Develop Reference

Seaborn heatmap: annotate with clickable hyperlink

Is there a way to annotate a seaborn heatmap with a clickable hyperlink in Jupyter notebook? The documentation explains clearly how to create simple annotated heatmaps. My question is, is it possible to make the annotations clickable in Jupyter?

In principle the answer creating a clickable hyperlink in a matplotlib figure in jupyter is given in Python matlplotlib add hyperlink to text. To apply it to a heatmap, one would need to add the texts manually. I.e. one would in that case not use seaborn to create the heatmap, but matplotlib directly.
The following creates an annotated heatmap where you can click on any number and be directed to the respective page on wolframalpha.
import numpy as np
import matplotlib.pyplot as plt
from IPython.display import set_matplotlib_formats
set_matplotlib_formats("svg")
data = np.random.randint(1,50, size=(3,3))
fig, ax = plt.subplots()
im=ax.imshow(data)
fig.colorbar(im)
for (j,i), x in np.ndenumerate(data):
url = "https://www.wolframalpha.com/input/?i={}".format(x)
ax.annotate(x, xy=(i,j), ha="center", va="center",
url=url, bbox=dict(color='w', alpha=1e-6, url=url))

unwanted blank subplots in matplotlib

I am new to matplotlib and seaborn and is currently trying to practice the two libraries using the classic titanic dataset. This might be elementary, but I'm trying to plot two factorplots side by side by inputting the argument ax = matplotlib axis as shown in the code below:
import matploblib.pyplot as plt
import seaborn as sns
%matplotlib inline
fig, (axis1,axis2) = plt.subplots(1,2,figsize=(15,4))
sns.factorplot(x='Pclass',data=titanic_df,kind='count',hue='Survived',ax=axis1)
sns.factorplot(x='SibSp',data=titanic_df,kind='count',hue='Survived',ax=axis2)
I was expecting the two factorplots side by side, but instead of just that, I ended up with two extra blank subplots as shown above
Edited: image was not there

Any call to sns.factorplot() actually creates a new figure, although the contents are drawn to the existing axes (axes1, axes2). Those figures are shown together with the original fig.
I guess the easiest way to prevent those unused figures from showing up is to close them, using plt.close(<figure number>).
Here is a solution for a notebook
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
%matplotlib inline
titanic_df = pd.read_csv(r"https://github.com/pcsanwald/kaggle-titanic/raw/master/train.csv")
fig, (axis1,axis2) = plt.subplots(1,2,figsize=(15,4))
sns.factorplot(x='pclass',data=titanic_df,kind='count',hue='survived',ax=axis1)
sns.factorplot(x='sibsp',data=titanic_df,kind='count',hue='survived',ax=axis2)
plt.close(2)
plt.close(3)
(For normal console plotting, remove the %matplotlib inline command and add plt.show() at the end.)

How to save Matplotlib.pyplot.loglog to file?

I am trying to generate the log-log plot of a vector, and save the generated plot to file.
This is what I have tried so far:
import matplotlib.pyplot as plt
...
plt.loglog(deg_distribution,'b-',marker='o')
plt.savefig('LogLog.png')
I am using Jupyter Notebook, in which I get the generated graph as output after statement 2 in the above code, but the saved file is blank.

Notice that pyplot has the concept of the current figure and the current axes. All plotting commands apply to the current axes. So, make sure you plot in the right axes. Here is a WME.
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.loglog(range(100), 'b-',marker='o')
plt.savefig('test.png') # apply to the axes `ax`

putting some text to a python plot

I'm trying to do a correlation plot using python, so I'm starting with this basic example
import numpy as np
import matplotlib.pyplot as plt
image=np.random.rand(10,10)
plt.imshow(image)
plt.colorbar()
plt.show()
ok, this script give to me an image like this
so the next step is to put my dataset and not a random matrix, i know it, but I want to put some axis or text in this plot, and to get something like this image
It is a very pretty image using paint (lol), but someone can say me what way I need to follow to do something like thik please (how to search it in google).
Before to post it I think in labels, but also I think that I can assign only one label to each axis
cheers

As #tcaswell said in the comments, the function you want to use is annotate, and the documentation can be found here.
I've given an example below using your code above:
import numpy as np
import matplotlib.pyplot as plt
def annotate_axes(x1,y1,x2,y2,x3,y3,text):
ax.annotate('', xy=(x1, y1),xytext=(x2,y2), #draws an arrow from one set of coordinates to the other
arrowprops=dict(arrowstyle='<->'), #sets style of arrow
annotation_clip=False) #This enables the arrow to be outside of the plot
ax.annotate(text,xy=(0,0),xytext=(x3,y3), #Adds another annotation for the text
annotation_clip=False)
fig, ax = plt.subplots()
image=np.random.rand(10,10)
plt.imshow(image)
plt.colorbar()
#annotate x-axis
annotate_axes(-0.5,10,4.5,10,2.5,10.5,'A') # changing these changes the position of the arrow and the text
annotate_axes(5,10,9.5,10,7.5,10.5,'B')
#annotate y-axis
annotate_axes(-1,0,-1,4,-1.5,2,'A')
annotate_axes(-1,4.5,-1,9.5,-1.5,7.5,'B')
plt.show()
This give the image shown below:

Blank image when saving an imshow matplotlib figure in iPython notebook

I'm using iPython notebook w/ matplotlib to display a bunch of images inline, but now it's come time to save a number of these images (think for-loop, i.e. not a small number of images to save). My issue seems to be something to do with how I'm using iPython since I could do this alright when my script was a standalone.
%matplotlib inline
import matplotlib.pyplot as plt
....
grid_z2 = griddata(....)
fig = plt.figure()
ax = fig.add_axes([1,1,1,1])
plt.imshow(grid_z2.transpose(),origin='Lower')
plt.colorbar()
plt.draw()
fig.savefig('slicemap.png')
I have also tried plt.savefig(), fig1 = plt.gcf() before plt.imshow then trying to save fig1... always every single time a blank file.
Any suggestions?