BUG: Series.rank modifies inplace with NaT

doc/source/whatsnew/v0.22.0.txt

@@ -315,7 +315,7 @@ Reshaping
 
 - Bug in :func:`DataFrame.stack` which fails trying to sort mixed type levels under Python 3 (:issue:`18310`)
 - Fixed construction of a :class:`Series` from a ``dict`` containing ``NaN`` as key (:issue:`18480`)
-
+- Bug in :func:`Series.rank` where ``Series`` containing ``NaT`` modifies the ``Series`` inplace (:issue:`18521`)
 -
 
 Numeric
@@ -336,4 +336,3 @@ Other
 ^^^^^
 
 - Improved error message when attempting to use a Python keyword as an identifier in a ``numexpr`` backed query (:issue:`18221`)
--

pandas/_libs/algos_rank_helper.pxi.in

@@ -84,6 +84,11 @@ def rank_1d_{{dtype}}(object in_arr, ties_method='average', ascending=True,
     mask = np.isnan(values)
     {{elif dtype == 'int64'}}
     mask = values == iNaT
+
+    # create copy in case of iNaT
+    # values are mutated inplace
+    if mask.any():
+        values = values.copy()
     {{endif}}
 
     # double sort first by mask and then by values to ensure nan values are

pandas/tests/frame/test_analytics.py

@@ -2214,3 +2214,12 @@ def test_series_broadcasting(self):
             df_nan.clip_lower(s, axis=0)
             for op in ['lt', 'le', 'gt', 'ge', 'eq', 'ne']:
                 getattr(df, op)(s_nan, axis=0)
+
+    def test_series_nat_conversion(self):
+        # GH 18521
+        # Check rank does not mutate DataFrame
+        df = DataFrame(np.random.randn(10, 3), dtype='float64')
+        expected = df.copy()
+        df.rank()
+        result = df
+        tm.assert_frame_equal(result, expected)

pandas/tests/series/test_rank.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-from pandas import compat
+from pandas import compat, Timestamp
 
 import pytest
 
@@ -368,3 +368,13 @@ def test_rank_object_bug(self):
         # smoke tests
         Series([np.nan] * 32).astype(object).rank(ascending=True)
         Series([np.nan] * 32).astype(object).rank(ascending=False)
+
+    def test_rank_modify_inplace(self):
+        # GH 18521
+        # Check rank does not mutate series
+        s = Series([Timestamp('2017-01-05 10:20:27.569000'), NaT])
+        expected = s.copy()
+
+        s.rank()
+        result = s
+        assert_series_equal(result, expected)