Load local data files to Colaboratory

Question

I just wondering that is it possible to load local data files(like .xlsx or .csv files that on my google drive) into Colaboratory?

Answer 1

I was a bit confused by the example for loading local files on first glance as there was no place to specify a file path. All you need to do is copy and paste the recipe to figure this out, but to be clear:

from google.colab import files
uploaded = files.upload()

will open an upload dialogue window where you can browse and select your local files for upload.

Then

for fn in uploaded.keys():
  print('User uploaded file "{name}" with length {length} bytes'.format(
      name=fn, length=len(uploaded[fn])))

will show you the keys to access what you just uploaded.

Edit for additional clarification: The dictionary uploaded will have keys of the selected filenames - so if for example you select a file my_test.txt, then you would access that file using uploaded['my_test.txt'].

Answer 2

Yes, all of these scenarios are supported.

For recipes to access local and Drive files, check out the I/O example notebook.

For access to xls files, you'll want to upload the file to Google Sheets. Then, you can use the gspread recipes in the same I/O example notebook.

A recently added way to upload local files is to use the 'Files' tab in the right hand side drawer.

From there, you can upload a local file using the 'upload' button.

(You can also download files by right clicking on them in the file tree.)

Answer 3

First, executing this cell should create an inline "Choose Files" button

from google.colab import files
uploaded = files.upload()

After selecting your file(s), uploaded will be a dictionary of keys (the file names) and values (the encoded file objects). To decode the files for a library such as Pandas, try

import pandas as pd
import io
df = pd.read_csv(io.StringIO(uploaded['filename.csv'].decode('utf-8')))

After this your dataframe df should be ready to go