Access WRDS data through PostgreSQL in Python.
Project description
WRDS-Py from Wharton Research Data Services
WRDS-Py is a Python package for examining datasets on the Wharton Research Data Services (WRDS) platform, and extracting data to Pandas dataframes. A WRDS account is required.
Installation
The WRDS-Py package requires Python 3.8 or newer. To ensure you have a supported Python version, type python --version
at a command line interface, and check that it is greater than 3.8. On some systems, Python may be in installed as python3
. You can download Python here if it isn't installed.
The WRDS-Py package must be installed before it can be used for the first time. The recommended method is to use a virtual environment (venv
), so you can import
it to use in Python. This example will install the WRDS-Py package (wrds
) and IPython, which provides a much nicer command line interface than is included with Python.
Linux or MacOS
$ python -m venv --copies --prompt wrds-py wrds-py
$ source wrds-py/bin/activate
(wrds-py) $ python -m pip install -U pip wheel wrds ipython
In this example, Python will create a venv
in your current directory ./wrds-py
, so that when you want to use it again, you can simply activate it:
$ source wrds-py/bin/activate
Windows
C:\Users\username> python -m venv --copies --prompt wrds-py wrds-py
C:\Users\username> wrds-py\Scripts\activate
(wrds-py) C:\Users\username> python -m pip install -U pip wheel wrds ipython
In this example, Python will create a venv
in the directory C:\Users\username\wrds-py
, so that when you want to use it again, you can simply activate it:
C:\Users\username> wrds-py\Scripts\activate
For detailed information on installation of the module, please see PYTHON: From Your Computer (Jupyter/Spyder)
Using the Py-WRDS Package
Type ipython
to start the IPython command line interface.
For detailed information on use of the module, please see Querying WRDS Data using Python
A quick tutorial:
In [1]: import wrds
In [2]: db = wrds.Connection()
Enter your credentials.
Username: <your_username>
Password: <your_password>
In [3]: db.list_libraries()
['audit', 'bank', 'block', 'bvd', 'bvdtrial', 'cboe', ...]
In [4]: db.list_tables(library="crsp")
['aco_amda', 'aco_imda', 'aco_indfnta', 'aco_indfntq', ...]
In [5]: db.describe_table(library="crsp", table="stocknames")
Approximately 58957 rows in crsp.stocknames.
name nullable type
0 permno True DOUBLE PRECISION
1 namedt True DATE
2 nameenddt True DATE
...
In [6]: stocknames = db.get_table(library="crsp", table="stocknames", rows=10)
In [7]: stocknames.head()
permno permco namedt nameenddt cusip ncusip ticker \
0 10000.0 7952.0 1986-01-07 1987-06-11 68391610 68391610 OMFGA
1 10001.0 7953.0 1986-01-09 1993-11-21 36720410 39040610 GFGC
2 10001.0 7953.0 1993-11-22 2008-02-04 36720410 29274A10 EWST
3 10001.0 7953.0 2008-02-05 2009-08-03 36720410 29274A20 EWST
4 10001.0 7953.0 2009-08-04 2009-12-17 36720410 29269V10 EGAS
In [7]: db.close() # Close the connection to the database.
In [8]: with wrds.Connection() as db: # You can use a context manager
...: stocknames = db.get_table(library='crsp', table='stocknames', rows=10)
...: stocknames.head()
permno permco namedt nameenddt cusip ncusip ticker \
0 10000.0 7952.0 1986-01-07 1987-06-11 68391610 68391610 OMFGA
1 10001.0 7953.0 1986-01-09 1993-11-21 36720410 39040610 GFGC
2 10001.0 7953.0 1993-11-22 2008-02-04 36720410 29274A10 EWST
3 10001.0 7953.0 2008-02-05 2009-08-03 36720410 29274A20 EWST
4 10001.0 7953.0 2009-08-04 2009-12-17 36720410 29269V10 EGAS
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