
 
4.0%
Other values (12) 13
26.0%
Common
ValueCountFrequency (%)
151
73.3%
, 37
 
18.0%
) 7
 
3.4%
( 7
 
3.4%
/ 3
 
1.5%
. 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 755
74.7%
ASCII 256
 
25.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
151
59.0%
, 37
 
14.5%
) 7
 
2.7%
( 7
 
2.7%
S 7
 
2.7%
E 5
 
2.0%
P 5
 
2.0%
D 4
 
1.6%
L 3
 
1.2%
I 3
 
1.2%
Other values (18) 27
 
10.5%
Hangul
ValueCountFrequency (%)
기 30
 
4.0%
제 28
 
3.7%
스 23
 
3.0%
장 23
 
3.0%
조 18
 
2.4%
자 14
 
1.9%
리 13
 
1.7%
용 13
 
1.7%
전 13
 
1.7%
트 13
 
1.7%
Other values (220) 567
75.1%

대여금액(시설)(백만원)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
0
87 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 87
100.0%

Length

2023-12-12T09:13:55.029020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:13:55.125393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 87
100.0%

대여금액(운전)(백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean366.11494
Minimum100
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2023-12-12T09:13:55.213362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile186
Q1300
median300
Q3500
95-th percentile500
Maximum1000
Range900
Interquartile range (IQR)200

Descriptive statistics

Standard deviation140.381
Coefficient of variation (CV)0.38343421
Kurtosis3.4033015
Mean366.11494
Median Absolute Deviation (MAD)100
Skewness1.0866954
Sum31852
Variance19706.824
MonotonicityNot monotonic
2023-12-12T09:13:55.319269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
500 28
32.2%
300 26
29.9%
200 8
 
9.2%
350 3
 
3.4%
150 2
 
2.3%
420 2
 
2.3%
240 2
 
2.3%
280 2
 
2.3%
250 2
 
2.3%
100 1
 
1.1%
Other values (11) 11
 
12.6%
ValueCountFrequency (%)
100 1
 
1.1%
150 2
 
2.3%
170 1
 
1.1%
180 1
 
1.1%
200 8
 
9.2%
240 2
 
2.3%
244 1
 
1.1%
250 2
 
2.3%
280 2
 
2.3%
300 26
29.9%
ValueCountFrequency (%)
1000 1
 
1.1%
700 1
 
1.1%
500 28
32.2%
450 1
 
1.1%
420 2
 
2.3%
410 1
 
1.1%
400 1
 
1.1%
388 1
 
1.1%
360 1
 
1.1%
350 3
 
3.4%

Interactions

2023-12-12T09:13:52.107459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:13:51.947521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:13:52.182397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:13:52.028206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:13:55.397963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역업종산업품목코드명주생산품대여금액(운전)(백만원)
번호1.0000.0690.2160.2921.0000.739
지역0.0691.0000.3850.8301.0000.067
업종0.2160.3851.0001.0001.0000.309
산업품목코드명0.2920.8301.0001.0001.0000.955
주생산품1.0001.0001.0001.0001.0001.000
대여금액(운전)(백만원)0.7390.0670.3090.9551.0001.000
2023-12-12T09:13:55.517664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역업종
지역1.0000.143
업종0.1431.000
2023-12-12T09:13:55.598169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호대여금액(운전)(백만원)지역업종
번호1.0000.9190.0000.084
대여금액(운전)(백만원)0.9191.0000.0000.149
지역0.0000.0001.0000.143
업종0.0840.1490.1431.000

Missing values

2023-12-12T09:13:52.314717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:13:52.480788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

번호지원연도지역업종산업품목코드명주생산품대여금액(시설)(백만원)대여금액(운전)(백만원)
012021경북식료기타 수산동물 가공 및 저장 처리업수산물 제조 가공업0100
122021부산기계선박 구성 부분품 제조업선박 소방관련 기자재0200
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