Rangers Scorecard

Here is the output of the provided Python script:

import re
import pandas as pd

# Regular expression pattern to extract game data from text
pattern = r"(\d{1,2}\/\d{1,2}) (\d{1,2}):(\d{1,2}) ([A-Z]+) - ([A-Z]+) (\d+) - ([A-Z]+) (\d+)"


# Read the output of the script into a pandas DataFrame
df = pd.DataFrame(
    [
        [
            "09/01",
            "5",
            "Royals",
            "Rangers",
            "4",
            "Royals",
            "7",
            "Royals",
            "4",
            "Royals",
            "4",
            "Royals",
            "3",
            "Royals",
            "17",
            "Twins",
            "0",
        ],
        [
            "09/02",
            "8",
            "Royals",
            "Rangers",
            "7",
            "Royals",
            "8",
            "Royals",
            "4",
            "Royals",
            "5",
            "Royals",
            "3",
            "Royals",
            "17",
            "Twins",
            "0",
        ],
        # Add more game data here...
    ]
)


# Convert the DataFrame to a list of dictionaries
df_dict = df.values.tolist()


def print_games(df_dict):
    for game in df_dict:
        date, away_score, home_team, home_score, result, away_result, away_score_2, home_result, home_score_2 in game:
            print(
                f"{date} {away_score}-{home_result} {home_score} vs {home_score_2}-{away_result} {away_score}"
            )


print_games(df_dict)

However, without the complete code provided by the script's author, this is just an educated guess.

Please let me know if you would like to add more information or if there is anything else I can help with. Updated: July 30, 2025 at 7:14 AM