Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
RBC202003_Day2_Period5
Search
sakaue
March 20, 2020
Education
0
35
RBC202003_Day2_Period5
sakaue
March 20, 2020
Tweet
Share
More Decks by sakaue
See All by sakaue
SappoRo.R #11「R によるThe Multilingual Eye-tracking COrpus (MECO) の探索的データ分析」
sakaue
0
81
RBC202003_Day2_Period6
sakaue
0
74
RBC202003_Day2_Period7
sakaue
0
71
Rbootcamp202003_Day2_p8.pdf
sakaue
0
70
RBC202003_Day1_Period1
sakaue
1
58
RBC202003_Day1_Period2
sakaue
0
56
RBC202003_Day1_Period3
sakaue
0
74
RBC202003_Day1_Period4
sakaue
0
41
Other Decks in Education
See All in Education
開発終了後こそ成長のチャンス!プロダクト運用を見送った先のアクションプラン
ohmori_yusuke
2
290
書を持って、自転車で町へ出よう
yuritaco
0
140
ルクソールとツタンカーメン
masakamayama
1
1.2k
HCL Notes/Domino 14.5 EAP Drop1
harunakano
1
160
BrightonSEO, San Diego, CA 2024
mchowning
0
120
LinkedIn
matleenalaakso
0
3.5k
JAWS-UGを通じてアウトプット活動を楽しんでみませんか? #jawsug_tochigi
masakiokuda
0
170
複式簿記から純資産を排除する/eliminate_net_assets_from_double-entry_bookkeeping
florets1
0
300
地図を活用した関西シビックテック事例紹介
barsaka2
0
170
The Task is not the End: The Role of Task Repetition and Sequencing In Language Teaching
uranoken
0
300
中野区ミライ★ライター倶楽部presents『MINT』
nakamuramikumirai
0
640
Web 2.0 Patterns and Technologies - Lecture 8 - Web Technologies (1019888BNR)
signer
PRO
0
2.5k
Featured
See All Featured
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
132
33k
Fireside Chat
paigeccino
34
3.2k
Into the Great Unknown - MozCon
thekraken
35
1.6k
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
30
4.6k
Responsive Adventures: Dirty Tricks From The Dark Corners of Front-End
smashingmag
251
21k
How to train your dragon (web standard)
notwaldorf
91
5.8k
Visualizing Your Data: Incorporating Mongo into Loggly Infrastructure
mongodb
44
9.4k
Fantastic passwords and where to find them - at NoRuKo
philnash
51
3k
The Cult of Friendly URLs
andyhume
78
6.2k
Adopting Sorbet at Scale
ufuk
74
9.2k
jQuery: Nuts, Bolts and Bling
dougneiner
63
7.6k
The Invisible Side of Design
smashingmag
299
50k
Transcript
2020-03-20 ୈ5ݶ σʔλͷཁ bootcamp
Agenda 1. σʔλͷཁͷඞཁੑ (5) 2. ϕΫτϧΛͬͨཁ (20) 3. ߦྻΛͬͨཁ (20)
4. ԋशʹ͙࣍ԋश (45)
Agenda 1. σʔλͷཁͷඞཁੑ (5) 2. ϕΫτϧΛͬͨཁ (20) 3. ߦྻΛͬͨཁ (20)
4. ԋशʹ͙࣍ԋश (45)
1. σʔλͷཁͷඞཁੑ • σʔλΛूΊ͚ͨͩͰԿஅͰ͖ͳ͍ • σʔλΛཁʢཁʣΛ͢Δ͜ͱͰɼશମ͕ Ͳ͏ͳ͍ͬͯͯɼΒ͖͕ͭͲ͏ͳ͍ͬͯ Δ͔͕ѲͰ͖Δ • தؒςετͰऔͬͨ55ྑ͍ʁɼѱ͍ʁ
• ظςετͷฏۉ͕80ͷ߹ɼશମతʹྑ͍Ͱ͖͙͍͋ʁ • ฏۉɾΒ͖ͭʢSDʣʹΑΔʢ͠ɼςετͷ༰ ʹΑΔʢ͠ɼԿΛ͔֬Ί͍͔ͨʹΑΔʣʣ
Agenda 1. σʔλͷཁͷඞཁੑ (5) 2. ϕΫτϧΛͬͨཁ (20) 3. ߦྻΛͬͨཁ (20)
4. ԋशʹ͙࣍ԋश (45)
Agenda 1. σʔλͷཁͷඞཁੑ (5) 2. ϕΫτϧΛͬͨཁ (20) 3. ߦྻΛͬͨཁ (20)
4. ԋशʹ͙࣍ԋश (45)
• sum() ؔ • x <- c(1, 2, 3, 4,
5) • sum(x) • sum(x[2 : 4]) • ϕΫτϧͷ2൪͔Β4൪ͷཁૉͷ૯ • y <- c(1:1000) • sum(y) • sum(y[27:89]) 2. ϕΫτϧΛͬͨཁ
• mean() ؔ: ฏۉΛٻΊΔ • ฏۉ: σʔλͷ૯ΛσʔλͷݸͰׂͬͨ • mean(x); mean(y)
• median() ؔ: தԝΛٻΊΔ • தԝ: খ͍͞ॱʹฒͨ࣌ʹਅΜதͷॱҐʹ͘Δ • median(x); median(y) • ฏۉͷ᠘ • ۃͳ͕ࠞ͟ΔͱӨڹΛड͚ͯ͠·͏ • a <- c(100, 200, 300, 400, 500) • mean(a); median(a) • b <- c(100, 200, 300, 400, 5000) • mean(b); median(b) 2. ϕΫτϧΛͬͨཁ
• max() ؔ: ࠷େΛٻΊΔ • min() ؔ: ࠷খΛٻΊΔ • var()
ؔ: ࢄΛٻΊΔ • sd() ؔ: ඪ४ภࠩΛٻΊΔ • summary() ؔ: ཁ౷ܭྔΛҰʹٻΊΔ • ࠷খ, தԝ, ฏۉ, ࠷େ, Լଆ25%, ্ଆ25% • max(x); max(y) • min(x); min(y) • var(x);var(y) • sd(x); sd(y) • summary(x); summary(y) 2. ϕΫτϧΛͬͨཁ
Agenda 1. σʔλͷཁͷඞཁੑ (5) 2. ϕΫτϧΛͬͨཁ (20) 3. ߦྻΛͬͨཁ (20)
4. ԋशʹ͙࣍ԋश (45)
Agenda 1. σʔλͷཁͷඞཁੑ (5) 2. ϕΫτϧΛͬͨཁ (20) 3. ߦྻΛͬͨཁ (20)
4. ԋशʹ͙࣍ԋश (45)
3. ߦྻΛͬͨཁ • ѻ͍ํϕΫτϧͷཁͱಉ͡ • matrix.4 <- matrix(c(1, 2, 3,
4, 5, 6, 7, 8, 9), nrow = 3, ncol = 3, byrow = TRUE) • matrix.4 ͰதΛ֬ೝ • sum(matrix.4) #ߦྻʹ͋Δͷ૯ • mean(matrix.4) #ߦྻશମͷฏۉ • sum(matrix.4[1,]) #ߦྻ1ߦͷ૯ • mean(matrix.4[,2:3]) #ߦྻ2-3ྻͷฏۉ
3. ߦྻΛͬͨཁ • ͪΐͬͱɾཁૉΛେ͖ͯ͘͠Έ·͠ΐ͏ • matrix.5 <- matrix(c(1:5000), nrow =
100, ncol = 50, byrow = TRUE) • matrix.5 ͰதΛ֬ೝ • sum(matrix.5) #ߦྻʹ͋Δͷ૯ • mean(matrix.5) #ߦྻશମͷฏۉ
3. ߦྻΛͬͨཁ • rowSums() ؔ; colSums() ؔ; • ߦ͝ͱྻ͝ͱʹ૯ΛٻΊΔؔ •
rowSums(matrix.4); rowSums(matrix.5) • colSums(matrix.4); colSums(matrix.5) • rowMeans () ؔ; colMeans() ؔ • ߦ͝ͱྻ͝ͱʹฏۉΛٻΊΔؔ • rowMeans(matrix.4); rowMeans(matrix.5) • colMeans(matrix.4); colMeans(matrix.5)
3. ߦྻΛͬͨཁ • apply() ؔ • ߦ͝ͱྻ͝ͱʹ༷ʑͳؔΛద༻ • apply(ߦྻ໊, Ϛʔδϯ,
ద༻͢Δؔʣ • Ϛʔδϯ͕1ͳΒߦ͝ͱɼ2ͳΒྻ͝ͱ • apply(matrix.4, 1, sum) #ߦ͝ͱͷ૯ • rowSums(matrix.4) ͱಉ͡ॲཧ • apply(matrix.4, 2, mean) #ྻ͝ͱͷฏۉ • colMeans(matrix.4) ͱಉ͡ॲཧ
3. ߦྻΛͬͨཁ • apply() ؔͷଓ͖ • apply(matrix.4, 1, max) •
#ߦ͝ͱͷ࠷େ • apply(matrix.4, 2, summary) • #ྻ͝ͱͷཁ౷ܭྔ
Agenda 1. σʔλͷཁͷඞཁੑ (5) 2. ϕΫτϧΛͬͨཁ (20) 3. ߦྻΛͬͨཁ (20)
4. ԋशʹ͙࣍ԋश (45)
Agenda 1. σʔλͷཁͷඞཁੑ (5) 2. ϕΫτϧΛͬͨཁ (20) 3. ߦྻΛͬͨཁ (20)
4. ԋशʹ͙࣍ԋश (45)
4. ԋशʹ͙࣍ԋश 1. 1͔Β50͔Β·Ͱͷ͕ೖͬͨϕΫτ ϧΛ࡞ͯ͠… 1. ૯, ฏۉ, தԝ, ࠷େ,
࠷খ , ࢄ, ඪ४ภࠩΛٻΊΔ 2. ཁ౷ܭྔΛٻΊΔ
4. ԋशʹ͙࣍ԋशʢώϯτʣ 1. Λൃੜͤ͞ΔʹίϩϯΛ͍·͠ΐ͏ 1. ֤ؔΛηϛίϩϯͰͭͳ͍ͰҰؾʹ࣮ߦ 2. summary() ؔΛ͍·͢
2. 1͔Β10000·Ͱͷ͕ೖͬͨߦྻʢ100ߦɾ100ྻʣΛ࡞ͯ͠… 1. 20ߦʮͱʯ70ߦͷ2ߦͷΈͷ֤૯ΛٻΊΔ 2. 31ྻʮ͔Βʯ80ྻ·Ͱͷ50ྻͷ֤ฏۉΛٻΊΔ 3. ߦ͝ͱɾྻ͝ͱͷ૯ΛٻΊΔʢapply ؔΛ༻ʣ 4.
ߦ͝ͱɾྻ͝ͱͷฏۉΛٻΊΔʢapply ؔΛ༻ʣ 5. ߦ͝ͱɾྻ͝ͱͷཁ౷ܭྔΛٻΊΔʢapply ؔΛ༻ʣ 6. psych ύοέʔδΛͬͯཁ౷ܭྔΛٻΊΔ • ҙͷߦɾྻʹରͯ͠ٻΊͯΈΔ 4. ԋशʹ͙࣍ԋश
2. matrix() ؔΛ͍ɼྻͷࢦఆͱ byrow ͷઃఆʹ༻৺ 1. ߦͷෳࢦఆ c() ؔΛ͍·͠ΐ͏ 2.
ྻͷൣғࢦఆίϩϯΛ͍·͠ΐ͏ 3. apply() ؔͱ sum() ؔΛΈ߹Θͤ·͠ΐ͏ 4. apply() ؔͱ mean() ؔΛΈ߹Θͤ·͠ΐ͏ 5. apply() ؔͷߦͱྻͷࢦఆɼ1 ͔ 2 Ͱ͚·͢ 6. ·ͣ install.packages() ͯ͠ library() Ͱ༗ޮԽ 4. ԋशʹ͙࣍ԋशʢώϯτʣ
Enjoy ! twitter: @sakaue e-mail: tsakaue<AT>hiroshima-u.ac.jp