Plot different DataFrames in the same figure

Question

Try:

ax = df1.plot()
df2.plot(ax=ax)

If you a running Jupyter/Ipython notebook and having problems using;

ax = df1.plot()

df2.plot(ax=ax)

Run the command inside of the same cell!! It wont, for some reason, work when they are separated into sequential cells. For me at least.

Although Chang's answer explains how to plot multiple times on the same figure, in this case you might be better off in this case using a groupby and unstacking:

(Assuming you have this in dataframe, with datetime index already)

In [1]: df
Out[1]:
            value  
datetime                         
2010-01-01      1  
2010-02-01      1  
2009-01-01      1  

# create additional month and year columns for convenience
df['Month'] = map(lambda x: x.month, df.index)
df['Year'] = map(lambda x: x.year, df.index)    

In [5]: df.groupby(['Month','Year']).mean().unstack()
Out[5]:
       value      
Year    2009  2010
Month             
1          1     1
2        NaN     1

Now it's easy to plot (each year as a separate line):

df.groupby(['Month','Year']).mean().unstack().plot()

To do this for multiple dataframes, you can do a for loop over them:

fig = plt.figure(num=None, figsize=(10, 8))
ax = dict_of_dfs['FOO'].column.plot()
for BAR in dict_of_dfs.keys():
    if BAR == 'FOO':
        pass
    else:
        dict_of_dfs[BAR].column.plot(ax=ax)

Just to enhance @adivis12 answer, you don't need to do the if statement. Put it like this:

fig, ax = plt.subplots()
for BAR in dict_of_dfs.keys():
    dict_of_dfs[BAR].plot(ax=ax)