Overview

Dataset statistics

Number of variables5
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory45.6 B

Variable types

Text3
Categorical1
Numeric1

Dataset

Description해외VC 투자유치를 지원하는 해외VC글로벌펀드의 자조합을 운용하는 운용사 정보 및 펀드 규모, 약정액 등에 대한 정보를 제공합니다.
Author한국벤처투자(주)
URLhttps://www.data.go.kr/data/15090980/fileData.do

Alerts

모태약정액(억원) is highly overall correlated with 운용사 국가High correlation
운용사 국가 is highly overall correlated with 모태약정액(억원)High correlation
펀드명 has unique valuesUnique
결성총액(억원) has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:31:10.978608
Analysis finished2023-12-12 14:31:11.637978
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

펀드명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T23:31:11.864894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length40
Mean length33.137931
Min length16

Characters and Unicode

Total characters961
Distinct characters57
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st rowBRV Lotus Fund 2012, L.P.
2nd rowAltos Korea Opportunity Fund, L.P.
3rd rowBig Basin Fund I, L.P.
4th rowStorm Ventures Fund V, L.P.
5th row500 Kimchi, L.P.
ValueCountFrequency (%)
l.p 23
 
15.5%
fund 19
 
12.8%
ventures 5
 
3.4%
ii 4
 
2.7%
i 4
 
2.7%
limited 3
 
2.0%
partnership 3
 
2.0%
korea 3
 
2.0%
iii 3
 
2.0%
capital 3
 
2.0%
Other values (68) 78
52.7%
2023-12-12T23:31:12.315305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
 
12.4%
n 76
 
7.9%
e 70
 
7.3%
t 55
 
5.7%
. 48
 
5.0%
r 48
 
5.0%
a 47
 
4.9%
i 38
 
4.0%
u 37
 
3.9%
I 34
 
3.5%
Other values (47) 389
40.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 550
57.2%
Uppercase Letter 203
 
21.1%
Space Separator 119
 
12.4%
Other Punctuation 71
 
7.4%
Decimal Number 11
 
1.1%
Dash Punctuation 4
 
0.4%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Control 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 76
13.8%
e 70
12.7%
t 55
10.0%
r 48
8.7%
a 47
8.5%
i 38
6.9%
u 37
6.7%
o 30
 
5.5%
s 29
 
5.3%
d 29
 
5.3%
Other values (14) 91
16.5%
Uppercase Letter
ValueCountFrequency (%)
I 34
16.7%
P 32
15.8%
L 31
15.3%
F 21
10.3%
V 14
6.9%
S 13
 
6.4%
K 11
 
5.4%
A 10
 
4.9%
G 8
 
3.9%
C 7
 
3.4%
Other values (11) 22
10.8%
Decimal Number
ValueCountFrequency (%)
0 5
45.5%
5 2
 
18.2%
2 2
 
18.2%
1 1
 
9.1%
9 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 48
67.6%
, 23
32.4%
Space Separator
ValueCountFrequency (%)
119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 753
78.4%
Common 208
 
21.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 76
 
10.1%
e 70
 
9.3%
t 55
 
7.3%
r 48
 
6.4%
a 47
 
6.2%
i 38
 
5.0%
u 37
 
4.9%
I 34
 
4.5%
P 32
 
4.2%
L 31
 
4.1%
Other values (35) 285
37.8%
Common
ValueCountFrequency (%)
119
57.2%
. 48
23.1%
, 23
 
11.1%
0 5
 
2.4%
- 4
 
1.9%
5 2
 
1.0%
2 2
 
1.0%
1 1
 
0.5%
) 1
 
0.5%
( 1
 
0.5%
Other values (2) 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 961
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
119
 
12.4%
n 76
 
7.9%
e 70
 
7.3%
t 55
 
5.7%
. 48
 
5.0%
r 48
 
5.0%
a 47
 
4.9%
i 38
 
4.0%
u 37
 
3.9%
I 34
 
3.5%
Other values (47) 389
40.5%

운용사명
Text

Distinct26
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T23:31:12.583534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length21
Mean length17.137931
Min length11

Characters and Unicode

Total characters497
Distinct characters60
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

Unique23 ?
Unique (%)79.3%

Sample

1st rowBlueRun Ventures
2nd rowAltos Ventures
3rd rowBig Basin Capital
4th rowStorm Ventures
5th row500 Startups
ValueCountFrequency (%)
ventures 11
 
17.2%
capital 6
 
9.4%
partners 3
 
4.7%
big 2
 
3.1%
strong 2
 
3.1%
500 2
 
3.1%
startups 2
 
3.1%
basin 2
 
3.1%
entrepreneurs 1
 
1.6%
roundtable 1
 
1.6%
Other values (32) 32
50.0%
2023-12-12T23:31:12.926649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 56
 
11.3%
t 43
 
8.7%
n 42
 
8.5%
r 40
 
8.0%
36
 
7.2%
a 33
 
6.6%
s 25
 
5.0%
u 23
 
4.6%
i 18
 
3.6%
o 17
 
3.4%
Other values (50) 164
33.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 358
72.0%
Uppercase Letter 75
 
15.1%
Space Separator 36
 
7.2%
Other Letter 16
 
3.2%
Decimal Number 6
 
1.2%
Dash Punctuation 4
 
0.8%
Other Punctuation 2
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 56
15.6%
t 43
12.0%
n 42
11.7%
r 40
11.2%
a 33
9.2%
s 25
7.0%
u 23
6.4%
i 18
 
5.0%
o 17
 
4.7%
l 14
 
3.9%
Other values (11) 47
13.1%
Uppercase Letter
ValueCountFrequency (%)
V 12
16.0%
S 10
13.3%
A 9
12.0%
C 7
9.3%
B 6
8.0%
T 5
6.7%
P 4
 
5.3%
K 4
 
5.3%
L 3
 
4.0%
G 3
 
4.0%
Other values (9) 12
16.0%
Other Letter
ValueCountFrequency (%)
스 2
 
12.5%
코 1
 
6.2%
트 1
 
6.2%
베 1
 
6.2%
터 1
 
6.2%
인 1
 
6.2%
처 1
 
6.2%
벤 1
 
6.2%
나 1
 
6.2%
브 1
 
6.2%
Other values (5) 5
31.2%
Decimal Number
ValueCountFrequency (%)
0 4
66.7%
5 2
33.3%
Space Separator
ValueCountFrequency (%)
36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 433
87.1%
Common 48
 
9.7%
Hangul 16
 
3.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 56
12.9%
t 43
 
9.9%
n 42
 
9.7%
r 40
 
9.2%
a 33
 
7.6%
s 25
 
5.8%
u 23
 
5.3%
i 18
 
4.2%
o 17
 
3.9%
l 14
 
3.2%
Other values (30) 122
28.2%
Hangul
ValueCountFrequency (%)
스 2
 
12.5%
코 1
 
6.2%
트 1
 
6.2%
베 1
 
6.2%
터 1
 
6.2%
인 1
 
6.2%
처 1
 
6.2%
벤 1
 
6.2%
나 1
 
6.2%
브 1
 
6.2%
Other values (5) 5
31.2%
Common
ValueCountFrequency (%)
36
75.0%
0 4
 
8.3%
- 4
 
8.3%
& 2
 
4.2%
5 2
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 481
96.8%
Hangul 16
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 56
 
11.6%
t 43
 
8.9%
n 42
 
8.7%
r 40
 
8.3%
36
 
7.5%
a 33
 
6.9%
s 25
 
5.2%
u 23
 
4.8%
i 18
 
3.7%
o 17
 
3.5%
Other values (35) 148
30.8%
Hangul
ValueCountFrequency (%)
스 2
 
12.5%
코 1
 
6.2%
트 1
 
6.2%
베 1
 
6.2%
터 1
 
6.2%
인 1
 
6.2%
처 1
 
6.2%
벤 1
 
6.2%
나 1
 
6.2%
브 1
 
6.2%
Other values (5) 5
31.2%

운용사 국가
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)41.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
미국
16 
중국
2 
싱가포르-중국
2 
미국-중국
 
1
한국-인니
 
1
Other values (7)
7 

Length

Max length7
Median length2
Mean length3.0689655
Min length2

Unique

Unique9 ?
Unique (%)31.0%

Sample

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

Common Values

ValueCountFrequency (%)
미국 16
55.2%
중국 2
 
6.9%
싱가포르-중국 2
 
6.9%
미국-중국 1
 
3.4%
한국-인니 1
 
3.4%
한국-중국 1
 
3.4%
미국&유럽 1
 
3.4%
멕시코 1
 
3.4%
한국-미국 1
 
3.4%
한국-태국 1
 
3.4%
Other values (2) 2
 
6.9%

Length

2023-12-12T23:31:13.076766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미국 16
55.2%
중국 2
 
6.9%
싱가포르-중국 2
 
6.9%
미국-중국 1
 
3.4%
한국-인니 1
 
3.4%
한국-중국 1
 
3.4%
미국&유럽 1
 
3.4%
멕시코 1
 
3.4%
한국-미국 1
 
3.4%
한국-태국 1
 
3.4%
Other values (2) 2
 
6.9%

결성총액(억원)
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T23:31:13.254789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.6896552
Min length6

Characters and Unicode

Total characters194
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row1,944.4
2nd row660.0
3rd row150.0
4th row1,951.4
5th row133.6
ValueCountFrequency (%)
1,944.4 1
 
3.4%
1,860.0 1
 
3.4%
555.6 1
 
3.4%
877.4 1
 
3.4%
231.1 1
 
3.4%
249.9 1
 
3.4%
460.0 1
 
3.4%
781.0 1
 
3.4%
465.5 1
 
3.4%
902.7 1
 
3.4%
Other values (19) 19
65.5%
2023-12-12T23:31:13.631123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 29
14.9%
29
14.9%
1 26
13.4%
0 20
10.3%
5 15
7.7%
4 12
6.2%
, 10
 
5.2%
7 10
 
5.2%
2 10
 
5.2%
6 9
 
4.6%
Other values (3) 24
12.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 126
64.9%
Other Punctuation 39
 
20.1%
Space Separator 29
 
14.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 26
20.6%
0 20
15.9%
5 15
11.9%
4 12
9.5%
7 10
 
7.9%
2 10
 
7.9%
6 9
 
7.1%
8 9
 
7.1%
3 8
 
6.3%
9 7
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 29
74.4%
, 10
 
25.6%
Space Separator
ValueCountFrequency (%)
29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 194
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 29
14.9%
29
14.9%
1 26
13.4%
0 20
10.3%
5 15
7.7%
4 12
6.2%
, 10
 
5.2%
7 10
 
5.2%
2 10
 
5.2%
6 9
 
4.6%
Other values (3) 24
12.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 194
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 29
14.9%
29
14.9%
1 26
13.4%
0 20
10.3%
5 15
7.7%
4 12
6.2%
, 10
 
5.2%
7 10
 
5.2%
2 10
 
5.2%
6 9
 
4.6%
Other values (3) 24
12.4%

모태약정액(억원)
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean115.64138
Minimum8.8
Maximum363
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T23:31:13.746457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.8
5-th percentile21.56
Q151
median88
Q3176
95-th percentile273.7
Maximum363
Range354.2
Interquartile range (IQR)125

Descriptive statistics

Standard deviation88.396358
Coefficient of variation (CV)0.76440076
Kurtosis0.8739953
Mean115.64138
Median Absolute Deviation (MAD)39.6
Skewness1.1804723
Sum3353.6
Variance7813.9161
MonotonicityNot monotonic
2023-12-12T23:31:13.859783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
88.0 4
 
13.8%
220.0 3
 
10.3%
110.0 3
 
10.3%
44.0 2
 
6.9%
27.5 2
 
6.9%
17.6 1
 
3.4%
95.7 1
 
3.4%
181.5 1
 
3.4%
48.4 1
 
3.4%
100.0 1
 
3.4%
Other values (10) 10
34.5%
ValueCountFrequency (%)
8.8 1
 
3.4%
17.6 1
 
3.4%
27.5 2
6.9%
44.0 2
6.9%
48.4 1
 
3.4%
51.0 1
 
3.4%
52.8 1
 
3.4%
55.0 1
 
3.4%
79.3 1
 
3.4%
88.0 4
13.8%
ValueCountFrequency (%)
363.0 1
 
3.4%
287.5 1
 
3.4%
253.0 1
 
3.4%
220.0 3
10.3%
181.5 1
 
3.4%
176.0 1
 
3.4%
110.0 3
10.3%
100.0 1
 
3.4%
99.0 1
 
3.4%
95.7 1
 
3.4%

Interactions

2023-12-12T23:31:11.317359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:31:13.946409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
펀드명운용사명운용사 국가결성총액(억원)모태약정액(억원)
펀드명1.0001.0001.0001.0001.000
운용사명1.0001.0001.0001.0000.925
운용사 국가1.0001.0001.0001.0000.857
결성총액(억원)1.0001.0001.0001.0001.000
모태약정액(억원)1.0000.9250.8571.0001.000
2023-12-12T23:31:14.038128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
모태약정액(억원)운용사 국가
모태약정액(억원)1.0000.509
운용사 국가0.5091.000

Missing values

2023-12-12T23:31:11.473843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:31:11.587258image/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

펀드명운용사명운용사 국가결성총액(억원)모태약정액(억원)
0BRV Lotus Fund 2012, L.P.BlueRun Ventures미국1,944.488.0
1Altos Korea Opportunity Fund, L.P.Altos Ventures미국660.052.8
2Big Basin Fund I, L.P.Big Basin Capital미국150.08.8
3Storm Ventures Fund V, L.P.Storm Ventures미국1,951.417.6
4500 Kimchi, L.P.500 Startups미국133.651.0
5Draper Athena, L.P.Draper Athena미국-중국722.5287.5
6Strong Seed Fund II, L.P.Strong Ventures미국165.544.0
7Asset Management Ventures IV, L.P.Asset Management Ventures미국284.527.5
8Top Tier Strategic Investment Fund, L.P.Top Tier Capital Partners미국1,180.679.3
9Shenzhen China-Korea Industrial Investment Fund, L.P.FortuneLink&SV중국1,100.0363.0
펀드명운용사명운용사 국가결성총액(억원)모태약정액(억원)
19Entrepreneurs Expansion Fund III, L.P.Entrepreneurs Roundtable Accelerator미국285.044.0
20Golden Gate Ventures K9, L.P.Golden Gate Ventures싱가포르-중국902.755.0
21Angel Ventures Pacific Alliance Fund II Limited PartnershipAngel Ventures멕시코465.588.0
22Kensington-SV Global Innovations LP에스브이-Kensington한국-미국781.0253.0
23Strong Seed Fund III, L.P.Strong Ventures미국460.0176.0
24Line Games-True-Kona Global Fund Limited Partnership코나벤처-True Incube한국-태국249.9100.0
25500 Startups Korea II, L.P.500 Startups미국231.188.0
26Partech Entrepreneur Fund III FPCIPartech Partners SAS프랑스877.448.4
27LC Fund VIII (Korea),L.P.Legend Capital중국555.6220.0
28Northzone IX L.P.Northzone Ventures스웨덴4,917.2181.5