src/analysis/__main__.py

@@ -1,13 +0,0 @@
-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

@@ -1,5 +0,0 @@
-import pandas as pd
-
-
-def load_sales(path: str) -> pd.DataFrame:
-    return pd.read_csv(path, sep=",", encoding="utf-8")

src/analysis/metrics.py

@@ -1,6 +0,0 @@
-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

@@ -1,9 +0,0 @@
-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

@@ -1,11 +0,0 @@
-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