python plotly plotly-dash dash-bootstrap-components

Plot bar chart with separate color legend - dash Plotly

I'm trying to plot certain values using dash as a bar chart but use a separate column to map the colors. Using below, I'm plotting dates as a bar-chart that corresponds to a drop down bar.

Is it possible to keep the dates as the x-axis but use DOW (day of the week) as a discrete color map? I'll attach the current output below. The dates get plotted but there are a few issues.

The string formatting for each date in the dropdown isn't in date time

The color map isn't sequenced to the day of the week

import dash
from dash import dcc
from dash import html
from dash.dependencies import Input, Output
import dash_bootstrap_components as dbc
import plotly.express as px
import plotly.graph_objs as go
import pandas as pd
from datetime import datetime as dt

df = pd.DataFrame({
       'Type': ['A','B','B','B','C','C','D','E','E','E','E','F','F','F'],
       })

N = 30
df = pd.concat([df] * N, ignore_index=True)

df['TIMESTAMP'] = pd.date_range(start='2022/01/01 07:30', end='2022/01/30 08:30', periods=len(df))
df['TIMESTAMP'] = pd.to_datetime(df['TIMESTAMP'], dayfirst = True).sort_values()

df['DATE'], df['TIME'] = zip(*[(d.date(), d.time()) for d in df['TIMESTAMP']])
df['DATE'] = pd.to_datetime(df['DATE'])

df = df.sort_values(by = 'DATE')

df['DOW'] = df['DATE'].dt.weekday
df = df.sort_values('DOW').reset_index(drop=True)
df['DOW'] = df['DATE'].dt.day_name()


external_stylesheets = [dbc.themes.SPACELAB, dbc.icons.BOOTSTRAP]

app = dash.Dash(__name__, external_stylesheets = external_stylesheets)

filter_box = html.Div(children=[

    html.Div(children=[
        html.Label('Day of the week:', style={'paddingTop': '2rem'}),
        dcc.Dropdown(
            id='DATE',
            options=[
                {'label': x, 'value': x} for x in df['DATE'].unique()
            ],
            value=df['DATE'].unique(),
            multi=True
        ),

    ], className="four columns",
    style={'padding':'2rem', 'margin':'1rem'} )

])

app.layout = dbc.Container([
    dbc.Row([
        dbc.Col(html.Div(filter_box, className="bg-secondary h-100"), width=2),
        dbc.Col([
            dbc.Row([
                dbc.Col(dcc.Graph(id = 'date-bar-chart'), 
                    ),
            ]),
        ], width=5),
    ])
], fluid=True)


@app.callback(
    Output('date-bar-chart', 'figure'),
    [Input("DATE", "value"),
    ])     

def date_chart(date):

    dff = df[df['DATE'].isin(date)]
    count = dff['DATE'].value_counts()

    data = px.bar(x = count.index, 
                  y = count.values,
                  #color = dff['DOW'],
                  )

    layout = go.Layout(title = 'Date')
    fig = go.Figure(data = data, layout = layout) 

    return fig


if __name__ == '__main__':
    app.run_server(debug=True, port = 8051)

Solution

Not sure why do you want to use DATE as Dropdown but I think you should change it to string and then pass it to dcc.Dropdown. Used the previous way to add color_discrete_map I think you can revise your code as below:

import dash
from dash import dcc
from dash import html
from dash.dependencies import Input, Output
import dash_bootstrap_components as dbc
import plotly.express as px
import plotly.graph_objs as go
import pandas as pd
from datetime import datetime as dt
from dash.exceptions import PreventUpdate

df = pd.DataFrame({
       'Type': ['A','B','B','B','C','C','D','E','E','E','E','F','F','F'],
       })

N = 30
df = pd.concat([df] * N, ignore_index=True)

df['TIMESTAMP'] = pd.date_range(start='2022/01/01 07:30', end='2022/01/30 08:30', periods=len(df))
df['TIMESTAMP'] = pd.to_datetime(df['TIMESTAMP'], dayfirst = True).sort_values()

df['DATE'], df['TIME'] = zip(*[(d.date(), d.time()) for d in df['TIMESTAMP']])
df['DATE'] = pd.to_datetime(df['DATE'],format='%Y-%m-%d')

df = df.sort_values(by = 'DATE')

df['DOW'] = df['DATE'].dt.weekday
df = df.sort_values('DOW').reset_index(drop=True)
df['DOW'] = df['DATE'].dt.day_name()
df['DATE'] = df['DATE'].astype(str)
df['Color'] = df['DOW'].map(dict(zip(df['DOW'].unique(),
                    px.colors.qualitative.Plotly[:len(df['DOW'].unique())])))

Color = df['Color'].unique()
Category = df['DOW'].unique()

Color = df['Color'].unique()
Category = df['DOW'].unique()

cats = dict(zip(Category,Color)) 
external_stylesheets = [dbc.themes.SPACELAB, dbc.icons.BOOTSTRAP]

app = dash.Dash(__name__, external_stylesheets = external_stylesheets)

filter_box = html.Div(children=[

    html.Div(children=[
        html.Label('Day of the week:', style={'paddingTop': '2rem'}),
        dcc.Dropdown(
            id='DATE',
            options=[
                {'label': x, 'value': x} for x in df['DATE'].unique()
            ],
            value=df['DATE'].unique(),
            multi=True
        ),

    ], className="four columns",
    style={'padding':'2rem', 'margin':'1rem'} )

])

app.layout = dbc.Container([
    dbc.Row([
        dbc.Col(html.Div(filter_box, className="bg-secondary h-100"), width=2),
        dbc.Col([
            dbc.Row([
                dbc.Col(dcc.Graph(id = 'date-bar-chart'), 
                    ),
            ]),
        ], width=5),
    ])
], fluid=True)


@app.callback(
    Output('date-bar-chart', 'figure'),
    [Input("DATE", "value"),
    ])     

def date_chart(date):
    if date:
        dff = df[df['DATE'].isin(date)]
        count = dff.groupby(['DATE',"DOW"])['DATE'].count().reset_index(name='counts')
        data = px.bar(x = count['DATE'], 
                  y = count['counts'],
                  color = count['DOW'],
                  color_discrete_map = cats,
                  )

        layout = go.Layout(title = 'Date')
        fig = go.Figure(data = data, layout = layout) 

        return fig
    else:
        raise PreventUpdate


if __name__ == '__main__':
    app.run_server(debug=False, port = 8051)

I used groupby in callback to return new dataframe and then use it to make graph. Hope this help.