So, bear with me as I'm VERY new to Django, Python, and web-development in general. What I want to do is display a graph that I've made using matplotlib. I had it working to where the home page automatically redirects to the png of the graph (basically a tab in the browser with the graph displayed). However, now what I want is to see the actual homepage with the graph simply embedded. In other words, I want to see the navigation bar, etc. and then the graph in the body of the site.
So far, I've searched and I sort of have an idea of how to accomplish this. What I'm thinking is having a special view that simply returns the graph. Then, somehow accessing this png image from an img src tag in my template that I will use to display my data.
Graph Code:
from django.shortcuts import render
import urllib
import json
from django.http import HttpResponse
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
import datetime as dt
import pdb
def index(request):
stock_price_url = 'https://www.quandl.com/api/v3/datatables/WIKI/PRICES.json?ticker=GOOGL&date.gte=20151101&qopts.columns=date,close&api_key=KEY'
date = []
price = []
#pdb.set_trace()
source_code = urllib.request.urlopen(stock_price_url).read().decode()
json_root = json.loads(source_code)
json_datatable = json_root["datatable"]
json_data = json_datatable["data"]
for day in json_data:
date.append(dt.datetime.strptime(day[0], '%Y-%m-%d'))
price.append(day[1])
fig=Figure()
ax = fig.add_subplot(1,1,1)
ax.plot(date, price, '-')
ax.set_xlabel('Date')
ax.set_ylabel('Price')
ax.set_title("Google Stock")
canvas = FigureCanvas(fig)
response = HttpResponse(content_type='image/png')
#canvas.print_png(response)
return response
Template Code:
{% extends "home/header.html" %}
{% block content %}
<p>Search a stock to begin!</p>
<img src="home/graph.py" />
{% endblock %}
What I'm getting now:
Current Page
November 15, 2021. When building applications using Django, you may need to present data visualizations using graphs and charts. Matplotlib is one of the popular Python libraries that lets you achieve this functionality.
I know this question is tagged as matplotlib, but I needed to do the same thing and I have found plotly to be easier to use and visually appealing as well. You can simply plot a graph and then in the view get the html code of the graph as :
# fig is plotly figure object and graph_div the html code for displaying the graph
graph_div = plotly.offline.plot(fig, auto_open = False, output_type="div")
# pass the div to the template
In the template do:
<div style="width:1000;height:100">
{{ graph_div|safe }}
</div>
I searched quite a bit until I found a solution that worked for me when it comes to rendering a matplotlib image on a Django page. Often, simply a lengthy string was printed instead of a visualization being produced. So, what finally worked for me was the following:
First, the imports:
import matplotlib.pyplot as plt
from io import StringIO
import numpy as np
The dummy function returning a graphic is the following:
def return_graph():
x = np.arange(0,np.pi*3,.1)
y = np.sin(x)
fig = plt.figure()
plt.plot(x,y)
imgdata = StringIO()
fig.savefig(imgdata, format='svg')
imgdata.seek(0)
data = imgdata.getvalue()
return data
This one can be called by some other function using and rendering the image returned by return_graph()
:
def home(request):
context['graph'] = return_graph()
return render(request, 'x/dashboard.html', context)
And in the dashboard.html
file, the graphic is embedded by the following command:
{{ graph|safe }}
I think you should uncoment this line:
#canvas.print_png(response)
You can easily return plot using django HttpResponse instead using some extra libs. In the matplotlib there is a FigureCanvasAgg which gives you access to canvas where plot is rendered. Finaly you can simple return it as HttpResonse. Here you have very basic example.
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.backends.backend_agg import FigureCanvasAgg
from django.http import HttpResponse
def plot(request):
# Data for plotting
t = np.arange(0.0, 2.0, 0.01)
s = 1 + np.sin(2 * np.pi * t)
fig, ax = plt.subplots()
ax.plot(t, s)
ax.set(xlabel='time (s)', ylabel='voltage (mV)',
title='About as simple as it gets, folks')
ax.grid()
response = HttpResponse(content_type = 'image/png')
canvas = FigureCanvasAgg(fig)
canvas.print_png(response)
return response
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