Go to options configuration in Pandas. Display all columns with: “display.max_columns.”. Set max column width with: “max_columns.”. Change the number of rows with: “max_rows” and “min_rows.”. Set the sequence of items with: “max_seq_items.”. I’ll be using the top 250 IMDB movies dataset, downloaded from Data World.

Thanks for the clear example. Unfortunately, I am not sure that SelectMultiple can be used in the way you intend. Generally, for an interact call, you need a function that you pass arguments to.

In more recent notebook versions Shift-L should toggle for all cells. If you can't remember the shortcut, bring up the command palette Ctrl-Shift+PCmd+Shift+P on Mac), and search for "line numbers"), it should allow to toggle and show you the shortcut. On IPython 2.2.0, just typing l (lowercase L) on command mode (activated by typing Esc) works

What are some good options to show a nice interactive table (2d) with python3? Id like the user to be able to sort the rowns (eg by clicking a column header), show/hide columns etc. Ideally without having to use (undebuggable) jupyter notebooks. If Im not incorrect it seems a lot easier to do this with jupyter notebooks than with "regular" python.

To see all lines, you need to change the "number of lines to show" value. Follow these steps to do so. Open VS code settings or (ctrl + ,) >> In search box type "output.textLineLimit" >> Find "Notebook>Output: Text Line Limit" >> Change the value as per your requirement (say 500 to show 500 lines) Share. Improve this answer. I can view all of the columns by scrolling left/right. However, this is a bit inconvenient and I was wondering if there was an elegant way to display the table with "foldover": To generate the above, I manually chopped up the dataframe into chunks and displayed each chunk (which is why the spacing/etc is not perfect). Now, fair is fair — Jupyter notebooks do make a decent-looking table, but using just pandas, we can do a fair bit of customisation to really make the table our own, and — more importantly — get our message across. In this article, we’ll see how to: Format dates; Format absolute numbers; Format currencies; Format ratios; Export formatted Fortunately, there is a better way. We can specify the maximum number of columns we want to see to some large value and get the friendly output in Jupyter without additional hassle. pd.set_option ('display.max_columns', 999) You can set "display.max_rows" option in pandas: pd.set_option('display.max_rows', None) or pd.set_option('display.max_rows', LARGE_NUMBER) To set it temporarily use a context manager: 925VPj.
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    • jupyter notebook display all columns