I run a several code and get
Draw = pf.plot_drawdown_periods(returns, top=5).set_xlabel('Date')
type(Draw)
<matplotlib.text.Text at 0x7fb063733f90>
How can make my result visible in different ways?
You need to explicitly call pyplot.show() to display the graphics.
import matplotlib.pyplot as plt
pf.plot_drawdown_periods(returns, top=5).set_xlabel('Date')
plt.show()
Related
I need to create a figure in a file without displaying it within IPython notebook. I am not clear on the interaction between IPython and matplotlib.pylab in this regard. But, when I call pylab.savefig("test.png") the current figure get's displayed in addition to being saved in test.png. When automating the creation of a large set of plot files, this is often undesirable. Or in the situation that an intermediate file for external processing by another app is desired.
Not sure if this is a matplotlib or IPython notebook question.
This is a matplotlib question, and you can get around this by using a backend that doesn't display to the user, e.g. 'Agg':
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.plot([1,2,3])
plt.savefig('/tmp/test.png')
EDIT: If you don't want to lose the ability to display plots, turn off Interactive Mode, and only call plt.show() when you are ready to display the plots:
import matplotlib.pyplot as plt
# Turn interactive plotting off
plt.ioff()
# Create a new figure, plot into it, then close it so it never gets displayed
fig = plt.figure()
plt.plot([1,2,3])
plt.savefig('/tmp/test0.png')
plt.close(fig)
# Create a new figure, plot into it, then don't close it so it does get displayed
plt.figure()
plt.plot([1,3,2])
plt.savefig('/tmp/test1.png')
# Display all "open" (non-closed) figures
plt.show()
We don't need to plt.ioff() or plt.show() (if we use %matplotlib inline). You can test above code without plt.ioff(). plt.close() has the essential role. Try this one:
%matplotlib inline
import pylab as plt
# It doesn't matter you add line below. You can even replace it by 'plt.ion()', but you will see no changes.
## plt.ioff()
# Create a new figure, plot into it, then close it so it never gets displayed
fig = plt.figure()
plt.plot([1,2,3])
plt.savefig('test0.png')
plt.close(fig)
# Create a new figure, plot into it, then don't close it so it does get displayed
fig2 = plt.figure()
plt.plot([1,3,2])
plt.savefig('test1.png')
If you run this code in iPython, it will display a second plot, and if you add plt.close(fig2) to the end of it, you will see nothing.
In conclusion, if you close figure by plt.close(fig), it won't be displayed.
I managed to make a displot as I intended with seaborn and the only thing I want to change is the bars' outline width. Specifically, I want to make it thinner. Here's the code and a sample of how the dataframe is composed.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
data_final = pd.merge(data, data_filt)
q = sns.displot(data=data_final[data_final['cond_state'] == True], y='Brand', hue='Style', multiple='stack')
plt.title('Sample of brands and their offering of ramen styles')
I'm specifying that the plot should only use rows where the cond_state is True. Here is a sample of the data_final dataframe.
Here is how the plot currently looks like.
I've tried various ways published online, but most of them use the deprecated distplot instead of displot. There also doesn't seem to be a parameter for changing the bars' outline width in the seaborn documentation for displot and FacetGrid
The documentation for the seaborn displot function doesn't have this parameter listed, but you can pass matplotlib axes arguments, such as linewidth = 0.25, to the seaborn.displot function to solve your problem.
i need to make a polar plot with just the main data content visible.
for now i have managed to get the following image by using these simple codes.
but there is still one outline circle left around it. how can i remove it
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
data = np.random.randint(1800,2200,(24*60))
data = list(data)
data.append(data[0])
print(data)
theta = np.arange(0,360+360/(24*60),360/(24*60))*np.pi/180
plt.polar(theta, data)
plt.xticks([])
plt.yticks([])
plt.savefig("p.png")
plt.show()
This should do the trick:
plt.box(on=None)
Solution inspired from the Q: Removing frame while keeping axes in pyplot subplots
I am making a python script using the PyCharm IDE, and the idea is to display descriptive statistics and a box plot for each group in a DataFrame. The statistics displays, but the boxplot is nowhere to be seen...
I have tried Googling an answer, but it does not seem this question have been answered before.
import pandas as pd
import matplotlib as plt
(...)
for name, group in grouped:
if len(group) > 3:
print("\n\nNAME: {}".format(name))
print("GROUP: {}".format(group))
print("DESCRIPTIVE STATISTICS
{}".format(group.distance2.describe()))
print(group.distance2.plot.box())
group.distance2.plot.box()
I do not get any error messages, the code runs and completes, but I do not know where the boxplot is supposed to display.
I think the code as it is does not create a matplotlib figure object. Try creating a test data object for group.distance2, then create a matplotlib boxplot object. I am assuming you are using the matplotlib library.
import matplotlib.pyplot as plt
for name, group in grouped:
if len(group) > 3:
data = group.distance2
# create a matplotlib figure object
fig, axs = plt.subplots(1, 1)
# basic plot
axs[0, 0].boxplot(data)
axs[0, 0].set_title('basic plot of group.distance2')
plt.show()
It that works, you can try putting several group data into one figure (axes). Here is more information: https://matplotlib.org/3.1.0/gallery/statistics/boxplot_demo.html
I put multiple heatmaps in one figure with matplotlib. I cannot layout it well. Here is my code.
import matplotlib; matplotlib.use('agg')
import matplotlib.pyplot as plt
import numpy as np
x = np.random.rand(6,240,240)
y = np.random.rand(6,240,240)
t = np.random.rand(6,240,240)
plt.subplots_adjust(wspace=0.2, hspace=0.3)
c=1
for i in range(6):
ax=plt.subplot(6,3,c)
plt.imshow(x[i])
ax.set_title("x"+str(i))
c+=1
ax=plt.subplot(6,3,c)
plt.imshow(y[i])
ax.set_title("y"+str(i))
c+=1
ax=plt.subplot(6,3,c)
plt.imshow(t[i])
ax.set_title("t"+str(i))
c+=1
plt.tight_layout()
plt.savefig("test.png")
test.png looks like this.
I want to
make each heatmap bigger
reduce the margin between each heatmaps in row.
I tried to adjust by "subplots_adjust", but it doesn't work.
Additional information
According to ImportanceOfBeingErnest's comment, I removed tight_layout(). It generated this.
It makes bigger each heatmap, but titles overlappes on subplots. And I still want to make each heatmap more bigger, and I want to reduce the margin in row.