Add bar plot to page

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,
     )