BUG: read_csv not applying dtype to index col (#44632)

doc/source/whatsnew/v1.4.0.rst

@@ -663,6 +663,7 @@ I/O
 - Bug in :func:`json_normalize` where multi-character ``sep`` parameter is incorrectly prefixed to every key (:issue:`43831`)
 - Bug in :func:`json_normalize` where reading data with missing multi-level metadata would not respect errors="ignore" (:issue:`44312`)
 - Bug in :func:`read_csv` with :code:`float_precision="round_trip"` which did not skip initial/trailing whitespace (:issue:`43713`)
+- Bug in :func:`read_csv` not applying dtype for ``index_col`` (:issue:`9435`)
 - Bug in dumping/loading a :class:`DataFrame` with ``yaml.dump(frame)`` (:issue:`42748`)
 - Bug in :class:`ExcelWriter`, where ``engine_kwargs`` were not passed through to all engines (:issue:`43442`)
 - Bug in :func:`read_csv` raising ``ValueError`` when ``parse_dates`` was used with ``MultiIndex`` columns (:issue:`8991`)

pandas/io/parsers/base_parser.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 from collections import defaultdict
+from copy import copy
 import csv
 import datetime
 from enum import Enum
@@ -149,6 +150,8 @@ def __init__(self, kwds):
         self.na_filter = kwds.get("na_filter", False)
         self.keep_default_na = kwds.get("keep_default_na", True)
 
+        self.dtype = copy(kwds.get("dtype", None))
+
         self.true_values = kwds.get("true_values")
         self.false_values = kwds.get("false_values")
         self.mangle_dupe_cols = kwds.get("mangle_dupe_cols", True)
@@ -511,6 +514,19 @@ def _get_name(icol):
 
         return index
 
+    def _clean_mapping(self, mapping):
+        """converts col numbers to names"""
+        if not isinstance(mapping, dict):
+            return mapping
+        clean = {}
+        for col, v in mapping.items():
+            # for mypy
+            assert self.orig_names is not None
+            if isinstance(col, int) and col not in self.orig_names:
+                col = self.orig_names[col]
+            clean[col] = v
+        return clean
+
     @final
     def _agg_index(self, index, try_parse_dates: bool = True) -> Index:
         arrays = []
@@ -535,7 +551,17 @@ def _agg_index(self, index, try_parse_dates: bool = True) -> Index:
                         col_name, self.na_values, self.na_fvalues, self.keep_default_na
                     )
 
-            arr, _ = self._infer_types(arr, col_na_values | col_na_fvalues)
+            clean_dtypes = self._clean_mapping(self.dtype)
+
+            cast_type = None
+            if isinstance(clean_dtypes, dict) and self.index_names is not None:
+                cast_type = clean_dtypes.get(self.index_names[i], None)
+
+            try_num_bool = not (cast_type and is_string_dtype(cast_type))
+
+            arr, _ = self._infer_types(
+                arr, col_na_values | col_na_fvalues, try_num_bool
+            )
             arrays.append(arr)
 
         names = self.index_names

pandas/io/parsers/python_parser.py

@@ -4,7 +4,6 @@
     abc,
     defaultdict,
 )
-from copy import copy
 import csv
 from io import StringIO
 import re
@@ -89,7 +88,6 @@ def __init__(
         self.verbose = kwds["verbose"]
         self.converters = kwds["converters"]
 
-        self.dtype = copy(kwds["dtype"])
         self.thousands = kwds["thousands"]
         self.decimal = kwds["decimal"]
 
@@ -308,21 +306,8 @@ def get_chunk(self, size=None):
 
     def _convert_data(self, data):
         # apply converters
-        def _clean_mapping(mapping):
-            """converts col numbers to names"""
-            clean = {}
-            for col, v in mapping.items():
-                if isinstance(col, int) and col not in self.orig_names:
-                    col = self.orig_names[col]
-                clean[col] = v
-            return clean
-
-        clean_conv = _clean_mapping(self.converters)
-        if not isinstance(self.dtype, dict):
-            # handles single dtype applied to all columns
-            clean_dtypes = self.dtype
-        else:
-            clean_dtypes = _clean_mapping(self.dtype)
+        clean_conv = self._clean_mapping(self.converters)
+        clean_dtypes = self._clean_mapping(self.dtype)
 
         # Apply NA values.
         clean_na_values = {}

pandas/tests/io/parser/test_index_col.py

@@ -321,3 +321,14 @@ def test_infer_types_boolean_sum(all_parsers):
     # index column of dtype 'object', and the Python parser will return a
     # index column of dtype 'int64'.
     tm.assert_frame_equal(result, expected, check_index_type=False)
+
+
+@skip_pyarrow
+@pytest.mark.parametrize("dtype, val", [(object, "01"), ("int64", 1)])
+def test_specify_dtype_for_index_col(all_parsers, dtype, val):
+    # GH#9435
+    data = "a,b\n01,2"
+    parser = all_parsers
+    result = parser.read_csv(StringIO(data), index_col="a", dtype={"a": dtype})
+    expected = DataFrame({"b": [2]}, index=Index([val], name="a"))
+    tm.assert_frame_equal(result, expected)