Comment on page
Importing data from flat files
Workspace features a library of curated datasets ready for you to analyze, but it is also possible to work with your own data files, be it CSV, Excel, text, geospatial, etc. data files. In this article, we'll assume that the data file you want to work with in Workspace is on your computer. The first step is uploading the file to Workspace, the next step is loading the data file into your notebook session.
- Click theicon in the left sidebar to open the file browser.
- To upload the data file, you have several options:
- Click theicon in the top right of the file browser tab and click Upload. Select the file from your local filesystem and confirm.
- Click on "Browse files" in the dashed rectangular box in the file browser. Select the file from your local filesystem and confirm.
- Drag the file from a file browser (Windows) or Finder (Mac) window into the file browser pane.
Now that you have uploaded to file to your workspace, you can load it into your session so you can start analyzing it.
First, copy the file path to your clipboard by clicking the
icon next to your data file and selecting "Copy path to clipboard".
Second, add a new code cell to your notebook file and add one of the following code snippets depending on the file format or the language you're using. Note that you may need to tweak this function call to deal with the specifics of your file (e.g. to skip rows, to specify the column names, etc). Replace
example.csvwith the file path you copied to your clipboard in the first step.
Finally, run the code cell. The data contained in the file will now be available as a dataframe
dfthat you can start analyzing.
Specifically for CSV files, there is a faster way: click the
icon next to the file you want to import and select "Load as DataFrame". A new code cell will be added to your notebook with the appropriate Python or R code.
"Load as DataFrame" is a quick way to import a CSV file into your notebook