plotly_activity_chart.py

# MIT LICENSE


import datetime
import plotly.graph_objs as go
from plotly.subplots import make_subplots
import numpy as np
import dash_core_components as dcc
import dash_html_components as html
import dash


def display_year(
    z,
    year: int = None,
    month_lines: bool = True,
    fig=None,
    row: int = None
):
    
    if year is None:
        year = datetime.datetime.now().year
        
    d1 = datetime.date(year, 1, 1)
    d2 = datetime.date(year, 12, 31)

    number_of_days = (d2-d1).days + 1
    
    data = np.ones(number_of_days) * np.nan
    data[:len(z)] = z
    

    d1 = datetime.date(year, 1, 1)
    d2 = datetime.date(year, 12, 31)

    delta = d2 - d1
    
    month_names = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
    month_days =   [31,    28,    31,     30,    31,     30,    31,    31,    30,    31,    30,    31]
    if number_of_days == 366:  # leap year
        month_days[1] = 29
    month_positions = (np.cumsum(month_days) - 15)/7

    dates_in_year = [d1 + datetime.timedelta(i) for i in range(delta.days+1)] # list with datetimes for each day a year
    weekdays_in_year = [i.weekday() for i in dates_in_year] # gives [0,1,2,3,4,5,6,0,1,2,3,4,5,6,…] (ticktext in xaxis dict translates this to weekdays
    
    weeknumber_of_dates = []
    for i in dates_in_year:
        inferred_week_no = int(i.strftime("%V"))
        if inferred_week_no >= 52 and i.month == 1:
            weeknumber_of_dates.append(0)
        elif inferred_week_no == 1 and i.month == 12:
            weeknumber_of_dates.append(53)
        else:
            weeknumber_of_dates.append(inferred_week_no)
    
    text = [str(i) for i in dates_in_year] #gives something like list of strings like ‘2018-01-25’ for each date. Used in data trace to make good hovertext.
    #4cc417 green #347c17 dark green
    colorscale=[[False, '#eeeeee'], [True, '#76cf63']]
    
    # handle end of year
    

    data = [
        go.Heatmap(
            x=weeknumber_of_dates,
            y=weekdays_in_year,
            z=data,
            text=text,
            hoverinfo='text',
            xgap=3, # this
            ygap=3, # and this is used to make the grid-like apperance
            showscale=False,
            colorscale=colorscale
        )
    ]
    
        
    if month_lines:
        kwargs = dict(
            mode='lines',
            line=dict(
                color='#9e9e9e',
                width=1,
            ),
            hoverinfo='skip',
        )
        
        for date, dow, wkn in zip(
            dates_in_year, weekdays_in_year, weeknumber_of_dates
        ):
            if date.day == 1:
                data += [
                    go.Scatter(
                        x=[wkn-.5, wkn-.5],
                        y=[dow-.5, 6.5],
                        **kwargs,
                    )
                ]
                if dow:
                    data += [
                    go.Scatter(
                        x=[wkn-.5, wkn+.5],
                        y=[dow-.5, dow - .5],
                        **kwargs,
                    ),
                    go.Scatter(
                        x=[wkn+.5, wkn+.5],
                        y=[dow-.5, -.5],
                        **kwargs,
                    )
                ]
                    
                    
    layout = go.Layout(
        title='activity chart',
        height=250,
        yaxis=dict(
            showline=False, showgrid=False, zeroline=False,
            tickmode='array',
            ticktext=['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun'],
            tickvals=[0, 1, 2, 3, 4, 5, 6],
            autorange="reversed",
        ),
        xaxis=dict(
            showline=False, showgrid=False, zeroline=False,
            tickmode='array',
            ticktext=month_names,
            tickvals=month_positions,
        ),
        font={'size':10, 'color':'#9e9e9e'},
        plot_bgcolor=('#fff'),
        margin = dict(t=40),
        showlegend=False,
    )

    if fig is None:
        fig = go.Figure(data=data, layout=layout)
    else:
        fig.add_traces(data, rows=[(row+1)]*len(data), cols=[1]*len(data))
        fig.update_layout(layout)
        fig.update_xaxes(layout['xaxis'])
        fig.update_yaxes(layout['yaxis'])

    
    return fig


def display_years(z, years):
    
    day_counter = 0
    
    fig = make_subplots(rows=len(years), cols=1, subplot_titles=years)
    for i, year in enumerate(years):
        d1 = datetime.date(year, 1, 1)
        d2 = datetime.date(year, 12, 31)
        
        number_of_days = (d2-d1).days + 1
        data = z[day_counter : day_counter + number_of_days]
        
        display_year(data, year=year, fig=fig, row=i)
        fig.update_layout(height=250*len(years))
        day_counter += number_of_days
    return fig

    
z = np.random.randint(2, size=(1200,))

display_years(z, (2020, 2021, 2022))

A great approach in my opinion, too. Thank you!

In my dash app under construction, however, I'd need this as a dash component with some configuration options.

1. Display horizontally or vertically,
2. In addition to month names on one side I'll need week numbers according to the preferred standard as given e.g. by epiweeks,
3. Include marked holidays from different selected holiday calendars (e.g. bank holidays or national holidays for different countries),
4. ... ?

Currently, it's not a priority for me, though.
Now I'll rather open Issue #16: Extension to calendar for picking dates instead