Export a Pandas dataframe as a table image

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.

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)

If you have pdflatex and imagemagick installed, you could export the DataFrame to tex, use pdflatex to convert it to a pdf file, and then convert the pdf to png using imagemagick:

import pandas as pd
import numpy as np
import subprocess

df = pd.DataFrame({'d': [1., 1., 1., 2., 2., 2.],
                   'c': np.tile(['a', 'b', 'c'], 2),
                   'v': np.arange(1., 7.)})
filename = 'out.tex'
pdffile = 'out.pdf'
outname = 'out.png'

template = r'''\documentclass[preview]{{standalone}}
\usepackage{{booktabs}}
\begin{{document}}
{}
\end{{document}}
'''

with open(filename, 'wb') as f:
    f.write(template.format(df.to_latex()))

subprocess.call(['pdflatex', filename])
subprocess.call(['convert', '-density', '300', pdffile, '-quality', '90', outname])

If you install phantomjs and imagemagick, you could export the DataFrame to HTML and then use phantomjs to convert the HTML to png, and imagemagick to crop the result:

import pandas as pd
import numpy as np
import subprocess

df = pd.DataFrame({'d': [1., 1., 1., 2., 2., 2.],
                   'c': np.tile(['a', 'b', 'c'], 2),
                   'v': np.arange(1., 7.)})
filename = '/tmp/out.html'
outname = '/tmp/out.png'
cropname = '/tmp/cropped.png'

with open(filename, 'wb') as f:
    f.write(df.to_html())
rasterize = '/path/to/phantomjs/examples/rasterize.js'
subprocess.call(['phantomjs', rasterize, filename, outname])
subprocess.call(['convert', outname, '-trim', cropname])

You could take a look at the dataframe-image package (https://pypi.org/project/dataframe-image/), which offers the possibility to export a (styled) dataframe as an image file. An example of how this can be achieved is shown in the image below (which I copied from the above mentioned webpage).

I had the same requirement for a project I am doing. But none of the answers came elegant to my requirement. Here is something which finally helped me, and might be useful for this case:

from bokeh.io import export_png, export_svgs
from bokeh.models import ColumnDataSource, DataTable, TableColumn

def save_df_as_image(df, path):
    source = ColumnDataSource(df)
    df_columns = [df.index.name]
    df_columns.extend(df.columns.values)
    columns_for_table=[]
    for column in df_columns:
        columns_for_table.append(TableColumn(field=column, title=column))

    data_table = DataTable(source=source, columns=columns_for_table,height_policy="auto",width_policy="auto",index_position=None)
    export_png(data_table, filename = path)