BlablaChallenge

submissions/Souka21/solution.py

@@ -0,0 +1,60 @@
+import pandas as pd
+
+MAX_PRICE = 100.00
+NUM_CHEAPEST_PRODUCTS = 5
+
+def process_city_data(filename):
+    """Process the input CSV file to extract city data.
+    Args:
+        filename (str): The name of the input CSV file.
+    Returns:
+        pd.DataFrame: A DataFrame containing city data.
+    """
+    df = pd.read_csv(filename, header=None, names=['City', 'Product', 'Price'])
+    df['Price'] = df['Price'].astype(float)
+    return df
+
+def find_cheapest_city(df):
+    """Find the city with the lowest total price.
+    Args:
+        df (pd.DataFrame): DataFrame containing city data.
+    Returns:
+        pd.Series: Series representing the City object with the lowest total price.
+    """
+    return df.groupby('City')['Price'].sum().idxmin()
+
+def find_cheapest_products(df, min_city):
+    """Find the cheapest products in a given city.
+    Args:
+        df (pd.DataFrame): DataFrame containing city data.
+        min_city (str): Name of the city.
+    Returns:
+        pd.DataFrame: DataFrame containing the cheapest products in the given city.
+    """
+    city_df = df[df['City'] == min_city]
+    return city_df.nsmallest(NUM_CHEAPEST_PRODUCTS, 'Price')[['Product', 'Price']]
+
+def write_output(filename, min_city, min_products):
+    """Write the output to a file.
+    Args:
+        filename (str): The name of the output file.
+        min_city (str): Name of the city with the lowest total price.
+        min_products (pd.DataFrame): DataFrame containing the cheapest products.
+    """
+    with open(filename, 'w') as file:
+        file.write(f"{min_city} {min_products['Price'].sum():.2f}\n")
+        for _, row in min_products.iterrows():
+            file.write(f"{row['Product']} {row['Price']:.2f}\n")
+
+def main():
+    """Main function to execute the program."""
+    input_filename = 'input.txt'
+    output_filename = 'output.txt'
+
+    df = process_city_data(input_filename)
+    min_city = find_cheapest_city(df)
+    min_products = find_cheapest_products(df, min_city)
+    write_output(output_filename, min_city, min_products)
+
+if __name__ == "__main__":
+    main()