Hands-On Exploratory Data Analysis with Python

Grouping time series data

We can group the data by different time periods and present them in box plots:

1. We can first group the data by months and then use the box plots to visualize the data:

fig, axes = plt.subplots(3, 1, figsize=(8, 7), sharex=True)for name, ax in zip(['Consumption', 'Solar', 'Wind'], axes):  sns.boxplot(data=df_power, x='Month', y=name, ax=ax)  ax.set_ylabel('GWh')  ax.set_title(name)  if ax != axes[-1]:    ax.set_xlabel('') 

The output of the preceding code is given here:

The preceding plot illustrates that electricity consumption is generally higher in the winter and lower in the summer. Wind production is higher during ...