def _generate_activity_count_plot(activity_data: pd.DataFrame,
ax: mpl.axes.Axes, colours: str):
"""
Generate a bar plot of activity counts over time (by type).
Arguments:
activity data - A pandas DataFrame containing the activity data.
ax - A set of matplotlib axes to generate the plot on.
colours - A name of the colour palette to generate the plot with.
"""
# Group the activity data by month and calculate the count of each activity type
data = (activity_data.groupby([activity_data.index.to_period('M'), 'type'
]).size().to_frame('count').reset_index())
# Generate and format the bar plot
sns.barplot(x='start_date_local',
y='count',
hue='type',
data=data,
palette=colours,
ax=ax)
ax.set(title='Activities over time',
ylabel='Number of activities',
xlabel='Month')
ax.set_xticklabels(ax.get_xticklabels(),
rotation=45,
horizontalalignment='right')
ax.get_xaxis().set_minor_locator(mpl.ticker.AutoMinorLocator())
ax.get_yaxis().set_minor_locator(mpl.ticker.AutoMinorLocator())
ax.grid(b=True, which='major', linewidth=1.0)
ax.yaxis.grid(b=True, which='minor', linewidth=0.5)
ax.set_axisbelow(True)
def _generate_commute_count_plot(commute_data: pd.DataFrame, ax: mpl.axes.Axes,
colours: dict):
"""
Generate a bar plot of number of commutes per month.
Arguments:
commute_data - A pandas DataFrame containing the commute activity data.
ax - A set of matplotlib axes to generate the plot on.
colours - A dictionary of colours to generate the plot with.
"""
# Group the commute data by month
data = commute_data.resample('M').count()
# Generate and format the bar plot
sns.barplot(x=data.index.to_period('M'),
y=data['distance'],
color=colours['commute_count'],
ax=ax)
ax.set(ylabel='Number of commutes', xlabel='Month')
ax.set_xticklabels(ax.get_xticklabels(),
rotation=45,
horizontalalignment='right')
ax.get_xaxis().set_minor_locator(mpl.ticker.AutoMinorLocator())
ax.get_yaxis().set_minor_locator(mpl.ticker.AutoMinorLocator())
ax.grid(b=True, which='major', linewidth=1.0)
ax.yaxis.grid(b=True, which='minor', linewidth=0.5)
ax.set_axisbelow(True)
def _generate_mean_distance_plot(activity_data: pd.DataFrame,
ax: mpl.axes.Axes, colour_palette: list):
"""
Generate a bar plot of mean activity distance over time (by type).
Arguments:
activity data - A pandas DataFrame containing the activity data.
ax - A set of matplotlib axes to generate the plot on.
colour_palette - The colour palette to generate the plot with.
"""
# Group the activity data by month and calculate the mean distance of each activity type
data = activity_data.groupby([activity_data.index.to_period('Y'),
'type']).mean().reset_index()
# Generate and format the bar plot
sns.barplot(x='start_date_local',
y='distance',
hue='type',
data=data,
palette=colour_palette,
ax=ax)
ax.set(title='Mean activity distance over time',
ylabel='Mean distance (km)',
xlabel='Year')
ax.set_xticklabels(ax.get_xticklabels(),
rotation=45,
horizontalalignment='right')
ax.get_xaxis().set_minor_locator(mpl.ticker.AutoMinorLocator())
ax.get_yaxis().set_minor_locator(mpl.ticker.AutoMinorLocator())
ax.grid(b=True, which='major', linewidth=1.0)
ax.yaxis.grid(b=True, which='minor', linewidth=0.5)
ax.set_axisbelow(True)
