In Django, It is easy to render the HTML templates by setting URLs of respective HTML pages. Here we will let to know about how we can work with DataFrame to modify them for table view in the HTML template or web-pages, and for that, we have to use ‘render’ and ‘HttpResponse’ functions to manipulate the data inside the DataFrame.
Methods to render dataframe to html template –
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Using pandas.DataFrame.to_html(): By using this inbuilt function ‘to_html()‘ to convert DataFrame into HTML template. After using this method, the overall DataFrame is converted to ‘table’ html element, while the name of each column are transformed into ‘thead’ tag of table head. Whereas, each row of the DataFrame is transformed into ‘tr’ tag of table row element in HTML template page.
views.pyfromdjango.shortcutsimportHttpResponseimportpandas as pddefTable(request):df=pd.read_csv("tableview/static/csv/20_Startups.csv")#'tableview/static/csv/20_Startups.csv' is the django# directory where csv file exist.# Manipulate DataFrame using to_html() functiongeeks_object=df.to_html()returnHttpResponse(geeks_object)urls.py
"""The `urlpatterns` list routes URLs to views. For more information please see:Function views1. Add an import: from my_app import views2. Add a URL to urlpatterns: path('', views.home, name ='home')Class-based views1. Add an import: from other_app.views import Home2. Add a URL to urlpatterns: path('', Home.as_view(), name ='home')Including another URLconf1. Import the include() function: from django.urls import include, path2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))"""fromdjango.contribimportadminfromdjango.urlsimportpathfromtableviewimportviewsurlpatterns=[path('admin/', admin.site.urls),path('', views.Table, name="table"),]- Parsing DataFrame into Json objects and render into bootstrap template: Here we use proper bootstrap template and get a table view using render() function.
views.py# Write Python3 code herefromdjango.shortcutsimportrenderimportpandas as pdimportjson# Create your views here.defTable(request):df=pd.read_csv("tableview/static/csv/20_Startups.csv")# parsing the DataFrame in json format.json_records=df.reset_index().to_json(orient='records')data=[]data=json.loads(json_records)context={'d': data}returnrender(request,'table.html', context)table.html (‘Bootstrap HTML Template’)
<!-- Write HTML code here --><!DOCTYPE html><htmllang="en"><head><title>TableView - Startup</title><metacharset="utf-8"><metaname="viewport"content="width=device-width, initial-scale=1"><linkrel="stylesheet"href="https://maxcdn.bootstrapcdn.com/bootstrap/4.5.0/css/bootstrap.min.css"></head><body><divclass="container"><h2class="text-center"><u>20 - Startups Table</u></h2><br><tableclass="table table-dark table-striped"><thead><tr><th>R&D Spend</th><th>Administration</th><th>Marketing Spend</th><th>State</th><th>Profit</th></tr></thead><tbody><!-- jinja2 Technique -->{% if d %}{% for i in d %}<tr><td>{{i.RD_Spend}}</td><td>{{i.Administration}}</td><td>{{i.Marketing_Spend}}</td><td>{{i.State}}</td><td>{{i.Profit}}</td></tr>{% endfor %}{% endif %}</tbody></table></div></body></html> - Parsing DataFrame into Json objects and render into bootstrap template: Here we use proper bootstrap template and get a table view using render() function.
