diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..5b6a065
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,4 @@
+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
diff --git a/twitter-data.Rproj b/twitter-data.Rproj
new file mode 100644
index 0000000..8e3c2eb
--- /dev/null
+++ b/twitter-data.Rproj
@@ -0,0 +1,13 @@
+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
diff --git a/twitter_data.Rmd b/twitter_data.Rmd
new file mode 100644
index 0000000..b024b5d
--- /dev/null
+++ b/twitter_data.Rmd
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+---
+title: "twitter"
+author: "Jing"
+date: "October 11, 2016"
+output: pdf_document
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = TRUE)
+```
+
+## R Markdown
+
+This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see <http://rmarkdown.rstudio.com>.
+
+When you click the **Knit** button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:
+
+```{r}
+twitter_data <- read.csv("HUDK4050-twitter-10-06-16.csv", header=TRUE,sep=",")
+View(twitter_data)
+```
+
+## Including Plots
+
+You can also embed plots, for example:
+
+```{r pressure, echo=FALSE}
+#plots
+plot(twitter_data) #too overwhelming
+plot(twitter_data$screenName,twitter_data$time) 
+
+#create subset
+D1<-twitter_data$screenName
+D2<-twitter_data$time
+
+#barplot
+table<-table(D2,D1)
+barplot(table)
+
+#lineplot
+plot(twitter_data$screenName, twitter_data$time, type = "l",lty = "dashed")
+   #why it is not a line plot, but a boxplot instead???
+
+#boxplot
+boxplot(twitter_data$time,twitter_data$screenName)
+
+#use of "aggregate": example of "last day of the month"
+dates <- data.frame(date = as.Date("2001-01-01", format = "%Y-%m-%d") + 0:729)
+last.day <- aggregate(x = dates["date"], by = list(month = substr(dates$date, 1, 7)), FUN = max)
+
+#create a table about how many times each person tweet:) or AKA frequency table
+library(plyr)
+table1<-data.frame(name=twitter_data$screenName,tweet=twitter_data$text)
+table2<-count(table1,"name")
+
+```
+
+
+Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot.