reconnect moved files to git repo

venv/lib/python3.11/site-packages/statsmodels/datasets/grunfeld/data.py

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+"""Grunfeld (1950) Investment Data"""
+import pandas as pd
+
+from statsmodels.datasets import utils as du
+
+__docformat__ = 'restructuredtext'
+
+COPYRIGHT   = """This is public domain."""
+TITLE       = __doc__
+SOURCE      = """This is the Grunfeld (1950) Investment Data.
+
+The source for the data was the original 11-firm data set from Grunfeld's Ph.D.
+thesis recreated by Kleiber and Zeileis (2008) "The Grunfeld Data at 50".
+The data can be found here.
+http://statmath.wu-wien.ac.at/~zeileis/grunfeld/
+
+For a note on the many versions of the Grunfeld data circulating see:
+http://www.stanford.edu/~clint/bench/grunfeld.htm
+"""
+
+DESCRSHORT  = """Grunfeld (1950) Investment Data for 11 U.S. Firms."""
+
+DESCRLONG   = DESCRSHORT
+
+NOTE        = """::
+
+    Number of observations - 220 (20 years for 11 firms)
+
+    Number of variables - 5
+
+    Variables name definitions::
+
+        invest  - Gross investment in 1947 dollars
+        value   - Market value as of Dec. 31 in 1947 dollars
+        capital - Stock of plant and equipment in 1947 dollars
+        firm    - General Motors, US Steel, General Electric, Chrysler,
+                Atlantic Refining, IBM, Union Oil, Westinghouse, Goodyear,
+                Diamond Match, American Steel
+        year    - 1935 - 1954
+
+    Note that raw_data has firm expanded to dummy variables, since it is a
+    string categorical variable.
+"""
+
+def load():
+    """
+    Loads the Grunfeld data and returns a Dataset class.
+
+    Returns
+    -------
+    Dataset
+        See DATASET_PROPOSAL.txt for more information.
+
+    Notes
+    -----
+    raw_data has the firm variable expanded to dummy variables for each
+    firm (ie., there is no reference dummy)
+    """
+    return load_pandas()
+
+def load_pandas():
+    """
+    Loads the Grunfeld data and returns a Dataset class.
+
+    Returns
+    -------
+    Dataset
+        See DATASET_PROPOSAL.txt for more information.
+
+    Notes
+    -----
+    raw_data has the firm variable expanded to dummy variables for each
+    firm (ie., there is no reference dummy)
+    """
+    data = _get_data()
+    data.year = data.year.astype(float)
+    raw_data = pd.get_dummies(data)
+    ds = du.process_pandas(data, endog_idx=0)
+    ds.raw_data = raw_data
+    return ds
+
+
+def _get_data():
+    data = du.load_csv(__file__, 'grunfeld.csv')
+    return data