# python – How to make inline plots in Jupyter Notebook larger?

## The Question :

305 people think this question is useful

I have made my plots inline on my Ipython Notebook with “%matplotlib inline.”

Now, the plot appears. However, it is very small. Is there a way to make it appear larger using either notebook settings or plot settings?

212 people think this answer is useful

Yes, play with figuresize and dpi like so (before you call your subplot):

fig=plt.figure(figsize=(12,8), dpi= 100, facecolor='w', edgecolor='k')



As @tacaswell and @Hagne pointed out, you can also change the defaults if it’s not a one-off:

plt.rcParams['figure.figsize'] = [12, 8]
plt.rcParams['figure.dpi'] = 100 # 200 e.g. is really fine, but slower



445 people think this answer is useful

The default figure size (in inches) is controlled by

matplotlib.rcParams['figure.figsize'] = [width, height]



For example:

import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = [10, 5]



creates a figure with 10 (width) x 5 (height) inches

70 people think this answer is useful

I have found that %matplotlib notebook works better for me than inline with Jupyter notebooks.

Note that you may need to restart the kernel if you were using %matplotlib inline before.

Update 2019: If you are running Jupyter Lab you might want to use %matplotlib widget

40 people think this answer is useful

If you only want the image of your figure to appear larger without changing the general appearance of your figure increase the figure resolution. Changing the figure size as suggested in most other answers will change the appearance since font sizes do not scale accordingly.

import matplotlib.pylab as plt
plt.rcParams['figure.dpi'] = 200



24 people think this answer is useful

The question is about matplotlib, but for the sake of any R users that end up here given the language-agnostic title:

If you’re using an R kernel, just use:

options(repr.plot.width=4, repr.plot.height=3)



13 people think this answer is useful

To adjust the size of one figure:

import matplotlib.pyplot as plt

fig=plt.figure(figsize=(15, 15))



To change the default settings, and therefore all your plots:

import matplotlib.pyplot as plt

plt.rcParams['figure.figsize'] = [15, 15]



1 people think this answer is useful

A small but important detail for adjusting figure size on a one-off basis (as several commenters above reported “this doesn’t work for me”):

You should do plt.figure(figsize=(,)) PRIOR to defining your actual plot. For example:

This should correctly size the plot according to your specified figsize:

values = [1,1,1,2,2,3]
_ = plt.figure(figsize=(10,6))
_ = plt.hist(values,bins=3)
plt.show()



Whereas this will show the plot with the default settings, seeming to “ignore” figsize:

values = [1,1,1,2,2,3]
_ = plt.hist(values,bins=3)
_ = plt.figure(figsize=(10,6))
plt.show()



1 people think this answer is useful

using something like:

import matplotlib.pyplot as plt
%matplotlib inline
plt.subplots(figsize=(18,8 ))
plt.subplot(1,3,1)
plt.subplot(1,3,2)
plt.subplot(1,3,3)



The output of the command

0 people think this answer is useful

A quick fix to “plot overlap” is to use plt.tight_layout():

### Example (in my case)

for i,var in enumerate(categorical_variables):
plt.title(var)
plt.xticks(rotation=45)
df[var].hist()
plt.subplot(len(categorical_variables)/2, 2, i+1)

plt.tight_layout()