title: Converting a list as a dictionary value to a cell in pandas
body: <p>I have a dictionary for a product I have been scraping on this website:
  <a href="https://www.adamhall.com/shop/gi-en/cables-connectors/pre-assembled-cables/microphone-cables/3323/4-star-mmf-1000" rel="nofollow noreferrer">https://www.adamhall.com/shop/gi-en/cables-connectors/pre-assembled-cables/microphone-cables/3323/4-star-mmf-1000</a>
  I get the image links as a list into a product dictionary, which I want to import into a DataFrame as a cell value in the column images. However, the output makes the data frame have as many rows as there are image links.</p>
  <p>Here is my code so far:</p>
  <pre><code>from requests_html import HTMLSession
  import pandas as pd
  
  
  url = 'https://www.adamhall.com/shop/gi-en/cables-connectors/pre-assembled-cables/microphone-cables/3323/4-star-mmf-1000'
  
  # product_properties=
  
  def get_product(url):
    s = HTMLSession()
    r = s.get(url)
    
    images = r.html.find('img.js-zoom-image')
    links=[]
    for image in images:
      link = image.attrs['data-zoom']
      links.append(link)
  
    product = {
      'id': r.html.find('div.right-item', first=True).text.strip(),
      'title': r.html.find('h1.articlename', first=True).text.strip().replace('\n',' '),
      'description':r.html.find('div.description &gt;p', first=True).text.strip(),
      'details': r.html.find('div.js-accordion__content.specification__content', first=True).text.strip(),
      'image':links,
      
      }
    return product
  
  AHdf=pd.DataFrame(get_product(url))
  
  print(AHdf)
  </code></pre>
  <p>Here is what gets returned:</p>
  <pre><code>              id  ...                                              image
  0  K4MMF1000  ...  https://cdn-shop.adamhall.com/ORIGINAL/media/M...
  1  K4MMF1000  ...  https://cdn-shop.adamhall.com/ORIGINAL/media/M...
  </code></pre>
  <p>I would like it to have just one row, with all the image links as a list of items, separated by a comma in one cell in the 'image' column.</p>