Overview

Dataset statistics

Number of variables8
Number of observations167
Missing cells224
Missing cells (%)16.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.4 KiB
Average record size in memory69.8 B

Variable types

Numeric4
Text2
Categorical2

Dataset

Description서울올림픽기념국민체육진흥공단 스포츠산업 R&D 지원실적(연도, 주관, 사업명, 지원금, 공모형태 등)입니다.
Author서울올림픽기념국민체육진흥공단
URLhttps://www.data.go.kr/data/15044467/fileData.do

Alerts

1년차 지원금(억원) is highly overall correlated with 2년차 지원금(억원) and 1 other fieldsHigh correlation
2년차 지원금(억원) is highly overall correlated with 1년차 지원금(억원) and 1 other fieldsHigh correlation
3년차 지원금(억원) is highly overall correlated with 1년차 지원금(억원) and 2 other fieldsHigh correlation
공모형태 is highly overall correlated with 3년차 지원금(억원)High correlation
4년차 지원금(억원) is highly imbalanced (94.7%)Imbalance
2년차 지원금(억원) has 78 (46.7%) missing valuesMissing
3년차 지원금(억원) has 146 (87.4%) missing valuesMissing
사 업 명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:30:25.530966
Analysis finished2023-12-12 22:30:28.303455
Duration2.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct14
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.9581
Minimum2007
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T07:30:28.370204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2007
Q12009
median2014
Q32016
95-th percentile2019
Maximum2020
Range13
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.8454374
Coefficient of variation (CV)0.0019103415
Kurtosis-1.1200228
Mean2012.9581
Median Absolute Deviation (MAD)3
Skewness-0.0088257265
Sum336164
Variance14.787389
MonotonicityIncreasing
2023-12-13T07:30:28.500611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2015 25
15.0%
2008 22
13.2%
2014 19
11.4%
2016 16
9.6%
2007 12
7.2%
2009 12
7.2%
2012 12
7.2%
2017 10
 
6.0%
2019 9
 
5.4%
2010 8
 
4.8%
Other values (4) 22
13.2%
ValueCountFrequency (%)
2007 12
7.2%
2008 22
13.2%
2009 12
7.2%
2010 8
 
4.8%
2011 8
 
4.8%
2012 12
7.2%
2013 4
 
2.4%
2014 19
11.4%
2015 25
15.0%
2016 16
9.6%
ValueCountFrequency (%)
2020 7
 
4.2%
2019 9
 
5.4%
2018 3
 
1.8%
2017 10
 
6.0%
2016 16
9.6%
2015 25
15.0%
2014 19
11.4%
2013 4
 
2.4%
2012 12
7.2%
2011 8
 
4.8%

주관
Text

Distinct149
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T07:30:28.713873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length11
Mean length7.4191617
Min length2

Characters and Unicode

Total characters1239
Distinct characters214
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)83.2%

Sample

1st row한국생산기술연구원
2nd row한국생산기술연구원
3rd row재활공학연구소
4th row티에스메디텍
5th row에스앤에스케어
ValueCountFrequency (%)
산학협력단 16
 
8.5%
한국전자통신연구원 6
 
3.2%
한국과학기술연구원 4
 
2.1%
연세대학교 3
 
1.6%
한국생산기술연구원 3
 
1.6%
건국대학교 3
 
1.6%
포항공대산학협력단 2
 
1.1%
대한장애인체육회 2
 
1.1%
주)디자인파크개발 2
 
1.1%
재활공학연구소 2
 
1.1%
Other values (140) 145
77.1%
2023-12-13T07:30:29.077700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 64
 
5.2%
㈜ 48
 
3.9%
대 43
 
3.5%
주 42
 
3.4%
) 39
 
3.1%
( 38
 
3.1%
산 37
 
3.0%
스 32
 
2.6%
이 30
 
2.4%
단 30
 
2.4%
Other values (204) 836
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1074
86.7%
Other Symbol 48
 
3.9%
Close Punctuation 39
 
3.1%
Open Punctuation 38
 
3.1%
Space Separator 24
 
1.9%
Uppercase Letter 15
 
1.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 64
 
6.0%
대 43
 
4.0%
주 42
 
3.9%
산 37
 
3.4%
스 32
 
3.0%
이 30
 
2.8%
단 30
 
2.8%
협 30
 
2.8%
력 29
 
2.7%
교 27
 
2.5%
Other values (189) 710
66.1%
Uppercase Letter
ValueCountFrequency (%)
S 4
26.7%
C 2
13.3%
Y 2
13.3%
M 1
 
6.7%
V 1
 
6.7%
P 1
 
6.7%
J 1
 
6.7%
E 1
 
6.7%
H 1
 
6.7%
T 1
 
6.7%
Other Symbol
ValueCountFrequency (%)
㈜ 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1122
90.6%
Common 102
 
8.2%
Latin 15
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 64
 
5.7%
㈜ 48
 
4.3%
대 43
 
3.8%
주 42
 
3.7%
산 37
 
3.3%
스 32
 
2.9%
이 30
 
2.7%
단 30
 
2.7%
협 30
 
2.7%
력 29
 
2.6%
Other values (190) 737
65.7%
Latin
ValueCountFrequency (%)
S 4
26.7%
C 2
13.3%
Y 2
13.3%
M 1
 
6.7%
V 1
 
6.7%
P 1
 
6.7%
J 1
 
6.7%
E 1
 
6.7%
H 1
 
6.7%
T 1
 
6.7%
Common
ValueCountFrequency (%)
) 39
38.2%
( 38
37.3%
24
23.5%
- 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1074
86.7%
ASCII 117
 
9.4%
None 48
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 64
 
6.0%
대 43
 
4.0%
주 42
 
3.9%
산 37
 
3.4%
스 32
 
3.0%
이 30
 
2.8%
단 30
 
2.8%
협 30
 
2.8%
력 29
 
2.7%
교 27
 
2.5%
Other values (189) 710
66.1%
None
ValueCountFrequency (%)
㈜ 48
100.0%
ASCII
ValueCountFrequency (%)
) 39
33.3%
( 38
32.5%
24
20.5%
S 4
 
3.4%
C 2
 
1.7%
Y 2
 
1.7%
M 1
 
0.9%
V 1
 
0.9%
P 1
 
0.9%
J 1
 
0.9%
Other values (4) 4
 
3.4%

사 업 명
Text

UNIQUE 

Distinct167
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T07:30:29.433739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length46
Mean length32.431138
Min length8

Characters and Unicode

Total characters5416
Distinct characters431
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique167 ?
Unique (%)100.0%

Sample

1st row첨단체력측정 및 평가 기반기술개발
2nd row고령자용 스포츠용품 기반기술개발
3rd row보급형 장애인 스포츠 보조기구 핵심기술 개발
4th row고령자 음파진동 레그프레스 시스템 개발
5th row고령자용 신종 운동기구 핵심기술개발
ValueCountFrequency (%)
개발 122
 
9.2%
위한 48
 
3.6%
및 43
 
3.3%
스포츠 28
 
2.1%
시스템 26
 
2.0%
기술 26
 
2.0%
스마트 21
 
1.6%
기반 18
 
1.4%
이용한 15
 
1.1%
서비스 13
 
1.0%
Other values (692) 959
72.7%
2023-12-13T07:30:29.965740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1157
 
21.4%
스 197
 
3.6%
기 158
 
2.9%
개 155
 
2.9%
발 154
 
2.8%
한 87
 
1.6%
이 81
 
1.5%
용 78
 
1.4%
츠 74
 
1.4%
포 73
 
1.3%
Other values (421) 3202
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3966
73.2%
Space Separator 1157
 
21.4%
Lowercase Letter 150
 
2.8%
Uppercase Letter 95
 
1.8%
Decimal Number 17
 
0.3%
Other Punctuation 12
 
0.2%
Close Punctuation 5
 
0.1%
Dash Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%
Initial Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 197
 
5.0%
기 158
 
4.0%
개 155
 
3.9%
발 154
 
3.9%
한 87
 
2.2%
이 81
 
2.0%
용 78
 
2.0%
츠 74
 
1.9%
포 73
 
1.8%
동 67
 
1.7%
Other values (361) 2842
71.7%
Lowercase Letter
ValueCountFrequency (%)
e 26
17.3%
r 15
10.0%
t 12
 
8.0%
a 12
 
8.0%
n 10
 
6.7%
i 10
 
6.7%
c 10
 
6.7%
l 9
 
6.0%
m 8
 
5.3%
o 8
 
5.3%
Other values (12) 30
20.0%
Uppercase Letter
ValueCountFrequency (%)
I 15
15.8%
T 13
13.7%
S 10
10.5%
D 10
10.5%
F 7
 
7.4%
C 6
 
6.3%
M 5
 
5.3%
E 4
 
4.2%
R 4
 
4.2%
A 3
 
3.2%
Other values (9) 18
18.9%
Decimal Number
ValueCountFrequency (%)
3 9
52.9%
1 2
 
11.8%
4 2
 
11.8%
2 1
 
5.9%
5 1
 
5.9%
8 1
 
5.9%
0 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/ 6
50.0%
& 2
 
16.7%
, 2
 
16.7%
: 2
 
16.7%
Initial Punctuation
ValueCountFrequency (%)
“ 1
50.0%
‘ 1
50.0%
Final Punctuation
ValueCountFrequency (%)
” 1
50.0%
’ 1
50.0%
Space Separator
ValueCountFrequency (%)
1157
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3966
73.2%
Common 1205
 
22.2%
Latin 245
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 197
 
5.0%
기 158
 
4.0%
개 155
 
3.9%
발 154
 
3.9%
한 87
 
2.2%
이 81
 
2.0%
용 78
 
2.0%
츠 74
 
1.9%
포 73
 
1.8%
동 67
 
1.7%
Other values (361) 2842
71.7%
Latin
ValueCountFrequency (%)
e 26
 
10.6%
I 15
 
6.1%
r 15
 
6.1%
T 13
 
5.3%
t 12
 
4.9%
a 12
 
4.9%
n 10
 
4.1%
i 10
 
4.1%
S 10
 
4.1%
c 10
 
4.1%
Other values (31) 112
45.7%
Common
ValueCountFrequency (%)
1157
96.0%
3 9
 
0.7%
/ 6
 
0.5%
) 5
 
0.4%
- 5
 
0.4%
( 5
 
0.4%
& 2
 
0.2%
, 2
 
0.2%
: 2
 
0.2%
1 2
 
0.2%
Other values (9) 10
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3966
73.2%
ASCII 1446
 
26.7%
Punctuation 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1157
80.0%
e 26
 
1.8%
I 15
 
1.0%
r 15
 
1.0%
T 13
 
0.9%
t 12
 
0.8%
a 12
 
0.8%
n 10
 
0.7%
i 10
 
0.7%
S 10
 
0.7%
Other values (46) 166
 
11.5%
Hangul
ValueCountFrequency (%)
스 197
 
5.0%
기 158
 
4.0%
개 155
 
3.9%
발 154
 
3.9%
한 87
 
2.2%
이 81
 
2.0%
용 78
 
2.0%
츠 74
 
1.9%
포 73
 
1.8%
동 67
 
1.7%
Other values (361) 2842
71.7%
Punctuation
ValueCountFrequency (%)
“ 1
25.0%
” 1
25.0%
’ 1
25.0%
‘ 1
25.0%

1년차 지원금(억원)
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)24.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0129371
Minimum0.5
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T07:30:30.085115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile0.9472
Q11.225
median2
Q34
95-th percentile9
Maximum15
Range14.5
Interquartile range (IQR)2.775

Descriptive statistics

Standard deviation2.7045292
Coefficient of variation (CV)0.89763878
Kurtosis4.4054852
Mean3.0129371
Median Absolute Deviation (MAD)1
Skewness2.0316577
Sum503.1605
Variance7.3144783
MonotonicityNot monotonic
2023-12-13T07:30:30.197849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
2.0 47
28.1%
1.0 17
 
10.2%
0.95 12
 
7.2%
5.0 11
 
6.6%
3.0 8
 
4.8%
1.9 7
 
4.2%
4.0 7
 
4.2%
10.0 6
 
3.6%
7.5 4
 
2.4%
7.0 4
 
2.4%
Other values (31) 44
26.3%
ValueCountFrequency (%)
0.5 1
 
0.6%
0.7 1
 
0.6%
0.73 1
 
0.6%
0.75 1
 
0.6%
0.86 1
 
0.6%
0.897 1
 
0.6%
0.94 2
 
1.2%
0.946 1
 
0.6%
0.95 12
7.2%
0.968 1
 
0.6%
ValueCountFrequency (%)
15.0 2
 
1.2%
10.0 6
3.6%
9.0 2
 
1.2%
8.0 1
 
0.6%
7.975 2
 
1.2%
7.5 4
 
2.4%
7.0 4
 
2.4%
6.38 1
 
0.6%
5.86 1
 
0.6%
5.0 11
6.6%

2년차 지원금(억원)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct23
Distinct (%)25.8%
Missing78
Missing (%)46.7%
Infinite0
Infinite (%)0.0%
Mean4.7128652
Minimum0.095
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T07:30:30.315033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.095
5-th percentile0.97
Q12
median4
Q37
95-th percentile10
Maximum15
Range14.905
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.2607458
Coefficient of variation (CV)0.69188183
Kurtosis-0.087812553
Mean4.7128652
Median Absolute Deviation (MAD)2
Skewness0.87052349
Sum419.445
Variance10.632463
MonotonicityNot monotonic
2023-12-13T07:30:30.435151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2.0 23
 
13.8%
5.0 14
 
8.4%
10.0 11
 
6.6%
4.0 8
 
4.8%
3.8 5
 
3.0%
8.83 3
 
1.8%
9.0 3
 
1.8%
7.0 3
 
1.8%
3.0 3
 
1.8%
0.95 3
 
1.8%
Other values (13) 13
 
7.8%
(Missing) 78
46.7%
ValueCountFrequency (%)
0.095 1
 
0.6%
0.73 1
 
0.6%
0.95 3
 
1.8%
1.0 1
 
0.6%
1.065 1
 
0.6%
1.4 1
 
0.6%
1.5 1
 
0.6%
1.605 1
 
0.6%
1.8 1
 
0.6%
2.0 23
13.8%
ValueCountFrequency (%)
15.0 1
 
0.6%
12.0 1
 
0.6%
10.0 11
6.6%
9.0 3
 
1.8%
8.83 3
 
1.8%
8.0 1
 
0.6%
7.0 3
 
1.8%
6.0 1
 
0.6%
5.91 1
 
0.6%
5.0 14
8.4%

3년차 지원금(억원)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)52.4%
Missing146
Missing (%)87.4%
Infinite0
Infinite (%)0.0%
Mean7.2409524
Minimum2
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T07:30:30.545542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14.9
median7
Q310
95-th percentile12
Maximum15
Range13
Interquartile range (IQR)5.1

Descriptive statistics

Standard deviation3.5562718
Coefficient of variation (CV)0.49113316
Kurtosis-0.45071658
Mean7.2409524
Median Absolute Deviation (MAD)3
Skewness0.16374194
Sum152.06
Variance12.647069
MonotonicityNot monotonic
2023-12-13T07:30:30.651987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
10.0 6
 
3.6%
7.0 4
 
2.4%
2.0 3
 
1.8%
8.25 1
 
0.6%
3.0 1
 
0.6%
15.0 1
 
0.6%
5.0 1
 
0.6%
4.0 1
 
0.6%
4.9 1
 
0.6%
5.91 1
 
0.6%
(Missing) 146
87.4%
ValueCountFrequency (%)
2.0 3
1.8%
3.0 1
 
0.6%
4.0 1
 
0.6%
4.9 1
 
0.6%
5.0 1
 
0.6%
5.91 1
 
0.6%
7.0 4
2.4%
8.25 1
 
0.6%
10.0 6
3.6%
12.0 1
 
0.6%
ValueCountFrequency (%)
15.0 1
 
0.6%
12.0 1
 
0.6%
10.0 6
3.6%
8.25 1
 
0.6%
7.0 4
2.4%
5.91 1
 
0.6%
5.0 1
 
0.6%
4.9 1
 
0.6%
4.0 1
 
0.6%
3.0 1
 
0.6%

4년차 지원금(억원)
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
166 
15
 
1

Length

Max length4
Median length4
Mean length3.988024
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 166
99.4%
15 1
 
0.6%

Length

2023-12-13T07:30:30.766469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:30:30.867111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 166
99.4%
15 1
 
0.6%

공모형태
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
자유
95 
지정
50 
정책
11 
자유(전략)
 
5
자유(일반)
 
4
Other values (2)
 
2

Length

Max length6
Median length2
Mean length2.245509
Min length2

Unique

Unique2 ?
Unique (%)1.2%

Sample

1st row정책
2nd row정책
3rd row지정
4th row지정
5th row지정

Common Values

ValueCountFrequency (%)
자유 95
56.9%
지정 50
29.9%
정책 11
 
6.6%
자유(전략) 5
 
3.0%
자유(일반) 4
 
2.4%
사업화 1
 
0.6%
지정(품목) 1
 
0.6%

Length

2023-12-13T07:30:30.962027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:30:31.062829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자유 95
56.9%
지정 50
29.9%
정책 11
 
6.6%
자유(전략 5
 
3.0%
자유(일반 4
 
2.4%
사업화 1
 
0.6%
지정(품목 1
 
0.6%

Interactions

2023-12-13T07:30:27.249020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:26.054459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:26.469532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:26.858963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:27.358508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:26.153782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:26.557189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:26.969561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:27.462389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:26.255817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:26.652999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:27.074376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:27.563439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:26.362277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:26.755139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:27.166766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:30:31.148684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도1년차 지원금(억원)2년차 지원금(억원)3년차 지원금(억원)공모형태
연도1.0000.5710.6030.5770.418
1년차 지원금(억원)0.5711.0000.8320.8170.684
2년차 지원금(억원)0.6030.8321.0000.8940.639
3년차 지원금(억원)0.5770.8170.8941.0000.826
공모형태0.4180.6840.6390.8261.000
2023-12-13T07:30:31.249532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공모형태4년차 지원금(억원)
공모형태1.000NaN
4년차 지원금(억원)NaN1.000
2023-12-13T07:30:31.330459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도1년차 지원금(억원)2년차 지원금(억원)3년차 지원금(억원)4년차 지원금(억원)공모형태
연도1.0000.4800.4900.097NaN0.225
1년차 지원금(억원)0.4801.0000.9130.898NaN0.453
2년차 지원금(억원)0.4900.9131.0000.945NaN0.426
3년차 지원금(억원)0.0970.8980.9451.000NaN0.524
4년차 지원금(억원)NaNNaNNaNNaN1.000NaN
공모형태0.2250.4530.4260.524NaN1.000

Missing values

2023-12-13T07:30:27.974651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:30:28.103881image/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.
2023-12-13T07:30:28.233987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연도주관사 업 명1년차 지원금(억원)2년차 지원금(억원)3년차 지원금(억원)4년차 지원금(억원)공모형태
02007한국생산기술연구원첨단체력측정 및 평가 기반기술개발2.02.02.0<NA>정책
12007한국생산기술연구원고령자용 스포츠용품 기반기술개발2.02.02.0<NA>정책
22007재활공학연구소보급형 장애인 스포츠 보조기구 핵심기술 개발1.98<NA><NA><NA>지정
32007티에스메디텍고령자 음파진동 레그프레스 시스템 개발2.0<NA><NA><NA>지정
42007에스앤에스케어고령자용 신종 운동기구 핵심기술개발2.0<NA><NA><NA>지정
52007대종체육건설스포츠인조잔디용 소재 신뢰성 평가기술개발1.77<NA><NA><NA>지정
62007휴모닉등속성 근력운동기능을 갖는 지능형 전자식 헬스 운동기기 개발0.897<NA><NA><NA>자유
72007디엠비에이치감성골프시스템 구현을 위한 3차원 센서기술 개발1.0<NA><NA><NA>자유
82007리임코리아이중 충격드라이버 개발1.0<NA><NA><NA>자유
92007택트인조잔디구장 충격성능 자동 평가 시스템 개발1.0<NA><NA><NA>자유
연도주관사 업 명1년차 지원금(억원)2년차 지원금(억원)3년차 지원금(억원)4년차 지원금(억원)공모형태
1572019㈜리얼디자인테크리얼사이클링 기반 헬스케어 플랫폼 및 콘텐츠 개발1.93.8<NA><NA>자유
1582019㈜브이씨정밀 GPS와 관성센서 통합기술을 활용한 고정밀 경기력 측정 기술 및 스포츠 트랙커 개발4.4158.83<NA><NA>자유
1592019㈜아이온커뮤니케이션즈수출형 스포츠 데이터 수집 및 서비스 플랫폼 개발4.4158.83<NA><NA>자유
1602020국민대산학협력단실전형 태권도 경기를 위한 스마트 전자 판정 시스템 개발6.389.0<NA><NA>지정
1612020한국전자통신연구원안전한 실내 스포츠 활동을 위한 지능형 실내 환경 및 안전관리 기술개발7.97512.012.0<NA>지정
1622020㈜디랙스개인 맞춤형 생애주기 스마트 피트니스 서비스 개발7.97510.010.0<NA>지정
1632020동국대산학협력단발달장애 아동의 건강증진을 위한 운동치료 기술 개발5.867.07.0<NA>지정
1642020㈜모아이스골프픽스 3D : On-device 인공지능 기반 3차원 골프 스윙 분석 기술 및 인공지능 클럽 피팅 기술 연구 개발과 상용화 서비스 제작1.93.8<NA><NA>자유
1652020㈜비플렉스생체역학 달리기/보행 자세분석 기술 기반 히어러블 자세 코칭 및 신체나이 평가 기기 개발1.93.8<NA><NA>자유
1662020㈜진글라이더패러글라이더 공력성능 핵심기술 개발4.418.83<NA><NA>자유