Plot multiple time series

Visualizing Time Series Data in Python

Thomas Vincent

Head of Data Science, Getty Images

Clarity is key

In this plot, the default matplotlib color scheme assigns the same color to the beef and turkey time series.

Color cycles in matplotlib

The colormap argument

ax = df.plot(colormap='Dark2', figsize=(14, 7))
ax.set_xlabel('Date')
ax.set_ylabel('Production Volume (in tons)')

plt.show()

For the full set of available colormaps, click here.

Changing line colors with the colormap argument

Changing color schemes for time series visualization

Enhancing your plot with information

ax = df.plot(colormap='Dark2', figsize=(14, 7))

df_summary = df.describe()

# Specify values of cells in the table
ax.table(cellText=df_summary.values, 
        # Specify width of the table
        colWidths=[0.3]*len(df.columns), 
        # Specify row labels
        rowLabels=df_summary.index, 
        # Specify column labels
        colLabels=df_summary.columns, 
        # Specify location of the table
        loc='top') 

plt.show()

Adding Statistical summaries to your plots

Dealing with different scales

Time series for beef and veal

Only veal

Time series for veal only

Facet plots

df.plot(subplots=True,
                linewidth=0.5,
                layout=(2, 4),
                figsize=(16, 10),
                sharex=False,
                sharey=False)

plt.show()

Facet plots

Time for some action!

Visualizing Time Series Data in Python