Overview

Dataset statistics

Number of variables9
Number of observations336
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.4 KiB
Average record size in memory80.4 B

Variable types

Categorical1
Numeric8

Dataset

Description국가과학기술연구회 소관 출연(연)의 특허 통계(출원(국내외), 등록(국내외), 연도별, 기관별)에 대한 정보입니다.
Author국가과학기술연구회
URLhttps://www.data.go.kr/data/15007235/fileData.do

Alerts

출원 소계 is highly overall correlated with 출원(국내) and 5 other fieldsHigh correlation
출원(국내) is highly overall correlated with 출원 소계 and 6 other fieldsHigh correlation
출원(국외 PCT) is highly overall correlated with 출원 소계 and 5 other fieldsHigh correlation
출원(국외 일반) is highly overall correlated with 출원 소계 and 5 other fieldsHigh correlation
등록 소계 is highly overall correlated with 출원 소계 and 5 other fieldsHigh correlation
등록(국내) is highly overall correlated with 출원 소계 and 5 other fieldsHigh correlation
등록(국외) is highly overall correlated with 출원 소계 and 5 other fieldsHigh correlation
기관명 is highly overall correlated with 출원(국내)High correlation
출원(국외 PCT) has 36 (10.7%) zerosZeros
출원(국외 일반) has 38 (11.3%) zerosZeros
등록 소계 has 4 (1.2%) zerosZeros
등록(국내) has 4 (1.2%) zerosZeros
등록(국외) has 41 (12.2%) zerosZeros

Reproduction

Analysis started2023-12-12 17:22:44.879642
Analysis finished2023-12-12 17:22:52.783536
Duration7.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관명
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
KIST
 
14
기초(연)
 
14
핵융합(연)
 
14
천문(연)
 
14
생명(연)
 
14
Other values (19)
266 

Length

Max length6
Median length5
Mean length5
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KIST 14
 
4.2%
기초(연) 14
 
4.2%
핵융합(연) 14
 
4.2%
천문(연) 14
 
4.2%
생명(연) 14
 
4.2%
KISTI 14
 
4.2%
한의학(연) 14
 
4.2%
생기원 14
 
4.2%
ETRI 14
 
4.2%
국보(연) 14
 
4.2%
Other values (14) 196
58.3%

Length

2023-12-13T02:22:52.847664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
kist 14
 
4.2%
기초(연 14
 
4.2%
안전(연 14
 
4.2%
화학(연 14
 
4.2%
전기(연 14
 
4.2%
에너지(연 14
 
4.2%
항우(연 14
 
4.2%
재료(연 14
 
4.2%
기계(연 14
 
4.2%
지자(연 14
 
4.2%
Other values (14) 196
58.3%

년도
Real number (ℝ)

Distinct14
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.5
Minimum2008
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T02:22:52.943956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2008
Q12011
median2014.5
Q32018
95-th percentile2021
Maximum2021
Range13
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.037141
Coefficient of variation (CV)0.0020040412
Kurtosis-1.2124712
Mean2014.5
Median Absolute Deviation (MAD)3.5
Skewness0
Sum676872
Variance16.298507
MonotonicityNot monotonic
2023-12-13T02:22:53.062628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2008 24
 
7.1%
2009 24
 
7.1%
2010 24
 
7.1%
2011 24
 
7.1%
2012 24
 
7.1%
2013 24
 
7.1%
2014 24
 
7.1%
2015 24
 
7.1%
2016 24
 
7.1%
2017 24
 
7.1%
Other values (4) 96
28.6%
ValueCountFrequency (%)
2008 24
7.1%
2009 24
7.1%
2010 24
7.1%
2011 24
7.1%
2012 24
7.1%
2013 24
7.1%
2014 24
7.1%
2015 24
7.1%
2016 24
7.1%
2017 24
7.1%
ValueCountFrequency (%)
2021 24
7.1%
2020 24
7.1%
2019 24
7.1%
2018 24
7.1%
2017 24
7.1%
2016 24
7.1%
2015 24
7.1%
2014 24
7.1%
2013 24
7.1%
2012 24
7.1%

출원 소계
Real number (ℝ)

HIGH CORRELATION 

Distinct257
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean346.59821
Minimum0
Maximum4310
Zeros3
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T02:22:53.184931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.5
Q169.75
median200
Q3317
95-th percentile782
Maximum4310
Range4310
Interquartile range (IQR)247.25

Descriptive statistics

Standard deviation648.19644
Coefficient of variation (CV)1.8701667
Kurtosis18.251533
Mean346.59821
Median Absolute Deviation (MAD)123.5
Skewness4.2361763
Sum116457
Variance420158.63
MonotonicityNot monotonic
2023-12-13T02:22:53.313982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
306 4
 
1.2%
7 4
 
1.2%
200 4
 
1.2%
5 4
 
1.2%
86 4
 
1.2%
39 3
 
0.9%
20 3
 
0.9%
12 3
 
0.9%
0 3
 
0.9%
13 3
 
0.9%
Other values (247) 301
89.6%
ValueCountFrequency (%)
0 3
0.9%
2 1
 
0.3%
3 3
0.9%
4 1
 
0.3%
5 4
1.2%
6 1
 
0.3%
7 4
1.2%
9 1
 
0.3%
10 1
 
0.3%
11 1
 
0.3%
ValueCountFrequency (%)
4310 1
0.3%
3871 1
0.3%
3755 1
0.3%
3670 1
0.3%
3574 1
0.3%
3546 1
0.3%
3225 1
0.3%
3223 1
0.3%
3168 1
0.3%
2900 1
0.3%

출원(국내)
Real number (ℝ)

HIGH CORRELATION 

Distinct225
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean245.4881
Minimum0
Maximum2244
Zeros3
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T02:22:53.446799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q150
median165
Q3253.25
95-th percentile606.25
Maximum2244
Range2244
Interquartile range (IQR)203.25

Descriptive statistics

Standard deviation397.275
Coefficient of variation (CV)1.6183066
Kurtosis14.785403
Mean245.4881
Median Absolute Deviation (MAD)106
Skewness3.8154093
Sum82484
Variance157827.43
MonotonicityNot monotonic
2023-12-13T02:22:53.958484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
183 6
 
1.8%
39 5
 
1.5%
17 5
 
1.5%
3 5
 
1.5%
169 5
 
1.5%
33 4
 
1.2%
28 4
 
1.2%
172 3
 
0.9%
173 3
 
0.9%
275 3
 
0.9%
Other values (215) 293
87.2%
ValueCountFrequency (%)
0 3
0.9%
2 2
 
0.6%
3 5
1.5%
4 1
 
0.3%
5 2
 
0.6%
6 3
0.9%
7 3
0.9%
9 3
0.9%
10 2
 
0.6%
11 3
0.9%
ValueCountFrequency (%)
2244 1
0.3%
2226 1
0.3%
2199 1
0.3%
2172 1
0.3%
2063 1
0.3%
2034 1
0.3%
2017 1
0.3%
2005 1
0.3%
1999 1
0.3%
1982 1
0.3%

출원(국외 PCT)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct69
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.550595
Minimum0
Maximum481
Zeros36
Zeros (%)10.7%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T02:22:54.130938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median11
Q326
95-th percentile59.25
Maximum481
Range481
Interquartile range (IQR)22

Descriptive statistics

Standard deviation32.514114
Coefficient of variation (CV)1.6630754
Kurtosis122.4267
Mean19.550595
Median Absolute Deviation (MAD)9
Skewness9.1606375
Sum6569
Variance1057.1676
MonotonicityNot monotonic
2023-12-13T02:22:54.333255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36
 
10.7%
11 16
 
4.8%
8 15
 
4.5%
3 15
 
4.5%
5 14
 
4.2%
7 13
 
3.9%
14 13
 
3.9%
1 12
 
3.6%
9 12
 
3.6%
4 11
 
3.3%
Other values (59) 179
53.3%
ValueCountFrequency (%)
0 36
10.7%
1 12
 
3.6%
2 11
 
3.3%
3 15
4.5%
4 11
 
3.3%
5 14
 
4.2%
6 10
 
3.0%
7 13
 
3.9%
8 15
4.5%
9 12
 
3.6%
ValueCountFrequency (%)
481 1
0.3%
175 1
0.3%
105 1
0.3%
102 1
0.3%
82 1
0.3%
77 1
0.3%
72 1
0.3%
69 1
0.3%
66 1
0.3%
65 1
0.3%

출원(국외 일반)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct110
Distinct (%)32.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.559524
Minimum0
Maximum1936
Zeros38
Zeros (%)11.3%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T02:22:54.545516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median19
Q351.5
95-th percentile209.25
Maximum1936
Range1936
Interquartile range (IQR)46.5

Descriptive statistics

Standard deviation243.59405
Coefficient of variation (CV)2.9867027
Kurtosis28.16626
Mean81.559524
Median Absolute Deviation (MAD)17
Skewness5.1584897
Sum27404
Variance59338.062
MonotonicityNot monotonic
2023-12-13T02:22:54.706493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38
 
11.3%
4 14
 
4.2%
1 13
 
3.9%
12 11
 
3.3%
5 10
 
3.0%
8 10
 
3.0%
6 9
 
2.7%
14 9
 
2.7%
11 8
 
2.4%
7 7
 
2.1%
Other values (100) 207
61.6%
ValueCountFrequency (%)
0 38
11.3%
1 13
 
3.9%
2 7
 
2.1%
3 5
 
1.5%
4 14
 
4.2%
5 10
 
3.0%
6 9
 
2.7%
7 7
 
2.1%
8 10
 
3.0%
9 3
 
0.9%
ValueCountFrequency (%)
1936 1
0.3%
1763 1
0.3%
1487 1
0.3%
1448 1
0.3%
1429 1
0.3%
1198 1
0.3%
1172 1
0.3%
982 1
0.3%
960 1
0.3%
912 1
0.3%

등록 소계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct224
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean210.50595
Minimum0
Maximum2136
Zeros4
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T02:22:54.890891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.75
Q143.75
median128.5
Q3246.25
95-th percentile635
Maximum2136
Range2136
Interquartile range (IQR)202.5

Descriptive statistics

Standard deviation315.29328
Coefficient of variation (CV)1.4977879
Kurtosis14.069342
Mean210.50595
Median Absolute Deviation (MAD)91.5
Skewness3.5583519
Sum70730
Variance99409.851
MonotonicityNot monotonic
2023-12-13T02:22:55.067985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37 5
 
1.5%
4 5
 
1.5%
25 4
 
1.2%
0 4
 
1.2%
190 4
 
1.2%
87 4
 
1.2%
48 4
 
1.2%
29 4
 
1.2%
116 4
 
1.2%
85 3
 
0.9%
Other values (214) 295
87.8%
ValueCountFrequency (%)
0 4
1.2%
1 3
0.9%
2 3
0.9%
3 2
 
0.6%
4 5
1.5%
5 1
 
0.3%
6 1
 
0.3%
7 2
 
0.6%
8 3
0.9%
9 2
 
0.6%
ValueCountFrequency (%)
2136 1
0.3%
1852 1
0.3%
1707 1
0.3%
1690 1
0.3%
1600 1
0.3%
1564 1
0.3%
1558 1
0.3%
1550 1
0.3%
1541 1
0.3%
1496 1
0.3%

등록(국내)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct212
Distinct (%)63.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean153.52679
Minimum0
Maximum1241
Zeros4
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T02:22:55.250091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.75
Q134.75
median103
Q3195.25
95-th percentile466
Maximum1241
Range1241
Interquartile range (IQR)160.5

Descriptive statistics

Standard deviation183.90478
Coefficient of variation (CV)1.1978677
Kurtosis11.660166
Mean153.52679
Median Absolute Deviation (MAD)77
Skewness2.9439793
Sum51585
Variance33820.966
MonotonicityNot monotonic
2023-12-13T02:22:55.501196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 5
 
1.5%
21 5
 
1.5%
43 5
 
1.5%
4 5
 
1.5%
20 5
 
1.5%
128 4
 
1.2%
69 4
 
1.2%
0 4
 
1.2%
15 4
 
1.2%
45 4
 
1.2%
Other values (202) 291
86.6%
ValueCountFrequency (%)
0 4
1.2%
1 3
0.9%
2 3
0.9%
3 2
 
0.6%
4 5
1.5%
5 1
 
0.3%
6 2
 
0.6%
7 3
0.9%
8 3
0.9%
9 2
 
0.6%
ValueCountFrequency (%)
1241 1
0.3%
1201 2
0.6%
934 1
0.3%
917 1
0.3%
865 1
0.3%
796 1
0.3%
791 1
0.3%
669 1
0.3%
644 1
0.3%
643 1
0.3%

등록(국외)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct99
Distinct (%)29.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.979167
Minimum0
Maximum957
Zeros41
Zeros (%)12.2%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T02:22:55.713961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median14.5
Q346.25
95-th percentile159.25
Maximum957
Range957
Interquartile range (IQR)43.25

Descriptive statistics

Standard deviation153.91813
Coefficient of variation (CV)2.7013054
Kurtosis21.218087
Mean56.979167
Median Absolute Deviation (MAD)13.5
Skewness4.6224136
Sum19145
Variance23690.791
MonotonicityNot monotonic
2023-12-13T02:22:55.900409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41
 
12.2%
1 17
 
5.1%
2 15
 
4.5%
9 13
 
3.9%
3 12
 
3.6%
4 12
 
3.6%
5 10
 
3.0%
8 9
 
2.7%
15 8
 
2.4%
14 7
 
2.1%
Other values (89) 192
57.1%
ValueCountFrequency (%)
0 41
12.2%
1 17
5.1%
2 15
 
4.5%
3 12
 
3.6%
4 12
 
3.6%
5 10
 
3.0%
6 6
 
1.8%
7 7
 
2.1%
8 9
 
2.7%
9 13
 
3.9%
ValueCountFrequency (%)
957 1
0.3%
935 1
0.3%
918 1
0.3%
911 1
0.3%
893 1
0.3%
881 1
0.3%
810 1
0.3%
741 1
0.3%
705 1
0.3%
699 1
0.3%

Interactions

2023-12-13T02:22:51.920616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:45.211313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:45.994981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:46.997613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:48.020681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:49.135135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:50.256658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:51.146882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:52.006620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:45.335786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:46.086476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:47.094750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:48.164947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:49.293866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:50.380004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:51.278620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:52.087254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:45.422423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:46.169818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:47.238991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:48.323209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:49.424292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:50.492927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:51.389712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:52.178073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:45.527480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:46.248210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:47.335216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:48.456177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:49.543872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:50.585301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:51.503145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:52.263285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:45.621211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:46.339170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:47.454120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:48.595030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:49.670894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:50.700545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:51.585369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:52.354023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:45.723127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:46.444659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:47.603884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:48.758214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:49.843883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:50.823948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:51.681317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:52.429325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:45.806620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:46.524570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:47.730289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:48.885548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:49.971786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:50.916240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:51.757333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:52.509587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:45.893489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:46.910613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:47.867979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:49.003461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:50.116850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:51.035974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:51.842713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:22:56.053575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관명년도출원 소계출원(국내)출원(국외 PCT)출원(국외 일반)등록 소계등록(국내)등록(국외)
기관명1.0000.0000.8110.8990.5010.7590.7760.7760.785
년도0.0001.0000.0000.0000.1110.0810.0000.1860.058
출원 소계0.8110.0001.0000.8300.7740.9600.8540.7870.949
출원(국내)0.8990.0000.8301.0000.7180.8030.9800.8520.797
출원(국외 PCT)0.5010.1110.7740.7181.0000.7220.7350.7000.884
출원(국외 일반)0.7590.0810.9600.8030.7221.0000.8790.7810.963
등록 소계0.7760.0000.8540.9800.7350.8791.0000.8660.832
등록(국내)0.7760.1860.7870.8520.7000.7810.8661.0000.840
등록(국외)0.7850.0580.9490.7970.8840.9630.8320.8401.000
2023-12-13T02:22:56.237061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도출원 소계출원(국내)출원(국외 PCT)출원(국외 일반)등록 소계등록(국내)등록(국외)기관명
년도1.0000.0080.0200.1270.0150.1570.1300.2730.000
출원 소계0.0081.0000.9830.7570.8450.9320.9250.7810.426
출원(국내)0.0200.9831.0000.6860.7600.9270.9330.7220.680
출원(국외 PCT)0.1270.7570.6861.0000.7140.6950.6710.7020.261
출원(국외 일반)0.0150.8450.7600.7141.0000.7940.7490.8350.370
등록 소계0.1570.9320.9270.6950.7941.0000.9900.8430.410
등록(국내)0.1300.9250.9330.6710.7490.9901.0000.7710.420
등록(국외)0.2730.7810.7220.7020.8350.8430.7711.0000.397
기관명0.0000.4260.6800.2610.3700.4100.4200.3971.000

Missing values

2023-12-13T02:22:52.613677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:22:52.733047image/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

기관명년도출원 소계출원(국내)출원(국외 PCT)출원(국외 일반)등록 소계등록(국내)등록(국외)
0KIST20084963124913526719671
1KIST20095963582920920212775
2KIST20105904063714726218676
3KIST20116094332315341733285
4KIST201270745443210509376133
5KIST201371145033228581463118
6KIST201468149124166635455180
7KIST201577658426166498337161
8KIST201672253535152455313142
9KIST201780056346191661504157
기관명년도출원 소계출원(국내)출원(국외 PCT)출원(국외 일반)등록 소계등록(국내)등록(국외)
326원자력(연)201230626383534528362
327원자력(연)201346135579929626036
328원자력(연)2014424330157932928742
329원자력(연)2015291249103232627650
330원자력(연)201630125993331125556
331원자력(연)201722420491126020456
332원자력(연)2018242199172620515847
333원자력(연)2019280218164624419054
334원자력(연)202031625385522516956
335원자력(연)2021309257133921117932