solv

solution.py

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+import pandas as pd
+from sqlalchemy import create_engine
+
+
+# Create connection to Sakila database
+def get_engine():
+
+    username = "root"
+    password = "YOUR_PASSWORD"
+    host = "localhost"
+    database = "sakila"
+
+    engine = create_engine(
+        f"mysql+pymysql://{username}:{password}@{host}/{database}"
+    )
+
+    return engine
+
+
+
+# ---------------------------------------------------
+# Function 1:
+# Get rentals for a specific month and year
+# ---------------------------------------------------
+
+def rentals_month(engine, month, year):
+
+    query = f"""
+    SELECT *
+    FROM rental
+    WHERE MONTH(rental_date) = {month}
+    AND YEAR(rental_date) = {year};
+    """
+
+    rentals = pd.read_sql(query, engine)
+
+    return rentals
+
+
+
+# ---------------------------------------------------
+# Function 2:
+# Count rentals per customer
+# ---------------------------------------------------
+
+def rental_count_month(rentals_df, month, year):
+
+    rental_count = (
+        rentals_df
+        .groupby("customer_id")
+        .size()
+        .reset_index(
+            name=f"rentals_{month:02d}_{year}"
+        )
+    )
+
+    return rental_count
+
+
+
+# ---------------------------------------------------
+# Function 3:
+# Compare two months
+# ---------------------------------------------------
+
+def compare_rentals(df1, df2):
+
+    comparison = pd.merge(
+        df1,
+        df2,
+        on="customer_id",
+        how="outer"
+    )
+
+    comparison = comparison.fillna(0)
+
+
+    first_column = df1.columns[1]
+    second_column = df2.columns[1]
+
+
+    comparison["difference"] = (
+        comparison[first_column] -
+        comparison[second_column]
+    )
+
+
+    return comparison
+
+
+
+# ---------------------------------------------------
+# Run the exercise
+# ---------------------------------------------------
+
+if __name__ == "__main__":
+
+    engine = get_engine()
+
+
+    # May 2005
+    may_rentals = rentals_month(
+        engine,
+        5,
+        2005
+    )
+
+    may_customer_rentals = rental_count_month(
+        may_rentals,
+        5,
+        2005
+    )
+
+
+    print("\nMay 2005")
+    print(may_customer_rentals.head())
+
+
+
+    # June 2005
+    june_rentals = rentals_month(
+        engine,
+        6,
+        2005
+    )
+
+
+    june_customer_rentals = rental_count_month(
+        june_rentals,
+        6,
+        2005
+    )
+
+
+    print("\nJune 2005")
+    print(june_customer_rentals.head())
+
+
+
+    # Compare May vs June
+    result = compare_rentals(
+        may_customer_rentals,
+        june_customer_rentals
+    )
+
+
+    print("\nComparison")
+    print(result.head())
+    password = "YOUR_PASSWORD"
+    python solution.py

solution.sql

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+import pandas as pd
+from sqlalchemy import create_engine
+
+
+# Create connection to Sakila database
+def get_engine():
+
+    username = "root"
+    password = "YOUR_PASSWORD"
+    host = "localhost"
+    database = "sakila"
+
+    engine = create_engine(
+        f"mysql+pymysql://{username}:{password}@{host}/{database}"
+    )
+
+    return engine
+
+
+
+# ---------------------------------------------------
+# Function 1:
+# Get rentals for a specific month and year
+# ---------------------------------------------------
+
+def rentals_month(engine, month, year):
+
+    query = f"""
+    SELECT *
+    FROM rental
+    WHERE MONTH(rental_date) = {month}
+    AND YEAR(rental_date) = {year};
+    """
+
+    rentals = pd.read_sql(query, engine)
+
+    return rentals
+
+
+
+# ---------------------------------------------------
+# Function 2:
+# Count rentals per customer
+# ---------------------------------------------------
+
+def rental_count_month(rentals_df, month, year):
+
+    rental_count = (
+        rentals_df
+        .groupby("customer_id")
+        .size()
+        .reset_index(
+            name=f"rentals_{month:02d}_{year}"
+        )
+    )
+
+    return rental_count
+
+
+
+# ---------------------------------------------------
+# Function 3:
+# Compare two months
+# ---------------------------------------------------
+
+def compare_rentals(df1, df2):
+
+    comparison = pd.merge(
+        df1,
+        df2,
+        on="customer_id",
+        how="outer"
+    )
+
+    comparison = comparison.fillna(0)
+
+
+    first_column = df1.columns[1]
+    second_column = df2.columns[1]
+
+
+    comparison["difference"] = (
+        comparison[first_column] -
+        comparison[second_column]
+    )
+
+
+    return comparison
+
+
+
+# ---------------------------------------------------
+# Run the exercise
+# ---------------------------------------------------
+
+if __name__ == "__main__":
+
+    engine = get_engine()
+
+
+    # May 2005
+    may_rentals = rentals_month(
+        engine,
+        5,
+        2005
+    )
+
+    may_customer_rentals = rental_count_month(
+        may_rentals,
+        5,
+        2005
+    )
+
+
+    print("\nMay 2005")
+    print(may_customer_rentals.head())
+
+
+
+    # June 2005
+    june_rentals = rentals_month(
+        engine,
+        6,
+        2005
+    )
+
+
+    june_customer_rentals = rental_count_month(
+        june_rentals,
+        6,
+        2005
+    )
+
+
+    print("\nJune 2005")
+    print(june_customer_rentals.head())
+
+
+
+    # Compare May vs June
+    result = compare_rentals(
+        may_customer_rentals,
+        june_customer_rentals
+    )
+
+
+    print("\nComparison")
+    print(result.head())
+    password = "YOUR_PASSWORD"
+    python solution.py