How to create a form Django (names and elements) from a column of a DataFrame or QuerySet column.?

How can I create a form - even if it's not a Django form, but a regular one via input? So that the names and elements of the form fields are taken from a column of a DataFrame or QuerySet column. I would like the form fields not to be set initially, but to be the result of data processing - in the form of data from a column of a DataFrame or QuerySet column. The name of the form fields to fill in from the data in Views.

Maybe send a list or a single DataFrame or QuerySet to the template via JINJA?

from django import forms
  
# creating a form 
class InputForm(forms.Form):
  
    first_name = forms.CharField(max_length = 200)
    last_name = forms.CharField(max_length = 200)
    roll_number = forms.IntegerField(
                     help_text = "Enter 6 digit roll number"
                     )
    password = forms.CharField(widget = forms.PasswordInput())

from django.shortcuts import render
from .forms import InputForm
  
# Create your views here.
def home_view(request):
    context ={}
    context['form']= InputForm()
    return render(request, "home.html", context)

<form action = "" method = "post">
    {% csrf_token %}
    <table>
        {{ form.as_table }}
    </table>
    <input type="submit" value="Submit">
</form>

How to create a form Django (names and elements of the form fields) from a column of a DataFrame or QuerySet column.?

This is how you can generate a form using a list of column names.

# Create your views here.
def home_view(request):
    context ={}
    context['fields']= ['column1', 'column2', ... ]
    return render(request, "home.html", context)


# home.html
<form>
{% csrf_token %}
{% for name in fields %}
  <label for="{{ name }}">{{ name }}</label>
  <input type="text" name="{{ name }}">
{% endfor %}
</form>

And to get the column names from a QuerySet or DataFrame, you can do something like this

# from queryset
context['fields'] = list(your_model.objects.all().values()[0])

# or from dataframe
context['fields'] = list(your_dataframe.columns.values)
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