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137 lines (119 loc) · 4.16 KB
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from pathlib import Path
import pandas as pd
from dash import Dash, html, dcc, Input, Output, dash_table
import plotly.express as px
external_stylesheets = ["https://codepen.io/chriddyp/pen/bWLwgP.css"]
app = Dash(__name__, external_stylesheets=external_stylesheets)
styles = {"pre": {"border": "thin lightgrey solid", "overflowX": "scroll"}}
src_file = Path.cwd() / "data" / "raw" / "EPA_fuel_economy_summary.csv"
df = pd.read_csv(src_file)
# Define the input parameters
min_year = df["year"].min()
max_year = df["year"].max()
all_years = df["year"].unique()
transmission_types = df["transmission"].unique()
data_table_cols = [
"make",
"model",
"year",
"transmission",
"drive",
"class_summary",
"cylinders",
"displ",
"fuelCost08",
]
# Need to keep track of button clicks to see if there is a change
total_clicks = 0
app.layout = html.Div(
[
html.H1("Fuel Cost Analysis"),
html.Div([
html.P("Talk Python Training Example"),
dcc.Graph(id="histogram-with-slider",
config={"displayModeBar": False}),
dcc.Graph(id="scatter-plot"),
html.Label("Year Range"),
dcc.RangeSlider(
id="year-slider",
min=min_year,
max=max_year,
value=(min_year, max_year),
marks={str(year): str(year)
for year in all_years},
),
html.Label("Transmission type"),
dcc.Checklist(
id="transmission-list",
options=[{
"label": i,
"value": i
} for i in transmission_types],
value=transmission_types,
labelStyle={"display": "inline-block"},
),
html.Hr(),
html.Button("Reset selections", id="reset", n_clicks=0),
html.H3(id="selected_count"),
dash_table.DataTable(
id="data-table",
data=[],
page_size=10,
columns=[{
"name": i,
"id": i
} for i in data_table_cols],
),
]),
],
style={"margin-bottom": "150px"},
)
@app.callback(
Output("histogram-with-slider", "figure"),
Output("scatter-plot", "figure"),
Output("data-table", "data"),
Output("selected_count", "children"),
Input("year-slider", "value"),
Input("transmission-list", "value"),
Input("scatter-plot", "selectedData"),
Input("reset", "n_clicks"),
)
def update_figure(year_range, transmission_list, selectedData, n_clicks):
# Global variables may cause unexepcted behavior in multi-user setup
global total_clicks
filtered_df = df[df["year"].between(year_range[0], year_range[1])
& df["transmission"].isin(transmission_list)]
fig_hist = px.histogram(
filtered_df,
x="fuelCost08",
color="class_summary",
labels={"fuelCost08": "Annual Fuel Cost"},
nbins=40,
)
fig_scatter = px.scatter(
filtered_df,
x="displ",
y="fuelCost08",
hover_data=[filtered_df.index, "make", "model", "year"],
)
fig_scatter.update_layout(clickmode="event", uirevision=True)
fig_scatter.update_traces(selected_marker_color="red")
if n_clicks > total_clicks:
# From here - https://community.plotly.com/t/applying-only-newest-selectedpoints-in-multiple-graphs-or-clearing-selection/31881
fig_scatter.update_traces(selected_marker_color=None)
total_clicks = n_clicks
selectedData = None
if selectedData:
points = selectedData["points"]
index_list = [
points[x]["customdata"][0] for x in range(0, len(points))
]
filtered_df = df[df.index.isin(index_list)]
num_points_label = f"Showing {len(points)} selected points:"
else:
num_points_label = "No points selected - showing top 10 only"
filtered_df = filtered_df.head(10)
return fig_hist, fig_scatter, filtered_df.to_dict(
"records"), num_points_label
if __name__ == "__main__":
app.run_server(debug=True)