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standardized axes; clarified the initally_hide_divs_other_than_the_first
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doc/python/dropdowns.md

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@@ -470,9 +470,12 @@ for continent in df['continent'].unique():
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fig_dict[continent] = px.scatter(continent_data, x='gdpPercap', y='lifeExp',
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title=f'GDP vs Life Expectancy for {continent}',
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labels={'gdpPercap': 'GDP per Capita (USD)', 'lifeExp': 'Life Expectancy (Years)'},
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hover_name='country',
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hover_name='country',size="pop", size_max=55
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)
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#Standardizing the axes would make the graphs easier to compare
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#Standardizing the axes makes the graphs easier to compare
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fig_dict[continent].update_xaxes(range=[0,50000])
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fig_dict[continent].update_yaxes(range=[25,90])
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# Create a dictionary, data_for_jinja with two entries:
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# the value for the "dropdown_entries" key is a string containing a series of <option> tags, one tag for each item in the drop down
@@ -485,7 +488,8 @@ for n, figname in enumerate(fig_dict.keys()):
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data_for_jinja["dropdown_entries"]+=f"<option value='{figname}'>{fig_dict[figname].layout.title.text}</option>"
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#YOU MAY NEED TO UPDATE THE LINK TO THE LATEST PLOTLY.JS
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fig_html = fig_dict[figname].to_html(full_html=False, config=dict(responsive=False, scrollZoom=False, doubleClick=False), include_plotlyjs = "https://cdn.plot.ly/plotly-2.35.2.min.js")
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data_for_jinja["divs"]+=f'<div id="{figname}" class="content-div" {"style=""display:none;"""*(n>0)}>{fig_html}{text_dict[figname]}</div>'
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initially_hide_divs_other_than_the_first = "style=""display:none;"""*(n>0)
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data_for_jinja["divs"]+=f'<div id="{figname}" class="content-div" {initially_hide_divs_other_than_the_first}>{fig_html}{text_dict[figname]}</div>'
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# Insert data into the template and write the file to disk
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# YOU WILL LIKELY NEED TO CUSTOMIZE THESE PATHS

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