Pretty-Print an Entire Pandas Series/Dataframe

Pretty-print an entire Pandas Series / DataFrame

You can also use the option_context, with one or more options:

with pd.option_context('display.max_rows', None, 'display.max_columns', None):  # more options can be specified also
    print(df)

This will automatically return the options to their previous values.

If you are working on jupyter-notebook, using display(df) instead of print(df) will use jupyter rich display logic (like so).

How can I display full (non-truncated) dataframe information in HTML when converting from Pandas dataframe to HTML?

Set the display.max_colwidth option to None (or -1 before version 1.0):

pd.set_option('display.max_colwidth', None)

set_option documentation

For example, in IPython, we see that the information is truncated to 50 characters. Anything in excess is ellipsized:

If you set the display.max_colwidth option, the information will be displayed fully:

Pretty print a pandas dataframe in VS Code

As of the January 2021 release of the python extension, you can now view pandas dataframes with the built-in data viewer when debugging native python programs. When the program is halted at a breakpoint, right-click the dataframe variable in the variables list and select "View Value in Data Viewer"

Print very long string completely in pandas dataframe

You can use options.display.max_colwidth to specify you want to see more in the default representation:

In [2]: df
Out[2]:
                                                 one
0                                                one
1                                                two
2  This is very long string very long string very...

In [3]: pd.options.display.max_colwidth
Out[3]: 50

In [4]: pd.options.display.max_colwidth = 100

In [5]: df
Out[5]:
                                                                               one
0                                                                              one
1                                                                              two
2  This is very long string very long string very long string veryvery long string

And indeed, if you just want to inspect the one value, by accessing it (as a scalar, not as a row as df.iloc[2] does) you also see the full string:

In [7]: df.iloc[2,0]    # or df.loc[2,'one']
Out[7]: 'This is very long string very long string very long string veryvery long string'

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