Suppose I have a DataFrame I want to export to a PDF. In the DataFrame I have the following columns: Code, Name, Price, Net, Sales. Every row is a Product.
I want to add to every product in that DataFrame an image which i could get using BeautifulSoup. Is there some way to add the image to the DataFrame? Not the link, just the image of the product.
Being more specific i want something like this:
import pandas as pd df = pd.DataFrame([['A231', 'Book', 5, 3, 150], ['M441', 'Magic Staff', 10, 7, 200]], columns = ['Code', 'Name', 'Price', 'Net', 'Sales') #Suppose this are the links that contains the imagen i want to add to the DataFrame images = ['Link 1','Link 2']
You’ll probably have to play a bit around with width and height attributes, but this should get you started. Basically, you’re just converting the image/links to html, then using the df.to_html to display those tags. Note, it won’t show if you’re working in Spyder, but as you can see below with my output, works fine through jupyter notebooks
import pandas as pd from IPython.core.display import display,HTML df = pd.DataFrame([['A231', 'Book', 5, 3, 150], ['M441', 'Magic Staff', 10, 7, 200]], columns = ['Code', 'Name', 'Price', 'Net', 'Sales']) # your images images = ['https://vignette.wikia.nocookie.net/2007scape/images/7/7a/Mage%27s_book_detail.png/revision/latest?cb=20180310083825', 'https://i.pinimg.com/originals/d9/5c/9b/d95c9ba809aa9dd4cb519a225af40f2b.png'] df['image'] = images # convert your links to html tags def path_to_image_html(path): return '<img src="'+ path + '" width="60" >' pd.set_option('display.max_colwidth', None) display(HTML(df.to_html(escape=False ,formatters=dict(image=path_to_image_html))))
Then you have some options of what to do there to go to pdf.
You could save as html
df.to_html('test_html.html', escape=False, formatters=dict(image=path_to_image_html))
then simply use and html to pdf converter here, or use a library such as pdfkit or WeasyPrint. I’m not entirely familiar with those (I only used one of them once a long time ago), but here’s a good link