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votes

I am doing some data pre-processing on Google Colab and just wondering how it works with manipulating dataset. For example R does not change the original dataset until you use write.csv to export the changed dataset. Does it work similarly in colab? Thank you!

1
The way I/O works depends on what library you are using to manipulate your data. Which one do you have in mind? - Bob Smith
Hi Bob, I am currently using pandas, numpy and datetime - nilsinelabore

1 Answers

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Until you explicitly save your changed data, e.g. using df.to_csv to the same file you read from, your changed dataset is not saved.

You must remember that due to inactivity (up to an hour or so), you colab session might expire and all progress be lost.

Update

  1. To download a model, dataset or a big file from Google Drive, gdown command is already available

!gdown https://drive.google.com/uc?id=FILE_ID

  1. Download your code from GitHub and run predictions using the model you already downloaded

!git clone https://USERNAME:[email protected]/username/project.git

  1. Write ! before a line of your code in colab and it would be treated as bash command. You can download files form internet using wget for example

!wget file_url

  1. You can commit and push your updated code to GitHub etc. And updated dataset / model to Google Drive or Dropbox.