Periodic Table Heatmap widget for Python and Jupyter notebooks using Bokeh and Pandas

periodic_table_plot.py

def periodic_table_plot(df, title="", element_column_name="element", value_column_name=None, colors="#ddd"):
    '''
    Create an interactive periodic table with heatmap. 

    Parameters:

    df                   Pandas Dataframe with relevant data. Has to have at least two columns with element 
                         symbols (e.g., Fe, Ir, H, ...) and a second column with values to display as heat map
    title                A descriptive string shown as title with the periodic table
    element_column_name  A string containing the name of the column with the element symbols in the df dataframe
    value_column_name    A string containing the name of the column with the heat map values in the df dataframe
    colors               A string or bokeh.palette as colormap to use as heatmap in the periodic table
    
    Usage:
    
    import pandas as pd
    from bokeh.plotting import show
    from bokeh.transform import linear_cmap
    from bokeh.bokeh.palettes import Spectral6
    
    voltages = pd.DataFrame([{"metal": "V", "voltage": 1.0},{"metal": "Ni", "voltage": 3.2}]) 
    pt = periodic_table_plot(voltages, title="Intercalation voltages", element_column_name="metal", value_column_name="voltage", colors=linear_cmap(field_name='voltage', palette=Spectral6, low=0.0, high=2.5))
    show(pt)
    '''
    
    from bokeh.plotting import figure
    from bokeh.sampledata.periodic_table import elements
    from bokeh.transform import dodge

    periods = ["I", "II", "III", "IV", "V", "VI", "VII"]
    groups = [str(x) for x in range(1, 19)]
    
    df = pd.merge(df,elements[['symbol','atomic number','name','group','period']], left_on=element_column_name, right_on='symbol')
    df["period"] = [periods[x-1] for x in df.period]

    df_missing = elements[~elements['symbol'].isin(df[element_column_name])][['symbol','atomic number','name','group','period']]
    df_missing["period"] = [periods[x-1] for x in df_missing.period]
    
    TOOLTIPS = [
        ("Name", "@name"),
        ("Atomic number", "@{atomic number}")
    ]

    if value_column_name:
        TOOLTIPS.append((value_column_name, f"@{{{value_column_name}}}"))
    
    p = figure(title=f"Periodic Table ({title})", width=1000, height=450,
               x_range=groups, y_range=list(reversed(periods)),
               tools="hover", toolbar_location=None, tooltips=TOOLTIPS)

    r = p.rect("group", "period", 0.95, 0.95, source=df, fill_alpha=0.6,
               color=colors)

    rm = p.rect("group", "period", 0.95, 0.95, source=df_missing, fill_alpha=0.6,
           color="#eee")


    # Print elements with values
    
    text_props = dict(source=df, text_align="left", text_baseline="middle")
    
    x = dodge("group", -0.4, range=p.x_range)
    
    p.text(x=x, y="period", text="symbol", text_font_style="bold", **text_props)
    
    p.text(x=x, y=dodge("period", 0.3, range=p.y_range), text="atomic number",
           text_font_size="11px", **text_props)
    
    p.text(x=x, y=dodge("period", -0.35, range=p.y_range), text="name",
           text_font_size="7px", **text_props)

    # # Print elements without values 
    
    text_props = dict(source=df_missing, text_align="left", text_baseline="middle", color="#aaa")
    
    p.text(x=x, y="period", text="symbol", text_font_style="bold", **text_props)
    
    p.text(x=x, y=dodge("period", 0.3, range=p.y_range), text="atomic number",
           text_font_size="11px", **text_props)
    
    p.text(x=x, y=dodge("period", -0.35, range=p.y_range), text="name",
           text_font_size="7px", **text_props)

    
    p.outline_line_color = None
    p.grid.grid_line_color = None
    p.axis.axis_line_color = None
    p.axis.major_tick_line_color = None
    p.axis.major_label_standoff = 0
    p.hover.renderers = [r] # only hover element boxes
    
    return p