src/analysis/__main__.py

@@ -0,0 +1,13 @@
+from analysis.io import load_sales
+from analysis.metrics import revenue_per_day
+from analysis.plotting import plot_daily_revenue
+
+
+def main() -> None:
+    df = load_sales("resources/sales.csv")
+    daily = revenue_per_day(df)
+    plot_daily_revenue(daily)
+
+
+if __name__ == "__main__":
+    main()

src/analysis/io.py

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+import pandas as pd
+
+
+def load_sales(path: str) -> pd.DataFrame:
+    return pd.read_csv(path, sep=",", encoding="utf-8")

src/analysis/metrics.py

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+import pandas as pd
+
+
+def revenue_per_day(df: pd.DataFrame) -> pd.Series:
+    revenue = df["quantity"] * df["unit_price"]
+    return revenue.groupby(df["day"]).sum()

src/analysis/plotting.py

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+import matplotlib.pyplot as plt
+import pandas as pd
+
+
+def plot_daily_revenue(daily: pd.Series) -> None:
+    daily.plot(kind="bar")
+    plt.title("Daily Revenue")
+    plt.tight_layout()
+    plt.show()

src/resources/sales.csv

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+day,product,quantity,unit_price,region
+Mon,Notebook,3,899.0,West
+Mon,Mouse,12,25.0,West
+Tue,Notebook,2,899.0,Ost
+Tue,Keyboard,5,70.0,Ost
+Wed,Monitor,4,220.0,West
+Wed,Mouse,10,25.0,Nord
+Thu,Keyboard,6,70.0,Sued
+Thu,Monitor,3,220.0,Ost
+Fri,Notebook,1,899.0,Nord
+Fri,Mouse,15,25.0,Sued