I need to open a bar charts in Matplotlib in a browser-Like Firefox- but I shouldn't use Bokeh in my Project. Any suggestions?
Use the WebAgg backend, which opens a browser window with the plot and is fully interactive like the Qt or GTK window.
import matplotlib as mpl
mpl.use('WebAgg')
import matplotlib.pyplot as plt
# do your plotting
plt.show()
For example:
>>> import numpy as np
>>> a=np.random.random(100)
>>> b=np.random.random(100)
>>> plt.plot(a,b)
Opens http://127.0.0.1:8988/ showing:
IPython with %matplotlib inline as demonstrated here
Related
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import style
style.use("fivethirtyeight")
df = pd.DataFrame({'day':[1,2,3,4,5],'visitors':[200,302,480,590,680],'Bounce_rate':[20,30,40,50,60]})
df.set_index('day',inplace=True)
df.plot()
plt.show()
output is <Figure size 640x480 with 1 Axes>, the desired output is a graph (in VS Code).
I can see my code is correct when using cloud jupyter by achieving the desired output but it's not possible in VS Code jupyter view...
Am I doing something wrong? or is it something else?
Embed IPython in a script and run:
from IPython import embed
# code ...
embed()
%matplotlib
#^ With or without; same result
fig = plt.figure()
Can't do anything with fig at this point.
It's already shown and the window is displayed,
even though I never called show.
plt.show() # does absolutely nothing
I normally import matplotlib in IPython this way:
%matplotlib inline
import matplotlib.pyplot as plt
ax, fig = plt.subplots()
plt.plot([[1,1], [2,2]])
plt.show()
Does this help?
I used matplotlib to create a graphics window, but I do not want the user to manually close it. Is there a way to disable the closing button in the upper right corner? See screenshot
The solution will depend on the backend in use.
PyQt
For the PyQt backend, you can do the following:
import matplotlib
# make sure Qt backend is used
matplotlib.use("Qt4Agg")
from PyQt4 import QtCore
import matplotlib.pyplot as plt
# create a figure and some subplots
fig, ax = plt.subplots(figsize=(4,2))
ax.plot([2,3,5,1])
fig.tight_layout()
win = plt.gcf().canvas.manager.window
win.setWindowFlags(win.windowFlags() | QtCore.Qt.CustomizeWindowHint)
win.setWindowFlags(win.windowFlags() & ~QtCore.Qt.WindowCloseButtonHint)
plt.show()
This will disable the close button (not hide it).
Tk
I'm not sure if Tk is able to control the close button. But what is possible is to draw a completely frameless window.
import matplotlib
# make sure Tk backend is used
matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
# create a figure and some subplots
fig, ax = plt.subplots(figsize=(4,2))
ax.plot([2,3,5,1])
fig.tight_layout()
win = plt.gcf().canvas.manager.window
win.overrideredirect(1) # draws a completely frameless window
plt.show()
When I run a program with PyCharm, it doesn't display graphs made with Matplotlib. E.g.:
import matplotlib.pyplot as plt
[...]
plt.imshow(montage(W / np.max(W)), cmap='coolwarm')
I tried calling
plt.interactive(False)
first, but it didn't make a difference.
Running the same program with ipython3, the graphs are displayed.
I set a default back-end for my system in matplotlibrc (TkAgg), and that did the trick.
The below code worked for me:
in pycharm-community-2018.2.2
import matplotlib.pyplot as plt
df.boxplot(column='ApplicantIncome')
plt.show()
I am interested in using the interact function to use a slider to adjust the position of text in a matplotlib plot (you know, instead of adjusting the position, running the code, and repeating 1000 times).
Here's a simple example of a plot
import matplotlib.pyplot as plt
x=0.2
y=0.9
plt.text(x, y,'To move',size=19)
plt.show()
and some interact code
from __future__ import print_function
from ipywidgets import interact, interactive, fixed
import ipywidgets as widgets
def f(x):
return x
interact(f, cx=0.2)
I'm wondering how I can combine these to generate a plot with the text along with a slider that will interactively move the text based on the specified value for x. Is this possible? What if I want to do the same for y?
Thanks in advance!
Here you go:
%matplotlib inline
import matplotlib.pyplot as plt
from ipywidgets import interact
def do_plot(x=0.2, y=0.9):
plt.text(x, y,'To move',size=19)
plt.show()
interact(do_plot)