吳齊軒/漫談 R 的學習挑戰與 R 語言翻轉教室
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The document discusses various resources and tools related to the R programming language, emphasizing its applications in data science, statistics, and data visualization. It includes links to educational materials, code examples, and comparisons between R and Python for data analysis. Additionally, it contains references to libraries like quantmod and practices for developing API packages.
![[1] "TWII"
TWII.OPEN TWII.HIGH TWII.LOW TWII.CLOSE TWII.VOLUME TWII.ADJUSTED
7871.41 7937.26 7843.60 7920.80 5710600 7920.777
7954.96 7999.42 7917.30 7917.30 5951400 7917.277
7929.89 7955.90 7901.24 7934.51 5717400 7934.487
7940.20 7942.23 7821.71 7835.57 5181400 7835.547
7778.57 7797.57 7736.11 7736.71 4292400 7736.688
7778.38 7827.93 7778.38 7790.01 4516000 7789.987
library(quantmod)
getSymbols("^TWII")
head(TWII)
18/80](https://image.slidesharecdn.com/random-160717042045/85/R-R-18-320.jpg)
![Estimate
NA
Beta
Beta
Intercept,data[,2],data[,3],data[,i],data[,j],data[,i]:data[,j]
33/80](https://image.slidesharecdn.com/random-160717042045/85/R-R-33-320.jpg)
![[ ]:
Oracle ( big5)
DBMSencoding
[ ]:
con <- odbcConnect(dsn, uid = "", pwd = "", DBMSencoding="big5")
34/80](https://image.slidesharecdn.com/random-160717042045/85/R-R-34-320.jpg)
![[ ]:
R ( SAS)
.DAT
65 40
R
read.delim() XD
~
36/80](https://image.slidesharecdn.com/random-160717042045/85/R-R-36-320.jpg)
吳齊軒/漫談 R 的學習挑戰與 R 語言翻轉教室
- 1. RR RR Wush Wu Taiwan R User Group
- 2. R 2/80
- 7. 7/80
- 11. R 11/80
- 16. Data Package Lahman R (httr rvest) R API Package · · · Best Practices for Writing an API Package quantmod twitteR - - 16/80
- 17. 17/80
- 18. [1] "TWII" TWII.OPEN TWII.HIGH TWII.LOW TWII.CLOSE TWII.VOLUME TWII.ADJUSTED 7871.41 7937.26 7843.60 7920.80 5710600 7920.777 7954.96 7999.42 7917.30 7917.30 5951400 7917.277 7929.89 7955.90 7901.24 7934.51 5717400 7934.487 7940.20 7942.23 7821.71 7835.57 5181400 7835.547 7778.57 7797.57 7736.11 7736.71 4292400 7736.688 7778.38 7827.93 7778.38 7790.01 4516000 7789.987 library(quantmod) getSymbols("^TWII") head(TWII) 18/80
- 19. : AirbnB uses R to scale data science Rbnb Airbnb's engineering, data science, analytics and user experience teams Hadoop / SQL R Missing Data · · · · 500+ How Airbnb uses Machine Learning to Detect Host Preferences How well does NPS predict rebooking? - - - 19/80
- 20. Reproducible Research· R Markdown Jupyter ir-kernel - - 20/80
- 21. 21/80
- 22. 22/80
- 23. R R· · 23/80
- 24. R R 24/80
- 29. · - 29/80
- 31. 31/80
- 34. [ ]: Oracle ( big5) DBMSencoding [ ]: con <- odbcConnect(dsn, uid = "", pwd = "", DBMSencoding="big5") 34/80
- 36. [ ]: R ( SAS) .DAT 65 40 R read.delim() XD ~ 36/80
- 38. 38/80
- 39. 39/80
- 40. · · · 40/80
- 41. R· · - - 41/80
- 42. R 42/80
- 43. http://radiusonline.com/interns/my-first-month-at-radiusonline/learn-by-doing/ 43/80
- 45. · - - · 45/80
- 46. 01-RBasic-02-Data-Structure-Vectors # 87 91 year1 <- 87:91 power1 <- c(6097059332, 6425887925, 6982579022, 7323992602.53436, 7954239517) # 87 91 power2 <- c(59090445718, 61981666330, 67378329131, 66127460204.6482, 69696372914.6949) # (`year1`) `7e9` # `7e9` R `7 * 10^9` year1.answer1 <- < > # 87 91 power1.mean <- < > 46/80
- 47. 02-RDataEngineer-01-Parsing # <http://data.gov.tw/node/7769> # # # # R pirate_info <- readLines(file(pirate_path, encoding = < encoding>)) 47/80
- 48. 02-RDataEngineer-06-Join #' `gdp_path` `gdp` #' `gdp_path` / GDP( ) ... #' cl_info mortgage_bal data_dt #' cl_info `cl_info_year` ... #' `gdp` `cl_info` #' gdp mortgage_total_bal / gdp 48/80
- 50. R · - · · 50/80
- 54. R Data Engineer · API Server JSON - - - - · · 54/80
- 57. Wush Wu Chih Cheng Liang Cheng-Yu Lin Johnson Hsieh CC - 3.0 · · 57/80
- 58. 58/80
- 60. 60/80
- 61. 61/80
- 62. R 62/80
- 64. 64/80
- 65. 65/80
- 67. 67/80
- 68. Swirl Project lesson.yaml swirl · - - - · https://github.com/swirldev/swirl/compare/master...wush978:mast- - Class: meta Course: DataScienceAndR Lesson: 00-Hello-DataScienceAndR Author: Wush Wu Type: Standard Organization: Taiwan R User Group 68/80
- 69. 69/80
- 70. cmd_question - Class: cmd_question Output: `chol2inv` CorrectAnswer: help(chol2inv) AnswerTests: any_of_exprs("?chol2inv", "help(chol2inv)") Hint: `?` `help` 70/80
- 71. 71/80
- 72. mult_question - Class: mult_question Output: | assignment R console `a - 1` AnswerChoices: 1;2;" ";"4" CorrectAnswer: 1 AnswerTests: omnitest(correctVal= '1') 72/80
- 73. 73/80
- 74. script - Class: script Output: | `submit()` Rstudio File -> Reopen With Encoding... -> UTF-8 Script: RBasic-02-HW.R AnswerTests: rbasic_02_hw_test() 74/80
- 75. 75/80
- 79. Q&A 79/80
- 80. R vs Python Choosing R or Python for data analysis? An infographic Pros and Cons of R vs Python Sci-kit learn Which is better for data analysis: R or Python? How to Choose Between Learning Python or R First · · · · 80/80