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35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
from bokeh import models as bm, plotting as bp
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from bokeh.transform import factor_cmap
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from pandas import DataFrame
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from data_utils import get_categorical_stats
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gender_colormap = factor_cmap("Sukupuoli", ["#4834d4", "#eb4d4b"], ["mies", "nainen"])
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def get_df_hover_tool(df: DataFrame):
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return bm.HoverTool(tooltips=[(c, f"@{{{c}}}") for c in df.columns])
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def set_yaxis_cash(plot):
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plot.yaxis.axis_label = "Vuositulot"
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plot.yaxis[0].formatter = bm.NumeralTickFormatter(format="€0")
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def get_categorical_stats_plot(df, *, category):
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df = get_categorical_stats(df, category, "Vuositulot")
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df.reset_index(inplace=True)
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df[category] = df[category].astype("category")
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plot = bp.figure(
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title=f"{category}/tulot", x_range=list(df[category].cat.categories)
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)
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set_yaxis_cash(plot)
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plot.vbar(df[category], 0.4, df["max"], df["min"], color="#a4b0be")
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plot.line(
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df[category], df["median"], legend_label="median", color="#1289A7", line_width=4
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)
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plot.line(
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df[category], df["mean"], legend_label="mean", color="#B53471", line_width=4
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)
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return plot
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