Plot different DataFrames in the same figure

I have a temperature file with many years temperature records, in a format as below:

2012-04-12,16:13:09,20.6
2012-04-12,17:13:09,20.9
2012-04-12,18:13:09,20.6
2007-05-12,19:13:09,5.4
2007-05-12,20:13:09,20.6
2007-05-12,20:13:09,20.6
2005-08-11,11:13:09,20.6
2005-08-11,11:13:09,17.5
2005-08-13,07:13:09,20.6
2006-04-13,01:13:09,20.6

Every year has different numbers, time of the records, so the pandas datetimeindices are all different.

I want to plot the different year’s data in the same figure for comparing . The X-axis is Jan to Dec, the Y-axis is temperature. How should I go about doing this?

Answers:

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Method 1

Try:

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

Method 2

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.

Method 3

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()

Method 4

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)

Method 5

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)

Method 6

You can make use of the hue parameter in seaborn. For example:

import seaborn as sns
df = sns.load_dataset('flights')

     year month  passengers
0    1949   Jan         112
1    1949   Feb         118
2    1949   Mar         132
3    1949   Apr         129
4    1949   May         121
..    ...   ...         ...
139  1960   Aug         606
140  1960   Sep         508
141  1960   Oct         461
142  1960   Nov         390
143  1960   Dec         432

sns.lineplot(x='month', y='passengers', hue='year', data=df)

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0