DOC: low_memory in read_csv

closes #5888,  xref #12686

Author: Chris <cbartak@gmail.com>

Closes #13293 from chris-b1/low-memory-doc and squashes the following commits:

daf9bca [Chris] DOC: low_memory in read_csv

Author: chris-b1

doc/source/io.rst

@@ -169,6 +169,13 @@ skipfooter : int, default ``0``
   Number of lines at bottom of file to skip (unsupported with engine='c').
 nrows : int, default ``None``
   Number of rows of file to read. Useful for reading pieces of large files.
+low_memory : boolean, default ``True``
+  Internally process the file in chunks, resulting in lower memory use
+  while parsing, but possibly mixed type inference.  To ensure no mixed
+  types either set ``False``, or specify the type with the ``dtype`` parameter.
+  Note that the entire file is read into a single DataFrame regardless,
+  use the ``chunksize`` or ``iterator`` parameter to return the data in chunks.
+  (Only valid with C parser)
 
 NA and Missing Data Handling
 ++++++++++++++++++++++++++++

pandas/io/parsers.py

@@ -220,6 +220,13 @@
 warn_bad_lines : boolean, default True
     If error_bad_lines is False, and warn_bad_lines is True, a warning for each
     "bad line" will be output. (Only valid with C parser).
+low_memory : boolean, default True
+    Internally process the file in chunks, resulting in lower memory use
+    while parsing, but possibly mixed type inference.  To ensure no mixed
+    types either set False, or specify the type with the `dtype` parameter.
+    Note that the entire file is read into a single DataFrame regardless,
+    use the `chunksize` or `iterator` parameter to return the data in chunks.
+    (Only valid with C parser)
 
 Returns
 -------

pandas/tools/tests/test_merge.py

@@ -1134,8 +1134,8 @@ def test_concat_NaT_series(self):
         tm.assert_series_equal(result, expected)
 
     def test_concat_tz_frame(self):
-        df2 = DataFrame(dict(A=Timestamp('20130102', tz='US/Eastern'),
-                             B=Timestamp('20130603', tz='CET')),
+        df2 = DataFrame(dict(A=pd.Timestamp('20130102', tz='US/Eastern'),
+                             B=pd.Timestamp('20130603', tz='CET')),
                         index=range(5))
 
         # concat