portfoliodash_6.py

df = plotlydf_portfval[['date', 'ptf_growth', 'sp500_growth']].copy().round(3)
df['month'] = df.date.dt.month_name()  # date column should be formatted as datetime
df['weekday'] = df.date.dt.day_name()  # could be interesting to analyze weekday returns later
df['year'] = df.date.dt.year
df['weeknumber'] = df.date.dt.week    # could be interesting to try instead of timeperiod
df['timeperiod'] = df.year.astype(str) + ' - ' + df.date.dt.month.astype(str).str.zfill(2)

# getting the percentage change for each period. the first period will be NaN
sp = df.reset_index().groupby('timeperiod').last()['sp500_growth'].pct_change()*100
ptf = df.reset_index().groupby('timeperiod').last()['ptf_growth'].pct_change()*100
plotlydf_growth_compare = pd.merge(ptf, sp, on='timeperiod').reset_index().round(3)
plotlydf_growth_compare.head()

# Plotly part
fig_growth2 = go.Figure()
fig_growth2.layout.template = CHART_THEME
fig_growth2.add_trace(go.Bar(
    x=plotlydf_growth_compare.timeperiod,
    y=plotlydf_growth_compare.ptf_growth.round(2),
    name='Portfolio'
))
fig_growth2.add_trace(go.Bar(
    x=plotlydf_growth_compare.timeperiod,
    y=plotlydf_growth_compare.sp500_growth.round(2),
    name='S&P 500',
))
fig_growth2.update_layout(barmode='group')
fig_growth2.layout.height=300
fig_growth2.update_layout(margin = dict(t=50, b=50, l=25, r=25))
fig_growth2.update_layout(
    xaxis_tickfont_size=12,
    yaxis=dict(
        title='% change',
        titlefont_size=13,
        tickfont_size=12,
        ))

fig_growth2.update_layout(legend=dict(
    yanchor="top",
    y=0.99,
    xanchor="right",
    x=0.99))
fig_growth2.show()