These scripts download the data from the Lahman’s Baseball Database and format it as a mirador project.
The scripts have the following dependencies:
- Python 2.7.3+ (not tested with 3+) and the following package:
1) Download and extract the zip files, indicating the release year and url (since it is not the same across years):
python download.py 2013 http://seanlahman.com/files/database/lahman-csv_2014-02-14.zip2) Update the table files to indicate the variables to be included in the aggregated dataset. These files can be constructed from the corresponding sections in the readme file included alongside the data files in the original package, for example
2.1 MASTER table
playerID A unique code asssigned to each player. The playerID links
the data in this file with records in the other files.
birthYear Year player was born
birthMonth Month player was born
birthDay Day player was born
birthCountry Country where player was born
birthState State where player was born
birthCity City where player was born
deathYear Year player died
deathMonth Month player died
deathDay Day player died
deathCountry Country where player died
deathState State where player died
deathCity City where player died
nameFirst Player's first name
nameLast Player's last name
nameGiven Player's given name (typically first and middle)
weight Player's weight in pounds
height Player's height in inches
bats Player's batting hand (left, right, or both)
throws Player's throwing hand (left or right)
debut Date that player made first major league appearance
finalGame Date that player made first major league appearance (blank if still active)
retroID ID used by retrosheet
bbrefID ID used by Baseball Reference website
First, the space between the variable name and description should be replaced by a tab, and the descriptions made into a single line if needed. Then, the variables that should be included into the mirador dataset are selected by adding a data type as a third column, resulting in something like follows:
playerID A unique code asssigned to each player. The playerID links the data in this file with records in the other files.
birthYear Year player was born int
birthMonth Month player was born int
birthDay Day player was born int
birthCountry Country where player was born category
birthState State where player was born category
birthCity City where player was born category
deathYear Year player died
deathMonth Month player died
deathDay Day player died
deathCountry Country where player died
deathState State where player died
deathCity City where player died
nameFirst Player's first name
nameLast Player's last name
nameGiven Player's given name (typically first and middle)
weight Player's weight in pounds int
height Player's height in inches int
bats Player's batting hand (left, right, or both) category
throws Player's throwing hand (left or right) category
debut Date that player made first major league appearance
finalGame Date that player made first major league appearance (blank if still active)
retroID ID used by retrosheet
bbrefID ID used by Baseball Reference website
3) The script uses yearly Consumer Price Index (CPI) values to normalize the player salaries to constant dollars. The CPI values are provided in the file cpi.tsv up to 2014 (taken from here). Edit this file to add new values.
4) Run the makedataset.py script, indicating the release year:
python makedataset.py 2013The resulting Mirador dataset will be saved in the mirador folder.