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Problem: I tried to export a pandas.DataFrame to LaTex using .to_latex().

However, the output for long values (in my case long strings) gets truncated.

Step to reproduce:

import pandas as pd df = pd.DataFrame(['veryLongString' * i for i in range(1, 5)], dtype='string') print(df.to_latex())

Output:

\begin{tabular}{ll} \toprule {} & 0 \\ \midrule 0 & veryLongString \\ 1 & veryLongStringveryLongString \\ 2 & veryLongStringveryLongStringveryLongString \\ 3 & veryLongStringveryLongStringveryLongStringvery... \\ \bottomrule \end{tabular}

As you can see, the last row gets truncated (with ...). I already tried to use the col_space parameter but this does not change the behavior as expected. It simply shifts the table cells as following:

\begin{tabular}{ll} \toprule {} & 0 \\ \midrule 0 & veryLongString \\ 1 & veryLongStringveryLongString \\ 2 & veryLongStringveryLongStringveryLongString \\ 3 & veryLongStringveryLongStringveryLongStringvery... \\ \bottomrule \end{tabular}

How do I get the full content of the DataFrame exported to Latex?

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2 Answers 2

Reset to default
10

You can call the context manager with a with statement to temporarily change the max column width:

with pd.option_context("max_colwidth", 1000): print (df.to_latex())

Output:

\begin{tabular}{ll} \toprule {} & 0 \\ \midrule 0 & veryLongString \\ 1 & veryLongStringveryLongString \\ 2 & veryLongStringveryLongStringveryLongString \\ 3 & veryLongStringveryLongStringveryLongStringveryLongString \\ \bottomrule \end{tabular}

This behaviour is also described here.

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1 Comment

What a useful alternative to temporarily change this option.
4

After spending some time trying out other parameters from to_latex() as well as other export options, e.g., to_csv(), I was sure that this is not a problem of to_latex().

I found the solution in the pandas documentation:

enter image description here

So the solution is setting this option to None to don't restrict the output (globally).

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

Source: https://pandas.pydata.org/pandas-docs/stable/user_guide/options.html

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