A handy tip for today—even if you already work with pandas or NumPy: display enriched tables right inside Google Colab.
These tips and notebooks are primarily geared toward Python, though you can also spin up notebooks for R scripts.
How do you get enriched tables?
Google Colab lets you add a single line to your scripts to surface enriched tables—and it can make a big difference.
It’s a straightforward trick, but it’s great for filtering your data “just like in Excel or Google Sheets.” It also helps you explore your datasets before applying further changes to your dataframe.
%load_ext google.colab.data_table
How do you turn enriched tables off?
Need to disable the feature for certain notebooks or when restarting a script? No problem—just run the following:
%unload_ext google.colab.data_table
Some enriched table options
Google Colab also makes it easy to control how data loads via from google.colab import data_table. For example, you can:
- Choose whether to include the index with
include_index=followed byTrueorFalse(case-sensitive). - Set how many rows display per page with
num_rows_per_page=and the value you prefer (5, 20, 50, etc.).
data_table.DataTable({your_dataset}, include_index=False, num_rows_per_page=10)
A handy companion to pandas and NumPy
This trick complements familiar functions like head, drop, or shape that you use regularly in Python.
If you still have questions, Google Colab offers a full notebook that lets you experiment with these features.
