Lab 1C: Export, Upload, Import

Lab 1C - Export, Upload, Import

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

Whose data? Our data.

• 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

Export, upload, import

• 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

Exporting

• 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.

Campaign Manager

• After logging in, your screen should look similar to this.

• Click on the dropdown arrow for the campaign you are interested in downloading.

  – At this point in the course, it will most likely be the Food Habits campaign

Dropdown Arrow

• 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!

Exporting

• 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.

Uploading

• 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!

Upload vs. Import

• 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.

Importing

• On the Files pane, find the data you want to import.

• Click on the name of the file and choose the option Import Data set...

Data Preview

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

What's in a name?

• 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.

read.csv()

• 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.

A word on staying organized...

• 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

Export, upload, import

• 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.