

In [1]:

    
%matplotlib inline
from ggplot import *
import pandas as pd

`scale_y_log`

scale_y_log applies a logarithmic scale to your y-axis. Its parameters are:

base - base value logarithm. defaults to 10



In [2]:

    
ggplot(diamonds, aes(x='carat', y='price')) + \
    geom_point() + \
    scale_y_log()









    












    Out[2]:





<ggplot: (284426693)>



In [3]:

    
pageviews['hour'] = pageviews.date_hour.apply(lambda x: x.hour)
ggplot(pageviews, aes(x='hour', weight='pageviews')) + \
    geom_bar()









    












    Out[3]:





<ggplot: (285670021)>



In [4]:

    
ggplot(pageviews, aes(x='hour', weight='pageviews')) + \
    geom_bar() + \
    scale_y_log()









    












    Out[4]:





<ggplot: (289832569)>



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