I am using the anaconda distribution of ipython/Qt console. I want to plot things inline so I type the following from the ipython console:
%pylab inline
Next I type the tutorial at (http://pandas.pydata.org/pandas-docs/dev/visualization.html) into ipython...
import matplotlib.pyplot as plt
import pandas as pd
ts = pd.Series(randn(1000), index = pd.date_range('1/1/2000', periods=1000))
ts = ts.cumsum()
ts.plot()
... and this is all that i get back:
<matplotlib.axes.AxesSubplot at 0x109253410>
But there is no plot. What could be wrong? Is there another command that I need to supply? The tutorial suggests that that is all that I need to type.
Plots are not displayed until you run
plt.show()
There could be 2 ways to approach this problem:
1) Either invoke the inline/osx/qt/gtk/gtk3/tk backend. Depends on the ipython console that you have been using. So, simply do:
%matplotlib inline #Here the inline backend is invoked, which removes the necessity of calling show after each plot.
or for ipython/qt console, do:
%matplotlib qt #This one works for me, thus, depends on the ipython console you use.
#
2) Or, do the traditional way as aforementioned (already answered above on this page):
plt.show() #However, you will have to call this show function each time.
Related
I'm using pycharm to run some code using Seaborn. I'm very new to python and am just trying to learn the ropes so I'm following a tutorial online. I've imported the necessary libraries and have run the below code
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
# import the data saved as a csv
df = pd.read_csv('summer-products-with-rating-and-performance_2020-08.csv')
df["has_urgency_banner"] = df["has_urgency_banner"].fillna(0)
df["discount"] = (df["retail_price"] -
df["price"])/df["retail_price"]
df["rating_five_percent"] = df["rating_five_count"]/df["rating_count"]
df["rating_four_percent"] = df["rating_four_count"]/df["rating_count"]
df["rating_three_percent"] = df["rating_three_count"]/df["rating_count"]
df["rating_two_percent"] = df["rating_two_count"]/df["rating_count"]
df["rating_one_percent"] = df["rating_one_count"]/df["rating_count"]
ratings = [
"rating_five_percent",
"rating_four_percent",
"rating_three_percent",
"rating_two_percent",
"rating_one_percent"
]
for rating in ratings:
df[rating] = df[rating].apply(lambda x: x if x>= 0 and x<= 1 else 0)
# Distribution plot on price
sns.histplot(df['price'])
My output is as follows:
Process finished with exit code 0
so I know there are no errors in the code but I don't see any graphs anywhere as I'm supposed to.
Ive found a way around this by using this at the end
plt.show()
which opens a new tab and uses matplotlib to show me a similar graph.
However in the code I'm using to follow along, matplotlib is not imported or used (I understand that seaborn has built in Matplotlib functionality) as in the plt.show statement is not used but the a visual graph is still achieved.
I've also used print which gives me the following
AxesSubplot(0.125,0.11;0.775x0.77)
Last point to mention is that the code im following along with uses the following
import seaborn as sns
# Distribution plot on price
sns.distplot(df['price'])
but distplot has now depreciated and I've now used histplot because I think that's the best alternative vs using displot, If that's incorrect please let me know.
I feel there is a simple solution as to why I'm not seeing a graph but I'm not sure if it's to do with pycharm or due to something within the code.
matplotlib is a dependency of seaborn. As such, importing matplotlib with import matplotlib.pyplot as plt and calling plt.show() does not add any overhead to your code.
While it is annoying that there is no sns.plt.show() at this time (see this similar question for discussion), I think this is the simplest solution to force plots to show when using PyCharm Community.
Importing matplotlib in this way will not affect how your exercises run as long as you use a namespace like plt.
Be aware the 'data' must be pandas DataFrame object, not: <class 'pandas.core.series.Series'>
I using this, work finely:
# Distribution plot on price
sns.histplot(df[['price']])
plt.show()
Running following code inside python interpretor displays a figure with random values
>>>fig = plt.figure();ax1 = fig.add_subplot(111);plt.ion();ax1 = ax1.imshow(np.random.rand(256,256))
while running the following script as a file does not display any output/figure.
import numpy as np
import matplotlib.pyplot as plt
import time
fig = plt.figure()
ax1 = fig.add_subplot(111)
plt.ion()
ax1 =ax1.imshow(np.random.rand(256,256))
what is the reason for difference in behaviour?
I suspect what is going on is that
matplotlib.rcParams['interactive'] == True
and this is set in your .matplotlibrc file.
which means that plt.show is non-blocking (so that you get a figure that you can interact with and an command prompt you can type more code at). However, in the case of a script the (implicit) plt.show does not block so the script exits, taking the figure with it.
I suggest the setting the interactive rcparam to False and then either explitily setting it to true in the repl or (the preferred method) use IPython and the %matplotlib magic.
Introduction
As I am coming from matlab, I am used to an interactive interface where a script can update figures while it is running. During the processing each figure can be re-sized or even closed. This probably means that each figure is running in its own thread which is obviously not the case with matplotlib.
IPython can imitate the Matlab behavior using the magic command %pylab or %matplotlib which does something that I don't understand yet and which is the very point of my question.
My goal is then to allow standalone Python scripts to work as Matlab does (or as IPython with %matplotlib does). In other words, I would like this script to be executed from the command line. I am expecting a new figure that pop-up every 3 seconds. During the execution I would be able to zoom, resize or even close the figure.
#!/usr/bin/python
import matplotlib.pyplot as plt
import time
def do_some_work():
time.sleep(3)
for i in range(10):
plt.plot([1,2,3,4])
plt.show() # this is way too boilerplate, I'd like to avoid it too.
do_some_work()
What alternative to %matplotlib I can use to manipulate figures while a script is running in Python (not IPython)?
What solutions I've already investigated?
I currently found 3 way to get a plot show.
1. %pylab / %matplotlib
As tom said, the use of %pylab should be avoided to prevent the namespace to be polluted.
>>> %pylab
>>> plot([1,2,3,4])
This solution is sweet, the plot is non-blocking, there is no need for an additionnal show(), I can still add a grid with grid() afterwards and I can close, resize or zoom on my figure with no additional issues.
Unfortunately the %matplotlib command is only available on IPython.
2. from pylab import * or from matplotlib.pyplot import plt
>>> from pylab import *
>>> plot([1,2,3,4])
Things are quite different here. I need to add the command show() to display my figure which is blocking. I cannot do anything but closing the figure to execute the next command such as grid() which will have no effect since the figure is now closed...
** 3. from pylab import * or from matplotlib.pyplot import plt + ion()**
Some suggestions recommend to use the ion() command as follow:
>>> from pylab import *
>>> ion()
>>> plot([1,2,3,4])
>>> draw()
>>> pause(0.0001)
Unfortunately, even if the plot shows, I cannot close the figure manually. I will need to execute close() on the terminal which is not very convenient. Moreover the need for two additional commands such as draw(); pause(0.0001) is not what I am expecting.
Summary
With %pylab, everything is wonderful, but I cannot use it outside of IPython
With from pylab import * followed by a plot, I get a blocking behavior and all the power of IPython is wasted.
from pylab import * followed by ion offers a nice alternative to the previous one, but I have to use the weird pause(0.0001) command that leads to a window that I cannot close manually (I know that the pause is not needed with some backends. I am using WxAgg which is the only one that works well on Cygwin x64.
This question advices to use matplotlib.interactive(True). Unfortunately it does not work and gives the same behavior as ion() does.
Change your do_some_work function to the following and it should work.
def do_some_work():
plt.pause(3)
For interactive backends plt.pause(3) starts the event loop for 3 seconds so that it can process your resize events. Note that the documentation says that it is an experimental function and that for complex animations you should use the animation module.
The, %pylab and %matplotlib magic commands also start an event loop, which is why user interaction with the plots is possible. Alternatively, you can start the event loop with %gui wx, and turn it off with %gui. You can use the IPython.lib.guisupport.is_event_loop_running_wx() function to test if it is running.
The reason for using ion() or ioff() is very well explained in the 'What is interactive mode' page. In principle, user interaction is possible without IPython. However, I could not get the interactive-example from that page to work with the Qt4Agg backend, only with the MacOSX backend (on my Mac). I didn't try with the WX backend.
Edit
I did manage to get the interactive-example to work with the Qt4Agg backend by using PyQt4 instead of PySide (so by setting backend.qt4 : PyQt4 in my ~/.config/matplotlibrc file). I think the example doesn't work with all backends. I submitted an issue here.
Edit 2
I'm afraid I can't think of a way of manipulating the figure while a long calculation is running, without using threads. As you mentioned: Matplotlib doesn't start a thread, and neither does IPython. The %pylab and %matplotlib commands alternate between processing commands from the read-eval-print loop and letting the GUI processing events for a short time. They do this sequentially.
In fact, I'm unable to reproduce your behavior, even with the %matplotlib or %pylab magic. (Just to be clear: in ipython I first call %matplotlib and then %run yourscript.py). The %matplotlib magic puts Matplotlib in interactive-mode, which makes the plt.show() call non-blocking so that the do_some_work function is executed immediately. However, during the time.sleep(3) call, the figure is unresponsive (this becomes even more apparent if I increase the sleeping period). I don't understand how this can work at your end.
Unless I'm wrong you'll have to break up your calculation in smaller parts and use plt.pause (or even better, the animation module) to update the figures.
My advice would be to keep using IPython, since it manages the GUI event loop for you (that's what pylab/pylot does).
I tried interactive plotting in a normal interpreter and it worked the way it is expected, even without calling ion() (Debian unstable, Python 3.4.3+, Matplotlib 1.4.2-3.1). If I recall it right, it's a fairly new feature in Matplotlib.
Alternatively, you can also use Matplotlib's animation capabilities to update a plot periodically:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import time
plt.ion()
tt = np.linspace(0, 1, 200)
freq = 1 # parameter for sine
t0 = time.time() # for measuring ellapsed time
fig, ax = plt.subplots()
def draw_func(i):
""" This function gets called repeated times """
global freq # needed because freq is changed in this function
xx = np.sin(2*np.pi*freq*tt)/freq
ax.set_title("Passed Time: %.1f s, " % (time.time()-t0) +
"Parameter i=%d" % i)
ax.plot(tt, xx, label="$f=%d$ Hz" % freq)
ax.legend()
freq += 1
# call draw_func every 3 seconds 1 + 4 times (first time is initialization):
ani = animation.FuncAnimation(fig, draw_func, np.arange(4), interval=3000,
repeat=False)
# plt.show()
Checkout matplotlib.animation.FuncAnimation for details. You'll find further examples in the examples section.
I have a problem using pyplot. I am new to Python so sorry if I am doing some obvious mistake.
After I have plotted something using pyplot it shows the graph, but when I then try and add e.g. ylabel it will not update the current graph. It results in a new graph with only the ylabel, not previously entered information. So to me it seems to be a problem with recognizing the current graph/axis, but the ishold delivers a True statement.
My setup is Python 2.7 in Python(x,y). The problem occurs both in the Spyder IDE and the IPython Qt Console. It does however not occur in the regular IPython console (which, by constrast, is not interactive, but everything is included when using show(). When I turn off interactive in Spyder/Qt console it does not show anything after using the show() command).
import matplotlib.pyplot as plt
plt.plot([1,2,3,4])
Out[2]: [<matplotlib.lines.Line2D at 0x78ca370>]

plt.ylabel('test')
Out[3]: <matplotlib.text.Text at 0x5bd5990>

plt.ishold()
Out[4]: True
matplotlib.get_backend()
Out[6]: 'module://IPython.kernel.zmq.pylab.backend_inline'
Hope any of you have some input. Thanks.
This is one of the things were InlineBackend have to behave differently from other backend or you would have sort of a memory leak. You have to keep explicit handle to matplotlib figure and/or set close_figure to False in config. Usually pyplot is a compatibility layer for matlab for convenience, try to learn to do using the Object Oriented way.
fig,ax = subplots()
ax.plot(range(4))
ax.set_ylabel('my label')
...
I'm working to migrate from MatLab to python in Sage.
So I use these commands and I faced this error in Sage:
from scipy import misc
l = misc.lena();
import pylab as pl
pl.imshow(l)
The Error or message (i don't know) is:
matplotlib.image.AxesImage object at 0xb80198c
And it doesn't show any image
It's not an error, just print the object that method returned.
There are two ways to show the figure:
Add pl.show() after calling pl.imshow(l)
Use ipython --pylab to open your python shell,
That is an object being returned from pylab after using the "imshow" command. That is the location of the Axes image object.
documentation:
http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.imshow
Looks like it says it displays the object to the current axes. If you havent already created a plot I imagine you wont see anything
Simple google search suggests this might be what you are looking for
http://docs.scipy.org/doc/scipy/reference/generated/scipy.misc.lena.html
from scipy import misc
l = misc.lena();
import pylab as pl
pl.imshow(l)
####use this
pl.show()