def get_emissions_timeseries(code_structure=None):
"""
Render and update a barplot figure to show emissions evolution with time
"""
# Load chorus dt data based on chosen code_structure
# TODO: improve and standardize data import logic
chorus_dt_df = ch.get_structure_data(code_structure)
chorus_dt_df["year_month"] = chorus_dt_df[
"date_debut_mission"].dt.to_period("M")
timeseries_df = chorus_dt_df.groupby(["year_month"
])["distance"].sum().reset_index()
fig = go.Figure()
fig.add_trace(
go.Scatter(
x=timeseries_df["year_month"].astype(str),
y=timeseries_df["distance"].values,
mode="lines+markers",
line=dict(width=3),
))
fig.update_layout(plot_bgcolor="white",
template="plotly_white",
margin={
"t": 30,
"r": 30,
"l": 30
},
xaxis=xaxis_format)
return fig
def get_donut_by_prestation_type(code_structure=None):
"""
Render and update a donut figure to show emissions distribution by prestation type
"""
# Load chorus dt data based on chosen code_structure
# TODO: improve and standardize data import logic
chorus_dt_df = ch.get_structure_data(code_structure)
prestation_df = chorus_dt_df.groupby(["prestation_type"])["distance"].sum().reset_index()
fig = go.Figure(data=[go.Pie(labels=prestation_df.prestation_type, values=prestation_df["distance"], hole=0.3)])
fig.update_layout(plot_bgcolor="white", template="plotly_white", margin={"t": 30, "r": 30, "l": 30})
return fig
def update_graphs(selected_entity, n_clicks, prestation_types: list, years, unreliable):
oc = OrganizationChart()
oc.load_current()
service = oc.get_entity_by_id(selected_entity)
chorus_dt_df = ch.get_structure_data(service.code_chorus).copy()
if "fiable" not in chorus_dt_df.columns:
chorus_dt_df["fiable"] = True
filters = (
chorus_dt_df.prestation.isin(prestation_types)
& chorus_dt_df.date_debut_mission.dt.year.isin(years)
& (chorus_dt_df.fiable.isin(unreliable) | chorus_dt_df.fiable)
)
chorus_dt_df = chorus_dt_df.loc[filters, :]
return [
get_kpi_emissions(chorus_dt_df),
get_kpi_trips_count(chorus_dt_df),
get_kpi_distance(chorus_dt_df),
get_donut_by_prestation_type(chorus_dt_df),
get_scatter_by_emission(chorus_dt_df),
get_emissions_timeseries(chorus_dt_df),
get_hist_top_emission(chorus_dt_df),
get_dashtable_by_emission(chorus_dt_df),
]
def load_data(self):
self.chorus_dt_df = ch.get_structure_data(self.service.code_chorus)
self.odrive_df = ov.get_structure_data(self.service.code_odrive)
self.osfi_df = oh.get_structure_data(self.service.code_osfi)