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bike_dashboard.py
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bike_dashboard.py
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"""bike count dashboard in dash"""
import dash
import dash_html_components as html
import dash_core_components as dcc
import pandas as pd
import plotly.graph_objects as go
import plotly.express as px
from dash.dependencies import Input, Output
from barchart_helper import (
Frequency,
prepare_dataframe,
get_parts_for_barchart,
frequency_dict,
streets_dict,
)
from comparison_helper import ComparisonBetweenStations, prepare_comparison_df, aggregate, map_colors
from polar_helper import prepare_data_for_polar
external_stylesheets = ["https://codepen.io/chriddyp/pen/bWLwgP.css"]
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
# Read in the data and transform
df = pd.read_csv("berlin_bikedata_2017-2019.csv")
prepare_dataframe(df)
comparison_df = df.set_index("timestamp")
# Create empty figures
comparison_fig = go.Figure()
barchart_fig = go.Figure()
fig = go.Figure()
# Dashboard layout
app.layout = html.Div(
[
# First row
html.Div(
[
# Image and Input container left
html.Div(
[
html.Div(
[
html.Img(
id="bike image",
height="240px",
src="assets/undraw_bike_ride_7xit.png",
),
html.P("This Bike Traffic Dashboard shows data from bicycle counters in Berlin. \nEach bicycle counter counts the amount of bicycles passing per hour. \nData is accessible starting from 2012, with most data points starting from 2017. \nThis dashboard includes the latest data from 2017 through 2019. \nThe original data can be accessed here.", title="About"),
html.H3("Bicycle Counter", className="filter"),
html.H4("Year:", className="control_label"),
dcc.Dropdown(
id="year-dropdown",
options=[
{"label": "2017", "value": "2017"},
{"label": "2018", "value": "2018"},
{"label": "2019", "value": "2019"},
],
clearable=False,
multi=True,
value=[2019],
placeholder="year",
),
html.H4("Station:", className="control_label"),
dcc.Dropdown(
id="station-dropdown",
options=[
{"label": item, "value": item}
for item in df["description"].unique().tolist()
],
clearable=False,
multi=False,
value="Maybachufer",
placeholder="station",
),
html.H4("Timeframe:", className="control_label"),
dcc.Dropdown(
id="timeframe-dropdown",
options=[
{"label": "hour", "value": "hour_str"},
{"label": "day", "value": "day_name"},
{"label": "month", "value": "month_name"},
],
clearable=False,
multi=False,
value="hour_str",
placeholder="timeframe",
),
html.H4("Radial Range:", className="control_label"),
dcc.Dropdown(
id="radialrange-dropdown",
options=[
{"label": "max", "value": "max"},
{"label": "median", "value": "median"},
],
clearable=False,
multi=False,
value="max",
placeholder="radial range",
),
], className="pretty-container"),
],
className="basic-container-column three columns",
),
# Title and main-graph container right
html.Div(
[
html.Div(
[
html.H1(
"BICYCLE COUNTERS IN BERLIN - DASHBOARD",
)
],
className="pretty-container",
),
html.Div(
[
#
html.Iframe(
id="map",
srcDoc=open(
"folium_maps/Maybachufer.html", "r"
).read(),
width="100%",
height="300",
),
],
className="pretty-container",
),
html.Div([
html.Div(
[
dcc.Graph(
id="scatter-polar",
figure=fig,
),
],
className="pretty-container",
),
html.Div(
[
dcc.Graph(
id="comparison-bar",
figure=comparison_fig,
),
],
className="pretty-container",
),
], className="basic-container",),
],
className="basic-container-column twelve columns",
),
],
className="basic-container",
),
# Second row
html.Div(
[
# Barchart left
html.Div(
[
html.Div(
[
dcc.Graph(
id="bar-chart",
figure=barchart_fig,
),
],
className="pretty-container",
),
],
className="basic-container-column twelve columns",
),
# Dropdowns right
html.Div(
[
html.H3("Bicycle Counter", className="filter"),
html.H4("Street:", className="control_label"),
dcc.Dropdown(
id="two-direction-station-dropdown",
options=[
{"label": key, "value": value}
for key, value in streets_dict.items()
],
style={
"flex-grow": "2",
},
clearable=False,
multi=False,
value="21",
placeholder="station",
),
html.H4("Frequency:", className="control_label"),
dcc.Dropdown(
id="frequency-dropdown",
options=[
{"label": "Day", "value": "Day"},
{"label": "Week", "value": "Week"},
{"label": "Month", "value": "Month"},
{"label": "Year", "value": "Year"},
],
style={
"flex-grow": "2",
},
clearable=False,
multi=False,
value="Month",
placeholder="frequency",
),
],
className="pretty-container three columns",
),
],
className="basic-container",
),
]
)
@app.callback(
[Output("scatter-polar", "figure"), Output("map", "srcDoc"), Output("comparison-bar", "figure")],
[
Input("year-dropdown", "value"),
Input("station-dropdown", "value"),
Input("timeframe-dropdown", "value"),
Input("radialrange-dropdown", "value"),
],
)
def update_fig(year, station, timeframe, radialrange):
"""updates polar chart"""
is_year = df["year"].isin(year)
complete_df = df[is_year]
category_sorters = {"day_name": "weekday", "hour_str": "hour", "month_name": "month"}
df_median, df_max, radialrange_dict, categories = prepare_data_for_polar(
complete_df, timeframe, category_sorters, station
)
fig = go.Figure()
fig.add_trace(
go.Scatterpolar(
r=df_max["total_bikes"],
theta=categories,
fill="toself",
name="max",
fillcolor="lightgreen",
mode="markers",
text=df_max["location"],
marker_color="lightgreen",
hovertemplate="<b>%{text}</b><br><i>%{theta}</i><br><br>Max: %{r} bikes<extra></extra>",
)
)
fig.add_trace(
go.Scatterpolar(
r=df_median["total_bikes"],
theta=categories,
fill="toself",
name="median",
fillcolor="dodgerblue",
mode="markers",
marker_color="dodgerblue",
text=df_median["location"],
hovertemplate="<b>%{text}</b><br><i>%{theta}</i><br><br>Median: %{r} bikes<extra></extra>",
)
)
fig.update_layout(
showlegend=True,
title=f"Maximum and Median Bikes for {station}",
title_x=0.5,
height=500,
polar=dict(
radialaxis_tickfont_size=10,
radialaxis=dict(range=[0, radialrange_dict[radialrange]]),
angularaxis=dict(
tickfont_size=10,
rotation=90, # start position of angular axis
direction="clockwise",
),
),
)
# Prepare data for comparison bar chart
aggregation_type = "sum"
x_label = "Total Bikes"
if radialrange == "median":
aggregation_type = "mean"
x_label = "Average Bikes"
comparison = ComparisonBetweenStations(year, aggregation_type)
agg_comp_df = aggregate(comparison_df, comparison)
stations_list, color_map = map_colors(agg_comp_df, station)
# Bar chart with total or average bikes by year and bicycle counter
comparison_fig = px.bar(
agg_comp_df.reset_index(),
x="total_bikes",
y="description",
color=stations_list,
color_discrete_map=color_map,
orientation="h",
height=500,
labels={"total_bikes": x_label, "description": "Bicycle Counter"},
)
comparison_fig.add_annotation(
text=f"{comparison.years_string}",
xref="paper",
yref="paper",
x=1,
y=-0.05,
showarrow=False,
opacity=0.1,
font=dict(family="Arial", size=70, color="black"),
)
comparison_fig.update_traces(hovertemplate=f"<b>%{{y}}</b><br><b>Bikes</b>: %{{x:.0f}}<extra></extra>")
comparison_fig.update_xaxes(tickfont=dict(size=11))
comparison_fig.update_yaxes(tickfont=dict(size=11))
comparison_fig.update_layout(showlegend=False, title="All Stations (Total and Average)",
title_x=0.5)
return fig, open(f"folium_maps/{station}.html", "r").read(), comparison_fig
@app.callback(
Output("bar-chart", "figure"),
[
Input("two-direction-station-dropdown", "value"),
Input("frequency-dropdown", "value"),
],
)
def update_barchart_fig(street, frequency):
"""updates bar chart"""
barchart_object = Frequency(frequency, frequency_dict, street)
barchart_df, barchart_title = get_parts_for_barchart(df, barchart_object)
barchart_fig = px.bar(
barchart_df[barchart_df.station_short == barchart_object.location_id],
x="timestamp",
y="total_bikes",
color="description",
color_discrete_sequence=["dodgerblue", "purple"],
title=barchart_title,
labels={
"total_bikes": "Total Bikes",
"description": "Street",
"timestamp": f"{frequency}",
},
)
barchart_fig.update_traces(hovertemplate=barchart_object.hovertext)
barchart_fig.update_layout(
xaxis=dict(
rangeselector=dict(
buttons=list(
[
dict(count=1, label="1m", step="month", stepmode="backward"),
dict(count=6, label="6m", step="month", stepmode="backward"),
dict(count=1, label="YTD", step="year", stepmode="todate"),
dict(count=1, label="1y", step="year", stepmode="backward"),
dict(step="all"),
]
)
),
rangeslider=dict(visible=True),
type="date",
)
)
return barchart_fig
if __name__ == "__main__":
app.run_server(debug=False)