Export, Upload, Import

Lab 1C

Directions: Follow along with the slides and answer the questions in red font in your journal.

• Throughout the previous labs, we've been using data that was already loaded in RStudio.
  • But what if we want to analyze our own data?
• This lab is all about learning how to load our own participatory sensing data into RStudio

• Before we can perform any analysis, we have to load data into R.
• When we want to get our participatory sensing data into RStudio, we:
  • Export the data from your class' campaign page.
  • Upload data to RStudio server
  • Import the data into R's working memory

• To begin, go to the IDS Tools Page.
  • Click on the Campaign Manager
  • Fill in your username and password and click “Sign in.” If you forget your username or password, ask your teacher to remind you.

• After logging in, your screen should look similar to this.
• Click on the dropdown arrow for the campaign you are interested in downloading.

• The options for the dropdown menu will look like this.
• Look for the option labeled Export Data. Click it.
  • Remember where you save your file!

• When you clicked the Export link a .csv file was saved on your computer.
• Now that the file is on your computer, we need to upload it into RStudio.

• Look at the four different panes in RStudio.
  • Find the pane with a Files tab.
  • Click it!

• Click the button on the Files pane that says “Upload”
  • Click on “Choose File” and find the SurveyResponses.csv file you saved to your computer.
  • Hit the OK button.
• Voila!
  • If you look in the Files pane, you should be able to find your data!

• By Uploading your data into RStudio you've really only given yourself access to it.
  • Don't believe me? Look at the Environment pane … where's your data?
• To actually use the data we need to Import it into your computer's memory.
• To compute more quickly and efficiently, R will only keep a few data sets stored in its memory at a time.
  • By importing data, you are telling R that this is a data set that is important to store it in its memory so you can use it.

• On the Files pane, find the data that you want to import.
• Click on the name of the file and choose the option “Import Data set…”

• You can give your data a name using the Name: field in the lower left corner.

• The name you give your data is what you will use when you write code to analyze your data.
  • Good names are short and descriptive.
  • For your food habits campaign, some good names to use would be “foodhabits” or even just “food”.
• When you're ready, click the Import button.

• After you click import you might notice something appeared in your console.

data.file <- read_csv("~/SurveyResponse.csv")
View(data.file)

• This is the actual code RStudio uses to read your data when you clicked the import button.
  • So instead of using the RStudio buttons, we can actually Import by writing code similar to what was output into the console!
  • This will come in handy later in the course.

• The Files tab has a few other features to help keep you organized.
  • SurveyResponse probably isn't the best name for your data. Click Rename to give it a clearer name.
  • Often, it's helpful to give your data file the same name as when you import your data.
  • So in this case, we could name our data file foodhabits.csv

• After you export, upload, import your data you're ready to analyze.
• View your data, select a variable and try to make an appropriate plot for that variable.
  • If you're having issues, make sure you're spelling the name of your data correctly.