Format

download_digital.py

@@ -71,6 +71,24 @@ bundesland_dict = {
 }
 
 
+landesbezirk_dict = {
+    "100": "Nord",
+    "200": "Niedersachsen-Bremen",
+    "300": "Berlin-Brandenburg",
+    "400": "Nordrhein-Westfalen",
+    "500": "Rheinland-Pfalz-Saarland",
+    "600": "Hessen",
+    "700": "Sachsen, Sachsen-Anhalt, Thüringen",
+    "800": "Bayern",
+    "900": "Baden-Württemberg",
+    "1000": "Hamburg",
+}
+
+
+def get_landesbezirk(id: str):
+    return landesbezirk_dict[str((int(id) // 100) * 100)]
+
+
 def get_bez_data(
     tags: list[str], url: str = "https://beschaeftigtenbefragung.verdi.de/"
 ) -> list[dict]:
@@ -90,22 +108,22 @@ def get_bez_data(
 
 def construct_dataframe(
     bez_data: dict[str, dict],
-    grouped: bool = False,
     special_tag: str | None = None,
-    no_processing: bool = False,
 ):
     data = {}
-    if not no_processing:
+
+    first_key = next(iter(bez_data.keys()))
+    if first_key in landesbezirk_dict:
+        data["Landesbezirk"] = pd.Series(
+            [v["name"] for v in bez_data.values()], index=list(bez_data.keys())
+        )
+    else:
         data["Bundesland"] = pd.Series(
             [bundesland_dict[k] for k in bez_data], index=list(bez_data.keys())
         )
         data["Bezirk"] = pd.Series(
             [v["name"] for v in bez_data.values()], index=list(bez_data.keys())
         )
-    else:
-        data["Landesbezirk"] = pd.Series(
-            [v["name"] for v in bez_data.values()], index=list(bez_data.keys())
-        )
 
     tot_col_data = []
     tot_col_index = []
@@ -121,15 +139,7 @@ def construct_dataframe(
                 tot_col_index.append(k)
 
     data["Digitale Befragung"] = pd.Series(tot_col_data, index=tot_col_index)
-    df = pd.DataFrame(data=data)
-    df = df.astype({"Digitale Befragung": "Int32"})
-
-    if grouped and no_processing:
-        raise ValueError
-    elif grouped:
-        df = df.groupby("Bundesland", as_index=False)[["Digitale Befragung"]].sum()
-
-    return df
+    return pd.DataFrame(data=data).astype({"Digitale Befragung": "Int32"})
 
 
 def main(
@@ -138,7 +148,6 @@ def main(
     dry_run: bool = False,
     grouped: bool = False,
     special_tag: str | None = None,
-    no_processing: bool = False,
     folder: str = "data",
     name: str = "data",
     sheet_name: str = "digital",
@@ -146,11 +155,12 @@ def main(
     bez_data = get_bez_data([tag], url)[0]
     df = construct_dataframe(
         bez_data=bez_data,
-        grouped=grouped,
         special_tag=special_tag,
-        no_processing=no_processing,
     )
 
+    if grouped:
+        df = df.groupby("Bundesland", as_index=False)[["Digitale Befragung"]].sum()
+
     if dry_run:
         print(df)
     else:

wsgi.py

@@ -1,5 +1,8 @@
 import datetime
 import io
+import locale
+import os
+import time
 from itertools import chain
 from pathlib import Path
 
@@ -11,7 +14,7 @@ import pandas as pd
 from flask import Flask, Markup, render_template, request
 from flask_caching import Cache
 
-from download_digital import construct_dataframe, get_bez_data
+from download_digital import construct_dataframe, get_bez_data, get_landesbezirk
 
 config = {
     "CACHE_TYPE": "FileSystemCache",
@@ -19,7 +22,9 @@ config = {
     "CACHE_THRESHOLD": 50,
     "CACHE_DIR": "cache",
 }
-import locale
+
+os.environ["TZ"] = "Europe/Berlin"
+time.tzset()
 
 locale.setlocale(locale.LC_ALL, "de_DE.UTF-8")
 app = Flask(__name__)
@@ -30,28 +35,18 @@ cache = Cache(app)
 def get_tables(url: str) -> tuple[pd.DataFrame, pd.DataFrame]:
     bez_data = get_bez_data(["bez_data_0", "bez_data_2"], url)
 
-    df = construct_dataframe(
-        bez_data=bez_data[0],
-        grouped=False,
-        special_tag="stud",
-    )
-
-    df_state = construct_dataframe(
-        bez_data=bez_data[1], grouped=False, no_processing=True
-    )
+    df = construct_dataframe(bez_data=bez_data[0], special_tag="stud")
+    df_state = construct_dataframe(bez_data=bez_data[1])
 
     return df, df_state
 
 
-def plot(
-    current_df: pd.DataFrame | None = None,
-    data_folder: str = "data",
-    sheet_name: str = "digital",
-    total_target: int = 1500,
-    alpha: float | None = None,
-) -> str:
-    curr_datetime = datetime.datetime.now()
-
+def create_plot_df(
+    current_df: pd.DataFrame | None,
+    data_folder: str,
+    sheet_name: str,
+    curr_datetime,
+) -> pd.DataFrame:
     data_dict = {}
 
     ## Important: If multiple results are stored for the same date
@@ -61,31 +56,55 @@ def plot(
 
     for f in sorted(Path(data_folder).iterdir()):
         with f.open("rb") as ff:
-            df = pd.read_excel(ff, sheet_name=sheet_name)
+            df = pd.read_excel(ff, sheet_name=sheet_name, index_col=0)
+
+        if "Landesbezirk" not in df.columns:
+            df["Landesbezirk"] = df.index.map(get_landesbezirk)
+
         df = df.astype({"Digitale Befragung": "Int32"})
-        sum_val = df[["Digitale Befragung"]].sum().iloc[0]
+        df = df.groupby("Landesbezirk")[["Digitale Befragung"]].sum()
+
         key = f.name[:10]
-        data_dict[key] = sum_val
+        data_dict[key] = df["Digitale Befragung"]
 
-    data_dict["2023-08-15"] = 275
+    df = pd.DataFrame(data=data_dict).T
 
-    series = pd.Series(data_dict.values(), index=data_dict)
-    series.index = series.index.astype("datetime64[ns]") + pd.DateOffset(hours=10)
+    df.index = df.index.astype("datetime64[ns]") + pd.DateOffset(hours=10)
 
-    df = series.to_frame("Digitale Befragung")
     df = df.reindex(
-        pd.date_range(start="2023-08-15", end=curr_datetime)
-        + pd.DateOffset(hours=10)
+        pd.date_range(start="2023-08-15", end=curr_datetime) + pd.DateOffset(hours=10)
     )
 
     if current_df is not None:
+        if "Landesbezirk" not in current_df.columns:
+            current_df["Landesbezirk"] = current_df.index.map(get_landesbezirk)
         current_df = current_df.astype({"Digitale Befragung": "Int32"})
-        sum_val = current_df[["Digitale Befragung"]].sum().iloc[0]
-        df.loc[curr_datetime] = sum_val
+        current_df = current_df.groupby("Landesbezirk")[["Digitale Befragung"]].sum()
+
+        df.loc[curr_datetime] = current_df["Digitale Befragung"]
 
         if pd.isna(df.loc[df.index.max()][0]):
             df = df.drop([df.index.max()])
 
+    return df
+
+
+def plot(
+    current_df: pd.DataFrame | None = None,
+    data_folder: str = "data",
+    sheet_name: str = "digital",
+    total_targets: tuple[int, ...] = (1500,),
+    alpha: float | None = None,
+    landesbez_str: str | None = None,
+) -> str:
+    curr_datetime = datetime.datetime.now()
+    df = create_plot_df(
+        current_df=current_df,
+        data_folder=data_folder,
+        sheet_name=sheet_name,
+        curr_datetime=curr_datetime,
+    )
+
     fig = plt.figure(dpi=300)
 
     # fill weekends
@@ -95,39 +114,51 @@ def plot(
         if day.weekday() >= 5:
             plt.gca().axvspan(days[idx], days[idx + 1], alpha=0.2, color="gray")
 
+    series = df.sum(axis=1) if landesbez_str is None else df[landesbez_str]
+    plot_df = series.to_frame("Digitale Befragung").replace(0, np.nan)
+    plot_df = plot_df.astype({"Digitale Befragung": "float32"})
+    if not pd.isna(plot_df).all().item():
         if alpha is not None:
             plt.fill_between(
-            df.dropna().index,
-            df.dropna()["Digitale Befragung"],
+                plot_df.dropna().index,
+                plot_df.dropna()["Digitale Befragung"],
                 color="#e4004e",
                 alpha=alpha,
             )
 
         plt.plot(
-        df.dropna().index,
-        df.dropna()["Digitale Befragung"],
+            plot_df.dropna().index,
+            plot_df.dropna()["Digitale Befragung"],
             ls="--",
             marker="o",
             lw=1,
             color="#e4004e",
             markersize=4,
+            label=landesbez_str,
         )
 
         if current_df is not None:
             plt.annotate(
                 "Jetzt",
-            (df.dropna().index[-1], df.dropna()["Digitale Befragung"][-1] * 1.03),
+                (
+                    plot_df.dropna().index[-1],
+                    plot_df.dropna()["Digitale Befragung"][-1] * 1.03,
+                ),
                 fontsize=8,
                 ha="center",
             )
 
-    plt.plot(df.index, df["Digitale Befragung"], lw=1.5, color="#e4004e")
+        plt.plot(
+            plot_df.index,
+            plot_df["Digitale Befragung"],
+            lw=1.5,
+            color="#e4004e",
+            label=landesbez_str,
+        )
 
     plt.title("Teilnahme an Digitaler Beschäftigtenbefragung")
     plt.ylabel("# Teilnahmen")
-    plt.ylim(0, total_target + 100)
-
-    # plt.gcf().autofmt_xdate()
+    plt.ylim(0, total_targets[0] + 100)
 
     # use timezone offset to center tick labels
     plt.gca().xaxis.set_major_locator(
@@ -142,18 +173,24 @@ def plot(
     plt.gca().tick_params("x", length=0, which="major")
 
     def val_to_perc(val):
-        return 100 * val / total_target
+        return 100 * val / total_targets[0]
 
     def perc_to_val(perc):
-        return perc * total_target / 100
+        return perc * total_targets[0] / 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())
 
+    for total_target in total_targets:
         plt.axhline(y=total_target, color="#48a9be", linestyle="--")
+
     plt.tight_layout()
 
+    return fig
+
+
+def convert_fig_to_svg(fig: plt.Figure) -> str:
     # Convert plot to SVG image
     imgdata = io.StringIO()
     fig.savefig(imgdata, format="svg")
@@ -209,23 +246,24 @@ def tables(
 
         df_state = df_state.sort_values("Landesbezirk")
 
-        image = plot(df_state)
+        fig = plot(df_state)
         timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
 
-    except Exception:
+    except Exception as e:
+        print(e)
         last_file = sorted(Path("data").iterdir())[-1]
         key = last_file.name[:10]
 
         with (Path("data") / f"{key}_data.ods").open("rb") as ff:
-            df = pd.read_excel(ff, sheet_name="digital").astype(
+            df = pd.read_excel(ff, sheet_name="digital", index_col=0).astype(
                 {"Digitale Befragung": "Int32"}
             )
         with (Path("data") / f"{key}_state_data.ods").open("rb") as ff:
-            df_state = pd.read_excel(ff, sheet_name="digital").astype(
+            df_state = pd.read_excel(ff, sheet_name="digital", index_col=0).astype(
                 {"Digitale Befragung": "Int32"}
             )
 
-        image = plot()
+        fig = plot()
         timestamp = Markup(f'<font color="red">{key} 10:00:00</font>')
 
     _print_as_html(df_state)
@@ -235,7 +273,7 @@ def tables(
         "base.html",
         tables="\n".join(output_str),
         timestamp=timestamp,
-        image=image,
+        image=convert_fig_to_svg(fig),
     )