Age-Collector/heights_plot.py at main · Velidonimo/Age-Collector · GitHub

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from bokeh.plotting import figure
from bokeh.models import ColumnDataSource, HoverTool
from bokeh.embed import components
from bokeh.resources import CDN
import pandas


def get_unique_heights(df_from_sql):
    """Making a new DataFrame with unique heights and its population"""
    # rounding heights
    df_from_sql["height"] = round(df_from_sql.height, 0)

    new_df = pandas.DataFrame(columns=("Height", "Population"))
    # unique heights
    new_df["Height"] = df_from_sql.height.unique()
    # number of unique heights in database
    new_df.Population = [df_from_sql.loc[df_from_sql.height == height].count()["height"] for height in new_df.Height]
    return new_df


def rounding_heights(real_df):
    """Making a new DataFrame with heights rounded to 5"""
    real_df["Rounded_Height"] = real_df.Height // 5 * 5
    new_heights = list(range(int(real_df.Rounded_Height.min()), int(real_df.Rounded_Height.max()) + 1, 5))
    new_heights_df = pandas.DataFrame(columns=("Height", "Population"))
    new_heights_df.Height = new_heights
    # summing population in each range
    new_heights_df.Population = [real_df.loc[real_df.Rounded_Height == height]["Population"].sum() for height in new_heights]
    return new_heights_df


def hover_tooltip(user_height, stat_height, number):
    """a func to fill the Hover column of Dataframe"""
    hover_string = ""
    if stat_height == user_height:
        if number > 1:
            hover_string = f"Your number is between {number} people!"
        else:
            hover_string = f"You are the only one this big!"
    else:
        if number > 1:
            hover_string = f"{number} people are this big."
        else:
            hover_string = f"1 person is this big."

    return hover_string


def build_plot(df_from_sql, user_height):
    """Build a plot for given DataFrame and user_height"""
    # rebuilding database to Height and Population
    stat_df = get_unique_heights(df_from_sql)

    # rounding heights by 5
    user_height = user_height // 5 * 5
    stat_df = rounding_heights(stat_df)

    # adding a column shifted by 2.5 to show on plot
    stat_df["Shifted_height"] = stat_df.Height + 2.5
    # adding a column for HoverTool
    stat_df["Hover"] = [hover_tooltip(user_height, st_ht, num) for st_ht, num in zip(stat_df.Height, stat_df.Population)]
    stat_cds = ColumnDataSource(stat_df)

    # DataFrame for the users glyph
    users_df = stat_df.loc[stat_df["Height"] == user_height]
    users_cds = ColumnDataSource(users_df)

    height_plot = figure(height=400, width=900, title="Height statistic",
                         x_axis_label="Height, cm", y_axis_label="Population",
                         tools="pan", x_minor_ticks=None, y_minor_ticks=None)
    height_plot.xaxis.ticker.desired_num_ticks = int((stat_df.Height.max() - stat_df.Height.min())/5)
    height_plot.yaxis.ticker.desired_num_ticks = stat_df.Population.max()


    stat_glyph = height_plot.vbar(x="Shifted_height", width=4.5, bottom=0,
                                  top="Population", color="darkorange", source=stat_cds)

    users_glyph = height_plot.vbar(x="Shifted_height", width=4.5, bottom=0,
                                   top="Population", color="darkgreen", source=users_cds)

    your_height_hover = HoverTool(tooltips="@Hover")
    height_plot.add_tools(your_height_hover)

    script, div = components(height_plot)
    cdn_js = CDN.js_files[0]
    cdn_css = CDN.css_files
    if len(cdn_css) > 0:
        cdn_css = cdn_css[0]

    return (script, div, cdn_js, cdn_css)


if __name__ == '__main__':
    df11 = pandas.read_csv("random_heights.csv")
    build_plot(df11, 189)