Export Pandas Dataframe into a Pdf File Using Python

Export Pandas DataFrame into a PDF file using Python

Well one way is to use markdown. You can use df.to_html(). This converts the dataframe into a html table. From there you can put the generated html into a markdown file (.md) (see http://daringfireball.net/projects/markdown/basics). From there, there are utilities to convert markdown into a pdf (https://www.npmjs.com/package/markdown-pdf).

One all-in-one tool for this method is to use Atom text editor (https://atom.io/). There you can use an extension, search "markdown to pdf", which will make the conversion for you.

Note: When using to_html() recently I had to remove extra '\n' characters for some reason. I chose to use Atom -> Find -> '\n' -> Replace "".

Overall this should do the trick!

Saving Pandas DataFrame into PDF File format without pdfkit

One option is to start with:

df.to_html()

and then use QT to convert the HTML to PDF as follows:

from PyQt4.QtGui import QTextDocument, QPrinter, QApplication

import sys
app = QApplication(sys.argv)

doc = QTextDocument()
location = "c://apython//Jim//html//notes.html"
html = open(location).read()
doc.setHtml(html)

printer = QPrinter()
printer.setOutputFileName("foo.pdf")
printer.setOutputFormat(QPrinter.PdfFormat)
printer.setPageSize(QPrinter.A4)
printer.setPageMargins(15, 15, 15, 15, QPrinter.Millimeter)

doc.print_(printer)
print("done!")

I obtained the second bit of code from html to pdf, and tested on Mac OSX with positive results.

How to save pandas dataframe into existing pdf from PdfPages

Just create a plot of the table, then save that. Given a dataframe such as:

import pandas as pd

df = pd.DataFrame()
df['Animal'] = ['Cow', 'Bear']
df['Weight'] = [250, 450]
df['Favorite'] = ['Grass', 'Honey']
df['Least Favorite'] = ['Meat', 'Leaves']

which looks like:

  Animal  Weight Favorite Least Favorite
0    Cow     250    Grass           Meat
1   Bear     450    Honey         Leaves

you can plot a table version of it like so:

import matplotlib.pyplot as plt

fig = plt.figure(figsize=(9,2))
ax = plt.subplot(111)
ax.axis('off')
ax.table(cellText=df.values, colLabels=df.columns, bbox=[0,0,1,1])

Output:

You can style the table plot a little nicer by adding some background color to the cells:

import matplotlib.pyplot as plt

fig = plt.figure(figsize=(9,2))
ax=plt.subplot(111)
ax.axis('off')
c = df.shape[1]
ax.table(cellText=np.vstack([df.columns, df.values]), cellColours=[['lightgray']*c] + [['none']*c]*2, bbox=[0,0,1,1])

Output:

See this ongoing thread (from which all these examples were taken) for more ideas/variants.

Edit

It occurred to me that you might want to plot images and tables on the same figure. You can do so to get results like this:

Here's a link to the tutorial that image came from, which has some example code to help get you started.

Exporting pandas table as pdf

The problem is that you're opening a file to write in bytes mode - that's what the "b" character means in the call to open() - and then passing it string data. Change this:

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

to this:

with open(filename, 'w') as f:
    f.write(template.format(z.to_latex()))

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