How can I display full (non-truncated) dataframe information in HTML when converting from Pandas dataframe to HTML?
PythonHtmlPandasPython Problem Overview
I converted a Pandas dataframe to an HTML output using the DataFrame.to_html function. When I save this to a separate HTML file, the file shows truncated output.
For example, in my TEXT column,
df.head(1) will show
The film was an excellent effort...
instead of
The film was an excellent effort in deconstructing the complex social sentiments that prevailed during this period.
This rendition is fine in the case of a screen-friendly format of a massive Pandas dataframe, but I need an HTML file that will show complete tabular data contained in the dataframe, that is, something that will show the latter text element rather than the former text snippet.
How would I be able to show the complete, non-truncated text data for each element in my TEXT column in the HTML version of the information? I would imagine that the HTML table would have to display long cells to show the complete data, but as far as I understand, only column-width parameters can be passed into the DataFrame.to_html function.
Python Solutions
Solution 1 - Python
Set the display.max_colwidth option to None (or -1 before version 1.0):
pd.set_option('display.max_colwidth', None)
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:
Solution 2 - Python
pd.set_option('display.max_columns', None)
id (second argument) can fully show the columns.
Solution 3 - Python
While pd.set_option('display.max_columns', None) sets the number of the maximum columns shown, the option pd.set_option('display.max_colwidth', -1) sets the maximum width of each single field.
For my purposes I wrote a small helper function to fully print huge data frames without affecting the rest of the code. It also reformats float numbers and sets the virtual display width. You may adopt it for your use cases.
def print_full(x):
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.width', 2000)
pd.set_option('display.float_format', '{:20,.2f}'.format)
pd.set_option('display.max_colwidth', None)
print(x)
pd.reset_option('display.max_rows')
pd.reset_option('display.max_columns')
pd.reset_option('display.width')
pd.reset_option('display.float_format')
pd.reset_option('display.max_colwidth')
Solution 4 - Python
Jupyter Users
Whenever I need this for just one cell, I use this:
with pd.option_context('display.max_colwidth', None):
display(df)
Solution 5 - Python
Try this too:
pd.set_option("max_columns", None) # show all cols
pd.set_option('max_colwidth', None) # show full width of showing cols
pd.set_option("expand_frame_repr", False) # print cols side by side as it's supposed to be
Solution 6 - Python
The following code results in the error below:
pd.set_option('display.max_colwidth', -1)
FutureWarning: Passing a negative integer is deprecated in version 1.0 and will not be supported in future version. Instead, use None to not limit the column width.
Instead, use:
pd.set_option('display.max_colwidth', None)
This accomplishes the task and complies with versions of Pandas following version 1.0.
Solution 7 - Python
Another way of viewing the full content of the cells in a Pandas dataframe is to use IPython's display functions:
from IPython.display import HTML
HTML(df.to_html())
Solution 8 - Python
For those looking to do this in Dask:
I could not find a similar option in Dask, but if I simply do this in same notebook for Pandas it works for Dask too.
import pandas as pd
import dask.dataframe as dd
pd.set_option('display.max_colwidth', -1) # This will set the no truncate for Pandas as well as for Dask. I am not sure how it does for Dask though, but it works.
train_data = dd.read_csv('./data/train.csv')
train_data.head(5)
Solution 9 - Python
For those who like to reduce typing (i.e., everyone!): pd.set_option('max_colwidth', None) does the same thing