Introduce Fama-French values reader for the Indian Market

Currently, there is a way to download Fama-French factors for doing
analysis on the US market. This diff introduces a reader that downloads
the files from the IIM Ahemdabad website to be used for analysing
portfolios and stocks in the Indian market.

References:
- https://faculty.iima.ac.in/iffm/Indian-Fama-French-Momentum/

Author: kirandasika0

pandas_datareader/data.py

@@ -12,6 +12,7 @@
 from pandas_datareader.eurostat import EurostatReader
 from pandas_datareader.exceptions import DEP_ERROR_MSG, ImmediateDeprecationError
 from pandas_datareader.famafrench import FamaFrenchReader
+from pandas_datareader.famafrench_in import FamaFrenchIndiaReader
 from pandas_datareader.fred import FredReader
 from pandas_datareader.oecd import OECDReader
 
@@ -83,11 +84,15 @@ def DataReader(
     ff = DataReader("F-F_Research_Data_Factors_weekly", "famafrench")
     ff = DataReader("6_Portfolios_2x3", "famafrench")
     ff = DataReader("F-F_ST_Reversal_Factor", "famafrench")
+
+    # Data from Fama/French for Indian markets
+    ff = DataReader("2025-12_FourFactors_and_Market_Returns_Daily", "famafrench_in")
     """
     expected_source = [
         "bankofcanada",
         "fred",
         "famafrench",
+        "famafrench_in",
         "oecd",
         "eurostat",
         "econdb",
@@ -126,7 +131,15 @@ def DataReader(
             pause=pause,
             session=session,
         ).read()
-
+    if data_source == "famafrench_in":
+        return FamaFrenchIndiaReader(
+            symbols=name,
+            start=start,
+            end=end,
+            retry_count=retry_count,
+            pause=pause,
+            session=session,
+        ).read()
     if data_source == "oecd":
         return OECDReader(
             symbols=name,

pandas_datareader/famafrench_in.py

@@ -0,0 +1,73 @@
+import datetime as dt
+import tempfile
+
+from pandas import read_csv, to_datetime
+
+from pandas_datareader.base import _BaseReader
+
+_URL = "https://faculty.iima.ac.in/iffm/Indian-Fama-French-Momentum/"
+_URL_PREFIX = "DATA/"
+_URL_SUFFIX = "_SurvivorshipBiasAdjusted.csv"
+
+
+def _parse_date_famafrench(x):
+    x = x.strip()
+    try:
+        return dt.datetime.strptime(x, "%Y%m")
+    except Exception:
+        pass
+    return to_datetime(x)
+
+
+class FamaFrenchIndiaReader(_BaseReader):
+    """
+    Get data for the given name from the Fama/French India data libary.
+
+    Credits to the IIM Ahemdabad
+    https://faculty.iima.ac.in/iffm/Indian-Fama-French-Momentum/
+    """
+
+    @property
+    def url(self):
+        """API URL"""
+        return f"{_URL}{_URL_PREFIX}{self.symbols}{_URL_SUFFIX}"
+
+    def read(self):
+        """
+        Read data
+
+        Returns
+        -------
+        df : DataFrame
+            A data frame that is indexed by the date
+        """
+        return super().read()
+
+    def _read_one_data(self, url, params):
+        params = {
+            "index_col": 0,
+            "parse_dates": True,
+        }
+
+        resp = self._get_response(url)
+
+        with tempfile.TemporaryFile() as tmpf:
+            tmpf.write(resp.content)
+            # seek to beginning so pandas can start reading the file
+            tmpf.seek(0)
+
+            df = read_csv(tmpf, **params)
+
+            # this dataset defines (Market - Risk-Free) rate as `MF` instead
+            # of `Mkt-RF`, so renaming it for better convenience.
+            df.rename(columns={"MF": "Mkt-RF"}, inplace=True)
+
+            if self.start is not None:
+                df = df[self.start :]
+            elif self.start is not None and self.end is not None:
+                df = df[self.start : self.end]
+            elif self.end is not None:
+                df = df[: self.end]
+
+            return df
+        return None

pandas_datareader/tests/test_famafrench_in.py

@@ -0,0 +1,36 @@
+import pandas as pd
+
+from pandas_datareader import data as web
+
+
+class TestFamaFrenchIndia:
+    def test_mkt_rf_rename(self):
+        ff = web.DataReader(
+            "2025-12_FourFactors_and_Market_Returns_Daily", "famafrench_in"
+        )
+        # assert that the col exists in the dataframe
+        assert ff["Mkt-RF"] is not None
+
+    def test_download_works_for_date_range(self):
+        ff = web.DataReader(
+            "2025-12_FourFactors_and_Market_Returns_Daily",
+            "famafrench_in",
+            start="2025-01-01",
+            end="2025-12-31",
+        )
+
+        assert ff.iloc[0].name.date() == pd.to_datetime("2025-01-01").date()
+        assert ff.iloc[-1].name.date() == pd.to_datetime("2025-12-31").date()
+
+    def test_download_monthly(self):
+        ff = web.DataReader(
+            "2025-12_FourFactors_and_Market_Returns_Monthly", "famafrench_in"
+        )
+        assert ff is not None
+
+    def test_download_yearly(self):
+        ff = web.DataReader(
+            "2025-12_FourFactors_and_Market_Returns_Yearly", "famafrench_in"
+        )
+
+        assert ff is not None