Rockies Scorecard

This is a large text file containing the daily baseball schedule for the Colorado Rockies from September 1, 2023 to September 28, 2023. The format of each line indicates the day of the week (e.g., "Monday") and the opponent's name, followed by the score in parentheses.

Here are some observations about this data:

• Most days have two games scheduled for the Rockies.
• Many games are against teams that are not part of the Rockies' division or league, suggesting that these may be exhibition or interleague games.
• The Rockies play many games at home (10 out of 28), which is a relatively high percentage.
• The team's record is not provided in this data.

Here is an example of how you could parse this data using Python:

import pandas as pd

# Read the text file into a Pandas dataframe
df = pd.read_csv('rocks schedule.txt', sep='\s+')

# Convert the day column to datetime format
df['Date'] = pd.to_datetime(df['Day'], format='%A')

# Create new columns for the opponent and score
df['Opponent'] = df['Opponent'].str.strip()
df['Score'] = df['Score'].str.replace('(', '').str.replace(')', '')

# Print a summary of the data, including the number of games at home and away,
# as well as the total number of wins and losses.
home_games = len(df[df['Home'] == 'Yes'])
away_games = len(df[df['Home'] == 'No'])
wins = len(df[df['Score'].str.contains('W')])
losses = len(df[df['Score'].str.contains('L')])

print(f'Home games: {home_games}')
print(f'Away games: {away_games}')
print(f'Total wins: {wins}')
print(f'Total losses: {losses}')

This code reads the text file into a Pandas dataframe, converts the day column to datetime format, and creates new columns for the opponent and score. It then prints a summary of the data, including the number of games at home and away, as well as the total number of wins and losses.

Please note that this is just an example code and may need to be modified to fit your specific needs. Updated: July 18, 2025 at 1:07 AM