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Export a Pandas dataframe as a table image

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python

pandas

Is it possible to export a Pandas dataframe as an image file? Something like df.to_png() or df.to_table().savefig('table.png').

At the moment I export a dataframe using df.to_csv(). I then open this csv file in Excel to make the data look pretty and then copy / paste the Excel table into Powerpoint as an image. I see matplotlib has a .table() method, but I'm having trouble getting it to work with my df.

The data frame I'm using has 5 columns and 5 rows and each 'cell' is a number.

like image 259
user2370852 Avatar asked Oct 31 '14 15:10

user2370852


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How do I save a Pandas DataFrame as a picture?

Pass your normal or styled DataFrame to the export function along with a file location to save it as an image. You may also export directly from the DataFrame or styled DataFrame using the dfi. export and export_png methods, respectively. Here, an example of how exporting a DataFrame would look like in a notebook.


1 Answers

With some additional code, you can even make output look decent:

import pandas as pd import numpy as np import matplotlib.pyplot as plt import six  df = pd.DataFrame() df['date'] = ['2016-04-01', '2016-04-02', '2016-04-03'] df['calories'] = [2200, 2100, 1500] df['sleep hours'] = [2200, 2100, 1500] df['gym'] = [True, False, False]   def render_mpl_table(data, col_width=3.0, row_height=0.625, font_size=14,                      header_color='#40466e', row_colors=['#f1f1f2', 'w'], edge_color='w',                      bbox=[0, 0, 1, 1], header_columns=0,                      ax=None, **kwargs):     if ax is None:         size = (np.array(data.shape[::-1]) + np.array([0, 1])) * np.array([col_width, row_height])         fig, ax = plt.subplots(figsize=size)         ax.axis('off')      mpl_table = ax.table(cellText=data.values, bbox=bbox, colLabels=data.columns, **kwargs)      mpl_table.auto_set_font_size(False)     mpl_table.set_fontsize(font_size)      for k, cell in  six.iteritems(mpl_table._cells):         cell.set_edgecolor(edge_color)         if k[0] == 0 or k[1] < header_columns:             cell.set_text_props(weight='bold', color='w')             cell.set_facecolor(header_color)         else:             cell.set_facecolor(row_colors[k[0]%len(row_colors) ])     return ax  render_mpl_table(df, header_columns=0, col_width=2.0) 

enter image description here

like image 52
volodymyr Avatar answered Sep 20 '22 14:09

volodymyr