Given that my data is a pandas dataframe and looks like this:
Ref +1 +2 +3 +4 +5 +6 +7
2013-05-28 1 -0.44 0.03 0.06 -0.31 0.13 0.56 0.81
2013-07-05 2 0.84 1.03 0.96 0.90 1.09 0.59 1.15
2013-08-21 3 0.09 0.25 0.06 0.09 -0.09 -0.16 0.56
2014-10-15 4 0.35 1.16 1.91 3.44 2.75 1.97 2.16
2015-02-09 5 0.09 -0.10 -0.38 -0.69 -0.25 -0.85 -0.47
How can I plot a chart of the 5 lines (1 for each ref), where the X axis are the columns (+1, +2...), and starts from 0? If is in seaborn, even better. But matplotlib solutions are also welcome.
Plotting a dataframe in pandas is generally all about reshaping the table so that the individual lines you want are in separate columns, and the x-values are in the index. Some of these reshape operations are a bit ugly, but you can do:
df = pd.read_clipboard()
plot_table = pd.melt(df.reset_index(), id_vars=['index', 'Ref'])
plot_table = plot_table.pivot(index='variable', columns='Ref', values='value')
# Add extra row to have all lines start from 0:
plot_table.loc['+0', :] = 0
plot_table = plot_table.sort_index()
plot_table
Ref 1 2 3 4 5
variable
+0 0.00 0.00 0.00 0.00 0.00
+1 -0.44 0.84 0.09 0.35 0.09
+2 0.03 1.03 0.25 1.16 -0.10
+3 0.06 0.96 0.06 1.91 -0.38
+4 -0.31 0.90 0.09 3.44 -0.69
+5 0.13 1.09 -0.09 2.75 -0.25
+6 0.56 0.59 -0.16 1.97 -0.85
+7 0.81 1.15 0.56 2.16 -0.47
Now that you have a table with the right shape, plotting is pretty automatic:
plot_table.plot()
