spx_yearly_roi_bokeh.py

import yfinance_download

from bokeh.plotting import figure, show
import bokeh.models
import bokeh.palettes
import bokeh.transform

df = yfinance_download.update_records('^GSPC', interval='1d')

# add column that shows the day of the year

df['day_of_year'] = df.index.dayofyear

# df.sort_values('day_of_year')

# add column for first open of the year

df['first_open_of_year'] = df.groupby(df.index.year)['Open'].transform('first')

# df[df.index.year == 2023]

df['year_roi'] = (df['Close'] / df['first_open_of_year'] - 1) * 100

# ----------------------------------------------------------------------

p = figure(title='S&P 500 Yearly ROI', x_axis_label='Day of Year', y_axis_label='%', x_axis_type='linear', sizing_mode='stretch_both')

p.line(x='day_of_year', y='year_roi', source=df[df.index.year == 2020], line_width=2, legend_label='2020', line_color='red')
p.line(x='day_of_year', y='year_roi', source=df[df.index.year == 2021], line_width=2, legend_label='2021', line_color='green')
p.line(x='day_of_year', y='year_roi', source=df[df.index.year == 2022], line_width=2, legend_label='2022', line_color='blue')
p.line(x='day_of_year', y='year_roi', source=df[df.index.year == 2023], line_width=2, legend_label='2023', line_color='orange')

p.xaxis.formatter = bokeh.models.NumeralTickFormatter(format='0')
p.yaxis.formatter = bokeh.models.NumeralTickFormatter(format='0')

p.add_tools(bokeh.models.HoverTool(
    tooltips=[
        ('Day of Year', '@day_of_year'),
        ('%', '@year_roi{0.00}')
    ],
    mode='vline'))

# add legend with toggle

p.legend.location = 'top_left'
p.legend.click_policy = 'hide'

show(p)