From f7f28616827e81e936f2e7f09ca7908bc96752c8 Mon Sep 17 00:00:00 2001 From: Felix Blanke Date: Sun, 27 Aug 2023 16:18:40 +0200 Subject: [PATCH] Add bar plot to page --- wsgi.py | 76 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 76 insertions(+) diff --git a/wsgi.py b/wsgi.py index 69acd62..efbeb09 100644 --- a/wsgi.py +++ b/wsgi.py @@ -1,9 +1,17 @@ import datetime +from pathlib import Path +import io +import base64 + import pandas as pd from flask import Flask, render_template, request from flask_caching import Cache +from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas +import matplotlib.pyplot as plt +import matplotlib.ticker as mtick + from download_digital import construct_dataframe, get_bez_data config = { @@ -34,6 +42,69 @@ def get_tables(url: str) -> tuple[pd.DataFrame, pd.DataFrame]: return df, df_state +def plot(current_df: pd.DataFrame | None = None, data_folder: str = "data", sheet_name: str = "digital", total_target: int = 1500, plot_all: bool = False) -> str: + data_dict = {} + for f in sorted(Path(data_folder).iterdir()): + with f.open("rb") as ff: + df = pd.read_excel(ff, sheet_name=sheet_name) + df = df.astype({"Digitale Befragung": "Int32"}) + sum_val = df[["Digitale Befragung"]].sum().iloc[0] + key = f.name[:10] + if plot_all or not (int(key[-2:]) - 15) % 7: + data_dict[key] = sum_val + + data_dict["2023-08-15"] = 275 + if not plot_all and current_df is not None: + current_df = current_df.astype({"Digitale Befragung": "Int32"}) + sum_val = current_df[["Digitale Befragung"]].sum().iloc[0] + data_dict["jetzt"] = sum_val + + if plot_all: + for day in range(16, 19): + data_dict[f"2023-08-{day}"] = 0 + for day in range(25, 27): + data_dict[f"2023-08-{day}"] = 0 + + sorted_data_dict = { + k: v + for k, v in sorted(data_dict.items(), key=lambda x: x[0]) + } + + plt.figure(figsize=(6, 5), dpi=300) + + plt.bar(sorted_data_dict.keys(), sorted_data_dict.values(), color="#e4004e") + plt.title("Entwicklung Digitale Beschäftigtenbefragung") + + plt.ylabel("# Teilnahmen") + + def val_to_perc(val): + return 100 * val / total_target + + def perc_to_val(perc): + return perc * total_target / 100 + + sec_ax = plt.gca().secondary_yaxis("right", functions=(val_to_perc, perc_to_val)) + sec_ax.set_ylabel("# Teilnahmen [% Erfolg]") + sec_ax.yaxis.set_major_formatter(mtick.PercentFormatter()) + + plt.axhline(y=total_target, color="#48a9be", linestyle="--") + # plt.axhline(y=federal_target_sheets[1], color="#48a9be", linestyle="--") + # plt.axhline(y=federal_target_sheets[2], color="#48a9be", linestyle="--") + + # tikzplotlib.save("plot.tikz", axis_width="\\linewidth") + plt.tight_layout() + + # Convert plot to PNG image + pngImage = io.BytesIO() + FigureCanvas(plt.gcf()).print_png(pngImage) + + # Encode PNG image to base64 string + pngImageB64String = "data:image/png;base64," + pngImageB64String += base64.b64encode(pngImage.getvalue()).decode('utf8') + + return pngImageB64String + + @app.route("/") @cache.cached(timeout=50) def tables( @@ -81,10 +152,15 @@ def tables( _print_as_html(df_state) _print_as_html(df) + + image = plot(df_state) + + return render_template( "base.html", tables="\n".join(output_str), timestamp=datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"), + image=image, )