Question: suppose i have the following code which creates one matplotlib figure with two axes, the second of which has x-axis labels as dates:

```
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import datetime as dt    

x1 = np.arange(0,30)
x2 = pd.date_range('1/1/2016', periods=30, freq='D')
y1 = np.random.randn(30)
y2 = np.random.randn(30)

%matplotlib inline
fig, ax = plt.subplots(1,2, figsize=(18,5))
ax[0].scatter(x1,y1)
ax[1].scatter(x2,y2)

```

displaying this in an ipython notebook will show the x axis labels of the graph on the right as running into one another. i would like to rotate the labels to improve visibility. all of the documentation and online searching seems to suggest one of the following 2 options (both after the last line above): 

**#1**

```
plt.setp(ax[1].xaxis.get_majorticklabels(),rotation=90,horizontalalignment='right')

```

**or #2**

```
plt.xticks(rotation=90)

```

either of these will work but will also print a list of labels (which for some reason is different in the first example than in the second)

how do i accomplish the rotation/display without also outputting some array?

Answer: 
i was able to use this approach. not sure if it is the most elegant way, but it works without outputting an array

```
for tick in ax[1].get_xticklabels():
    tick.set_rotation(90)

```
A bit late, so just for future reference:

Jupyter notebooks always print the return value from the last command in a cell.
I would just suppress this by adding another function or statement that doesn't return anything, instead of searching for a workaround for the actual function you want to call. 

So you could do:

```
plt.xticks(rotation=90)
pass

```

or:

```
plt.xticks(rotation=90)
plt.show()

```