![]() Firstly, we have to import libraries we are going to use. Use it as follows: dataframe_to_pdf(df, 'test_1.pdf')ĭataframe_to_pdf(df, 'test_6. This Python script allows to extract tables from PDF files and save them in Excel or CSV format. # Add a part/page number at bottom-center of page as well as to optionally paginate the PDF: import pandas as pdįrom _pdf import PdfPagesĪlternating_colors = * len(df.columns), * len(df.columns)] * len(df)Īlternating_colors = alternating_colorsĬolColours=*len(df.columns),ĭef dataframe_to_pdf(df, filename, numpages=(1, 1), pagesize=(11, 8.5)): When using Matplotlib, here's how to get a prettier table with alternating colors for the rows, etc. I did not use pdfkit, because I had some problems with it on a headless machine. ![]() Thanks to for the pretty printer, see stackoverflowuser2010's answer ![]() Ht += df.to_html(classes='wide', escape=False)į.write(HTML_TEMPLATE1 + ht + HTML_TEMPLATE2)įont-family: Helvetica, Arial, sans-serif Write an entire dataframe to an HTML file ![]() Refer to the docs for the library if you run into any installation errors. Install it by running: pip install tabula-py Make sure you have Java installed in your system. We will be using the tabula-py library for extracting our tables from the pdf files. # This is the table pretty printer used above:ĭef to_html_pretty(df, filename='/tmp/out.html', title=''): A copy of the file pdf file can be found here. Weasyprint.HTML(intermediate_html).write_pdf(out_pdf) # Convert the html file to a pdf file using weasyprint # if you do not want pretty printing, just use pandas: To_html_pretty(df,intermediate_html,'Iris Data') Intermediate_html = '/tmp/intermediate.html' # Pretty print the dataframe as an html table to a file # Create a pandas dataframe with demo data: The pdf conversion is done with weasyprint. The table is pretty printed with some minimal css. This is a solution with an intermediate pdf file.
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