Final R class Yay

vijieaswar/intror/Challenges.R

@@ -75,3 +75,8 @@ lapply(df, range, na.rm=T)
 sapply(df, range, na.rm=T)
 #the sapply displays the range min and max value in 2 rows
 
+mapply()
+?mapply (not in class)
+
+Question8 <- tapply(df$hp, df$gear, max, na.rm=T)
+Question8

vijieaswar/intror/Practice.R

@@ -0,0 +1,66 @@
+
+cat <- "cat"
+alpha <1
+int <-3L
+#for integer, you have to have the L at the end, else it will be treated as a numeric
+
+#vectors are a sequence of objects that all have the same class. R will convert some of them if you have a word along with other numerics
+
+list is a special type of vector that can have objects of different classes.
+
+matrices are vectors with a deminsion attributes
+
+x = matrix (1:6, nrow=2, ncol=3)
+
+dim(x)
+attributes(x)
+
+x <- 1:10
+dim(x) <- c(2,5)
+# we added a dimension to create a matrix
+# the above does the same as the command below
+y <- matrix(1:10, nrow=2, ncol=5)
+y
+#you can also create a matrix with cbind
+
+x <- 1:3
+y <- 10:12
+#binding by coloumn
+x1 <- cbind(x,y)
+x1
+#binding by row
+x2 <- rbind(x,y)
+x2
+
+#matrices all have to be the same class- cant mix char, numeric. dataframe acn have mixed classes
+#Factors is another class- can label 
+
+unclass(x) is more descriptive- 
+
+num <- c(1,1,2,2,3)  
+fact <- factor(num, level=c(1,2,3), labels=c("yes","no","maybe"))
+#database has intergers and you are giving it an atrribute by giving it labels and saying what it means
+
+
+datafram: each column has to be the same type of data 
+
+(x <- data.frame(foo=1:4,bar=c(T,T,F,F)))
+
+attributes are like metadata
+adding information to your data without adding more values in the ddata.class(
+
+  datafames have row.names
+
+  you could give specific attributes such as names etc
+
+x <-1:3
+names(x)
+#there wont be any names
+
+names(x) <- c("alpha", "beta","gamma")
+#the above does not give a data fram
+names(x)
+str(x)
+#it is not a factor but it is assigning names- it is making a label
+names function unique to the person but factor labels will replace any value = to that by that character
+

vijieaswar/plotting/Classwork.R

@@ -102,7 +102,6 @@ library(reshape2)
 
 #cor returns a matric, not a df
 #creating a heatmap
-
 mtcars %>% 
   select(c(1,3,4,5,6,7)) %>% 
   cor() %>% 

vijieaswar/rmarkdown/Challenge.Rmd

@@ -0,0 +1,75 @@
+---
+title: "Challenge"
+author: "Viji"
+date: "November 23, 2015"
+output: 
+  html_document:
+    fig_caption: true
+    number_section: true
+    toc: true
+---
+
+
+
+```{r, echo = FALSE}
+library(dplyr)
+library(tidyr)
+library(pander)
+library(captioner)
+library(ggplot2)
+library(rmarkdown)
+
+knitr::opts_chunk$set(echo = FALSE, warning = FALSE)
+setwd("~/Desktop/practice-2015-10/vijieaswar/rmarkdown")
+```
+
+```{r}
+ds <- as.data.frame(state.x77) %>% 
+  add_rownames() %>% 
+  tbl_df()
+
+str(state.x77)
+
+names(ds)
+
+
+```
+
+# Brief Description
+The dataset consists of demographic information from `r dim(ds)[1]` states for the following `r dim(ds[-1])[2]` variables: `r names(ds[-1])`. The mean population across all states is `r round( mean(ds$Population),2)` and the standard deviation is `r round(sd(ds$Population),2)`
+
+```{r}
+
+figNums <- captioner(prefix = 'Figure')
+state_cap <- figNums('stateLitIncome', 'Income varies across illiteracy')
+
+```
+
+# Plots
+```{r, echo=FALSE, fig.cap=state_cap, dpi=150}
+ ds %>% 
+ ggplot(aes(x=Illiteracy, y=Income))+
+  geom_point()+
+  labs(plot.title="Income across illteracy", x="Illiteracy", y="Income")
+
+
+```
+
+#Tables
+```{r}
+
+tabNums <- captioner(prefix = 'Table')
+
+ds %>% 
+  gather(Variable, Value, -rowname) %>% 
+  group_by(Variable) %>% 
+  summarise(Means = mean(Value) %>% round(2),
+            SD = sd(Value) %>% round(2)) %>% 
+  pander(caption = tabNums('Demodata', 'Demographic data of 50 states'))
+```
+
+```{r, eval=FALSE}
+render('Challenge.Rmd', c('word_document', 'html_document'))
+```
+
+

vijieaswar/rmarkdown/Practice.Rmd

@@ -0,0 +1,134 @@
+---
+title: "Practice"
+author: "Viji"
+date: "November 23, 2015"
+output: 
+  html_document:
+      fig_caption: true
+      toc: true
+---
+```{r}
+#in the YAML, add the following
+#bibliography: give the location of the bib file
+#for a particular style
+#csl: give the location of the bib file citation style language. can be found in github
+
+```
+
+This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see <http://rmarkdown.rstudio.com>.
+
+When you click the **Knit** button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:
+
+# Intro
+
+## Citing a study
+```{r}
+
+
+
+#how to enter here from papers. need to export the bib key
+#@some bibkey
+#[] will make the round bracketts around the citation. 
+```
+
+```{r}
+
+
+#* makes the text in italics
+#** on either side will bold words
+#``` is a code block
+
+#` having things in line
+# > indicates that it is goin to be quote 
+# @ with bib key will extract refs
+
+#YAML header is for R to know what to do. YAML has o be closed in ---
+
+#pander, kable creates tables
+#ggplot qplot creates figure
+
+#conrol+shift+K will knit html
+```
+
+```{r, echo=FALSE}
+library(pander)
+library(captioner)
+
+#install.packages('captioner', type = 'source') if you get an error message while installing
+
+knitr::opts_chunk$set(echo = FALSE, warning = FALSE)
+#Can use this above ling to apply to every chunk
+
+#table option 1
+knitr::kable(summary(cars))
+
+
+#table option 2 
+tabNums <- captioner(prefix = 'Table')
+figNums <- captioner(prefix = 'Figure')
+cars_cap <- figNums('carsFig', 'This is a caption for the figure')
+
+
+pander(lm(cars), caption = tabNums('tab1', 'This is the caption for table 1')) #first coloumn as Y, and second column as X. if you have many columns, 2nd 3rd columnds are X2, X3 etc.
+
+
+```
+
+REference to **`r tabNums('tab1', display = 'cite')`**.
+
+You can also embed plots, for example:
+
+```{r, echo=FALSE, fig.cap=cars_cap}
+#have to write fig.caps = cars_cap because knitr is finicky
+
+plot(cars)
+```
+
+```{r}
+#Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot.
+
+#`r will take the following stuff within ` as a command. if you dont write r after ` it will take it as text
+#compare `r mean(cars$dist)` with `mean(cars$dist)`
+```
+
+#Tables
+```{r}
+library(dplyr)
+library(tidyr)
+
+cars %>% 
+  gather(Measure, Value) %>% 
+  group_by(Measure) %>% 
+  summarise(means =mean(Value) %>%  round(2)) %>% 
+  pander()
+
+```  
+
+# Figures
+## Scatterplot
+
+```{r, message = FALSE, fig.height=10, fig.width=5, dpi=150, dev='png'}
+library(ggplot2)
+qplot(dist,speed, data = cars, geom= 'point')
+
+```
+
+This is a list
+
+- There is `r length(cars)` rows in `cars`
+- There are `r dim(cars)[2]` variables in `cars`
+
+you would add ` ` around the cars to differentiate it from regular text
+
+This is a quote:
+
+> to be or not to be 
+
+```{r}
+#command+option+i is a new R chunk
+#command+alt+c runs the R chunk
+
+
+```
+
+# References

vijieaswar/wrangling/ChallengesVE.R

@@ -0,0 +1,3 @@
+
+#Date: 9th Nov 2015
+