文件列表:

Codes/ (0, 2020-05-09)
Codes/.RData (9718, 2020-05-09)
Codes/.Rapp.history (0, 2020-05-09)
Codes/.Rhistory (8953, 2020-05-09)
Codes/R01_2_1_InstallingR.R (757, 2020-05-09)
Codes/R01_2_2_RStudio.R (770, 2020-05-09)
Codes/R01_2_3_Packages.R (1174, 2020-05-09)
Codes/R01_3_1_plot().R (1476, 2020-05-09)
Codes/R01_3_2_BarCharts.R (956, 2020-05-09)
Codes/R01_3_3_Histograms.R (1429, 2020-05-09)
Codes/R01_3_4_Scatterplots.R (1116, 2020-05-09)
Codes/R01_3_5_OverlayingPlots.R (1527, 2020-05-09)
Codes/R01_4_1_summary().R (795, 2020-05-09)
Codes/R01_4_2_describe().R (1224, 2020-05-09)
Codes/R01_4_3_SelectingCases.R (1928, 2020-05-09)
Codes/R01_5_1_DataFormats.R (2657, 2020-05-09)
Codes/R01_5_2_Factors.R (1291, 2020-05-09)
Codes/R01_5_3_EnteringData.R (1289, 2020-05-09)
Codes/R01_5_4_ImportingData.R (2073, 2020-05-09)
Codes/R01_5_4_ImportingData_Datasets/ (0, 2020-05-09)
Codes/R01_5_4_ImportingData_Datasets/._mbb.csv (70, 2020-05-09)
Codes/R01_5_4_ImportingData_Datasets/._mbb.txt (70, 2020-05-09)
Codes/R01_5_4_ImportingData_Datasets/._mbb.xlsx (70, 2020-05-09)
Codes/R01_5_4_ImportingData_Datasets/mbb.csv (2298, 2020-05-09)
Codes/R01_5_4_ImportingData_Datasets/mbb.txt (2298, 2020-05-09)
Codes/R01_5_4_ImportingData_Datasets/mbb.xlsx (36899, 2020-05-09)
Codes/R01_5_5_Assignment_Datasets/ (0, 2020-05-09)
Codes/R01_5_5_Assignment_Datasets/._import.txt (70, 2020-05-09)
Codes/R01_5_5_Assignment_Datasets/import.csv (7725, 2020-05-09)
Codes/R01_5_5_Assignment_Datasets/import.txt (7722, 2020-05-09)
Codes/R01_5_5_Assignment_Datasets/import.xlsx (18901, 2020-05-09)
Codes/R01_6_1_HierarchicalClustering.R (1537, 2020-05-09)
Codes/R01_6_2_PrincipalComponents.R (1722, 2020-05-09)
Codes/R01_6_3_Regression.R (2332, 2020-05-09)
Codes/R01_Exercise_Template.R (831, 2020-05-09)
LICENSE (1070, 2020-05-09)
Main.R (196, 2020-05-09)
plots/ (0, 2020-05-09)
plots/iris.png (14697, 2020-05-09)
... ...

# R - Language of Data Science: a Tutorial In this repository, a useful, though short, tutorial of R is provided for beginners and those who are interested to learn about Data Science. R is a statistical computing programming language. Creating and analyzing data is R could not be easier. For instant to create a vector of strings in R you just need write ```R MyVector <- c(1,2,3,4,5) ``` where `c` stands for combine and `<-` is assignment operator. Data types in R is almost similar to any other programming language. There are - numerics (integer, single, double): `1`, `2.32` - characters: `"HelloWorld"` - logical: `True`, `False` - complex: `(-1)^(1/2)` - raw: contains bytes Data structures in R is also similar to other programming languages but with extra feature. There are - Vector: `c(1, 2, 3, 4, 5)` - Matrix/array: `matrix(c(T, T, F, F, T, F), nrow = 2)` and `array(c( 1:24), c(4, 3, 2))` - Data frame: `cbind(c(1, 2), c("a", "b"), c(True, False))` - List: `list(True, c(1, 2), "a")` ## Installation To install R, please visit [r-project.org](https://www.r-project.org/). You can also install R Studio to assist you in programming and visualizing the data. Download R Studio [here](https://rstudio.com/). ## Load, Summary, Plot on Built-in Data There are some buit-in datasets in R that you can use to experiment on. To load a dataset use `library()`, to see the head (first row) of dataset use `head()`, to get a summary of stats use `summary()`, to plot the data simply use `plot()`. Run ```R library(datasets) # Load built-in datasets head(iris) # Show the first six lines of iris data summary(iris) # Summary statistics for iris data plot(iris) # Plot the dataset ``` The output is ```cmd > head(iris) Sepal.Length Sepal.Width Petal.Length Petal.Width Species 1 5.1 3.5 1.4 0.2 setosa 2 4.9 3.0 1.4 0.2 setosa 3 4.7 3.2 1.3 0.2 setosa 4 4.6 3.1 1.5 0.2 setosa 5 5.0 3.6 1.4 0.2 setosa 6 5.4 3.9 1.7 0.4 setosa > summary(iris) Sepal.Length Sepal.Width Petal.Length Petal.Width Min. :4.300 Min. :2.000 Min. :1.000 Min. :0.100 1st Qu.:5.100 1st Qu.:2.800 1st Qu.:1.600 1st Qu.:0.300 Median :5.800 Median :3.000 Median :4.350 Median :1.300 Mean :5.843 Mean :3.057 Mean :3.758 Mean :1.199 3rd Qu.:6.400 3rd Qu.:3.300 3rd Qu.:5.100 3rd Qu.:1.800 Max. :7.900 Max. :4.400 Max. :6.900 Max. :2.500 Species setosa :50 versicolor:50 virginica :50 > plot(iris) ```  To clear a plot, write `dev.off()` and hit enter! ## Load Packages Use `pacman` for managing add-on packages. To install `pacman`, enter ```R install.packages("pacman") ``` You can then choose the packages you need and load them as follows ```R pacman::p_load(pacman, dplyr, GGally, ggplot2, ggthemes, ggvis, httr, lubridate, plotly, rio, rmarkdown, shiny, stringr, tidyr) ``` Make sure to clear all packages and datasets before exit ```R p_unload(all) # Clears all add-ons detach("package:datasets", unload = TRUE) # Clear data-base ```

近期下载者：

相关文件：

评论：[我要评论] [举报此文件]

收藏者：