display django-pandas dataframe in a django template

to_html is a function, you have to call it.

def index2(request):
    df = read_frame(Product.objects.all())
    return HttpResponse(df.to_html())

Here is a minimal but elegant solution using Django_Pandas and an 'extended Bootstrap table' (https://github.com/wenzhixin/bootstrap-table)

The elegance comes from the ability to export a Pandas DataFrame to JSON, and for the Bootstrap Table script to consume that JSON content.

The HTML table is written for us, we don't need to worry about it (look below where we just include the 'table' tag without writing the rows ourselves, or even a for loop.) And it's interactive. And Bootstrap makes it look pretty.

requirements: Bootstrap, JQuery, Django_Pandas, wenzhixin/bootstrap-table

models.py

from django.db import models
from django_pandas.managers import DataFrameManager

class Product(models.Model):
  product_name=models.TextField()
  objects = models.Manager()
  pdobjects = DataFrameManager()  # Pandas-Enabled Manager 

views.py

from models import Product
def ProductView(request):
  qs = Product.pdobjects.all()  # Use the Pandas Manager
  df = qs.to_dataframe()
  template = 'product.html'

  #Format the column headers for the Bootstrap table, they're just a list of field names, 
  #duplicated and turned into dicts like this: {'field': 'foo', 'title: 'foo'}
  columns = [{'field': f, 'title': f} for f in Product._Meta.fields]
  #Write the DataFrame to JSON (as easy as can be)
  json = df.to_json(orient='records')  # output just the records (no fieldnames) as a collection of tuples
  #Proceed to create your context object containing the columns and the data
  context = {
             'data': json,
             'columns': columns
            }
  #And render it!
  return render(request, template, context)

product.html

<script src='/path/to/bootstrap.js'>
<script src='/path/to/jquery.js'>
<script src='/path/to/bootstrap-table.js'>
<script src='/path/to/pandas_bootstrap_table.js'>
<table id='datatable'></table>
<!-- Yep, all you need is a properly identified
     but otherwise empty, table tag! -->

pandas_bootstrap_table.js

$(function() {
  $('#datatable')({
    striped: true,
    pagination: true,
    showColumns: true,
    showToggle: true,
    showExport: true,
    sortable: true,
    paginationVAlign: 'both',
    pageSize: 25,
    pageList: [10, 25, 50, 100, 'ALL'],
    columns: {{ columns|safe }},  // here is where we use the column content from our Django View
    data: {{ data|safe }}, // here is where we use the data content from our Django View. we escape the content with the safe tag so the raw JSON isn't shown.
  });
});