diff --git a/doc/source/release.rst b/doc/source/release.rst
index 8bf6a8d7b9488..b541ef4d2dd4b 100644
--- a/doc/source/release.rst
+++ b/doc/source/release.rst
@@ -180,6 +180,28 @@ Prior Version Deprecations/Changes
 
 - Remove ``column`` keyword from ``DataFrame.sort`` (:issue:`4370`)
 
+- Remove ``precision`` keyword from :func:`set_eng_float_format` (:issue:`6641`)
+
+- Remove ``force_unicode`` keyword from :meth:`DataFrame.to_string`,
+  :meth:`DataFrame.to_latex`, and :meth:`DataFrame.to_html`; these function
+  encode in unicode by default (:issue:`6641`)
+
+- Remove ``nanRep`` keyword from :meth:`DataFrame.to_csv` and
+  :meth:`DataFrame.to_string` (:issue:`6641`)
+
+- Remove ``unique`` keyword from :meth:`HDFStore.select_column` (:issue:`6641`)
+
+- Remove ``inferTimeRule`` keyword from :func:`Timestamp.offset` (:issue:`6641`)
+
+- Remove ``name`` keyword from :func:`get_data_yahoo` and
+  :func:`get_data_google` (:issue:`6641`)
+
+- Remove ``offset`` keyword from :class:`DatetimeIndex` constructor
+  (:issue:`6641`)
+
+- Remove ``time_rule`` from several rolling-moment statistical functions, such
+  as :func:`rolling_sum` (:issue:`6641`)
+
 Experimental Features
 ~~~~~~~~~~~~~~~~~~~~~
 
diff --git a/doc/source/v0.14.0.txt b/doc/source/v0.14.0.txt
index 23ab8f10116c1..335546a983e6f 100644
--- a/doc/source/v0.14.0.txt
+++ b/doc/source/v0.14.0.txt
@@ -328,6 +328,29 @@ Therse are prior version deprecations that are taking effect as of 0.14.0.
 
 - Remove ``column`` keyword from ``DataFrame.sort`` (:issue:`4370`)
 
+- Remove ``precision`` keyword from :func:`set_eng_float_format` (:issue:`6641`)
+
+- Remove ``force_unicode`` keyword from :meth:`DataFrame.to_string`,
+  :meth:`DataFrame.to_latex`, and :meth:`DataFrame.to_html`; these function
+  encode in unicode by default (:issue:`6641`)
+
+- Remove ``nanRep`` keyword from :meth:`DataFrame.to_csv` and
+  :meth:`DataFrame.to_string` (:issue:`6641`)
+
+- Remove ``unique`` keyword from :meth:`HDFStore.select_column` (:issue:`6641`)
+
+- Remove ``inferTimeRule`` keyword from :func:`Timestamp.offset` (:issue:`6641`)
+
+- Remove ``name`` keyword from :func:`get_data_yahoo` and
+  :func:`get_data_google` (:issue:`6641`)
+
+- Remove ``offset`` keyword from :class:`DatetimeIndex` constructor
+  (:issue:`6641`)
+
+- Remove ``time_rule`` from several rolling-moment statistical functions, such
+  as :func:`rolling_sum` (:issue:`6641`)
+  
+
 Deprecations
 ~~~~~~~~~~~~
 
diff --git a/pandas/core/format.py b/pandas/core/format.py
index 636b3f452a20c..a7cbf2c70a5d3 100644
--- a/pandas/core/format.py
+++ b/pandas/core/format.py
@@ -358,15 +358,10 @@ def _to_str_columns(self):
 
         return strcols
 
-    def to_string(self, force_unicode=None):
+    def to_string(self):
         """
         Render a DataFrame to a console-friendly tabular output.
         """
-        import warnings
-        if force_unicode is not None:  # pragma: no cover
-            warnings.warn(
-                "force_unicode is deprecated, it will have no effect",
-                FutureWarning)
 
         frame = self.frame
 
@@ -423,8 +418,7 @@ def _join_multiline(self, *strcols):
             st = ed
         return '\n\n'.join(str_lst)
 
-    def to_latex(self, force_unicode=None, column_format=None,
-                 longtable=False):
+    def to_latex(self, column_format=None, longtable=False):
         """
         Render a DataFrame to a LaTeX tabular/longtable environment output.
         """
@@ -435,12 +429,6 @@ def get_col_type(dtype):
             else:
                 return 'l'
 
-        import warnings
-        if force_unicode is not None:  # pragma: no cover
-            warnings.warn(
-                "force_unicode is deprecated, it will have no effect",
-                FutureWarning)
-
         frame = self.frame
 
         if len(frame.columns) == 0 or len(frame.index) == 0:
@@ -2139,7 +2127,7 @@ def __call__(self, num):
         return formatted  # .strip()
 
 
-def set_eng_float_format(precision=None, accuracy=3, use_eng_prefix=False):
+def set_eng_float_format(accuracy=3, use_eng_prefix=False):
     """
     Alter default behavior on how float is formatted in DataFrame.
     Format float in engineering format. By accuracy, we mean the number of
@@ -2147,11 +2135,6 @@ def set_eng_float_format(precision=None, accuracy=3, use_eng_prefix=False):
 
     See also EngFormatter.
     """
-    if precision is not None:  # pragma: no cover
-        import warnings
-        warnings.warn("'precision' parameter in set_eng_float_format is "
-                      "being renamed to 'accuracy'", FutureWarning)
-        accuracy = precision
 
     set_option("display.float_format", EngFormatter(accuracy, use_eng_prefix))
     set_option("display.column_space", max(12, accuracy + 9))
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 8875d2fdfb39a..a5d93f09c9e07 100755
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -1071,7 +1071,7 @@ def to_panel(self):
     @deprecate_kwarg(old_arg_name='cols', new_arg_name='columns')
     def to_csv(self, path_or_buf=None, sep=",", na_rep='', float_format=None,
                columns=None, header=True, index=True, index_label=None,
-               mode='w', nanRep=None, encoding=None, quoting=None,
+               mode='w', encoding=None, quoting=None,
                quotechar='"', line_terminator='\n', chunksize=None,
                tupleize_cols=False, date_format=None, doublequote=True,
                escapechar=None, **kwds):
@@ -1128,10 +1128,6 @@ def to_csv(self, path_or_buf=None, sep=",", na_rep='', float_format=None,
             Format string for datetime objects
         cols : kwarg only alias of columns [deprecated]
         """
-        if nanRep is not None:  # pragma: no cover
-            warnings.warn("nanRep is deprecated, use na_rep",
-                          FutureWarning)
-            na_rep = nanRep
 
         formatter = fmt.CSVFormatter(self, path_or_buf,
                                      line_terminator=line_terminator,
@@ -1275,21 +1271,12 @@ def to_stata(
     @Appender(fmt.docstring_to_string, indents=1)
     def to_string(self, buf=None, columns=None, col_space=None, colSpace=None,
                   header=True, index=True, na_rep='NaN', formatters=None,
-                  float_format=None, sparsify=None, nanRep=None,
-                  index_names=True, justify=None, force_unicode=None,
-                  line_width=None, max_rows=None, max_cols=None,
+                  float_format=None, sparsify=None, index_names=True,
+                  justify=None, line_width=None, max_rows=None, max_cols=None,
                   show_dimensions=False):
         """
         Render a DataFrame to a console-friendly tabular output.
         """
-        if force_unicode is not None:  # pragma: no cover
-            warnings.warn("force_unicode is deprecated, it will have no "
-                          "effect", FutureWarning)
-
-        if nanRep is not None:  # pragma: no cover
-            warnings.warn("nanRep is deprecated, use na_rep",
-                          FutureWarning)
-            na_rep = nanRep
 
         if colSpace is not None:  # pragma: no cover
             warnings.warn("colSpace is deprecated, use col_space",
@@ -1318,9 +1305,8 @@ def to_string(self, buf=None, columns=None, col_space=None, colSpace=None,
     def to_html(self, buf=None, columns=None, col_space=None, colSpace=None,
                 header=True, index=True, na_rep='NaN', formatters=None,
                 float_format=None, sparsify=None, index_names=True,
-                justify=None, force_unicode=None, bold_rows=True,
-                classes=None, escape=True, max_rows=None, max_cols=None,
-                show_dimensions=False):
+                justify=None, bold_rows=True, classes=None, escape=True,
+                max_rows=None, max_cols=None, show_dimensions=False):
         """
         Render a DataFrame as an HTML table.
 
@@ -1341,10 +1327,6 @@ def to_html(self, buf=None, columns=None, col_space=None, colSpace=None,
 
         """
 
-        if force_unicode is not None:  # pragma: no cover
-            warnings.warn("force_unicode is deprecated, it will have no "
-                          "effect", FutureWarning)
-
         if colSpace is not None:  # pragma: no cover
             warnings.warn("colSpace is deprecated, use col_space",
                           FutureWarning)
@@ -1372,7 +1354,7 @@ def to_html(self, buf=None, columns=None, col_space=None, colSpace=None,
     def to_latex(self, buf=None, columns=None, col_space=None, colSpace=None,
                  header=True, index=True, na_rep='NaN', formatters=None,
                  float_format=None, sparsify=None, index_names=True,
-                 bold_rows=True, force_unicode=None, longtable=False):
+                 bold_rows=True, longtable=False):
         """
         Render a DataFrame to a tabular environment table. You can splice
         this into a LaTeX document. Requires \\usepackage(booktabs}.
@@ -1387,10 +1369,6 @@ def to_latex(self, buf=None, columns=None, col_space=None, colSpace=None,
 
         """
 
-        if force_unicode is not None:  # pragma: no cover
-            warnings.warn("force_unicode is deprecated, it will have no "
-                          "effect", FutureWarning)
-
         if colSpace is not None:  # pragma: no cover
             warnings.warn("colSpace is deprecated, use col_space",
                           FutureWarning)
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 4ab7855ec2f84..bf6d96848b41b 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -881,7 +881,7 @@ def _repr_footer(self):
                                                str(self.dtype.name))
 
     def to_string(self, buf=None, na_rep='NaN', float_format=None,
-                  nanRep=None, length=False, dtype=False, name=False):
+                  length=False, dtype=False, name=False):
         """
         Render a string representation of the Series
 
@@ -906,10 +906,6 @@ def to_string(self, buf=None, na_rep='NaN', float_format=None,
         formatted : string (if not buffer passed)
         """
 
-        if nanRep is not None:  # pragma: no cover
-            warnings.warn("nanRep is deprecated, use na_rep", FutureWarning)
-            na_rep = nanRep
-
         the_repr = self._get_repr(float_format=float_format, na_rep=na_rep,
                                   length=length, dtype=dtype, name=name)
 
diff --git a/pandas/io/data.py b/pandas/io/data.py
index dc5dd2b4b7d80..e875e8aa3c6db 100644
--- a/pandas/io/data.py
+++ b/pandas/io/data.py
@@ -338,11 +338,7 @@ def _dl_mult_symbols(symbols, start, end, chunksize, retry_count, pause,
 
 
 def _get_data_from(symbols, start, end, retry_count, pause, adjust_price,
-                   ret_index, chunksize, source, name):
-    if name is not None:
-        warnings.warn("Arg 'name' is deprecated, please use 'symbols' "
-                      "instead.", FutureWarning)
-        symbols = name
+                   ret_index, chunksize, source):
 
     src_fn = _source_functions[source]
 
@@ -367,7 +363,7 @@ def _get_data_from(symbols, start, end, retry_count, pause, adjust_price,
 
 def get_data_yahoo(symbols=None, start=None, end=None, retry_count=3,
                    pause=0.001, adjust_price=False, ret_index=False,
-                   chunksize=25, name=None):
+                   chunksize=25):
     """
     Returns DataFrame/Panel of historical stock prices from symbols, over date
     range, start to end. To avoid being penalized by Yahoo! Finance servers,
@@ -402,12 +398,12 @@ def get_data_yahoo(symbols=None, start=None, end=None, retry_count=3,
     hist_data : DataFrame (str) or Panel (array-like object, DataFrame)
     """
     return _get_data_from(symbols, start, end, retry_count, pause,
-                          adjust_price, ret_index, chunksize, 'yahoo', name)
+                          adjust_price, ret_index, chunksize, 'yahoo')
 
 
 def get_data_google(symbols=None, start=None, end=None, retry_count=3,
                     pause=0.001, adjust_price=False, ret_index=False,
-                    chunksize=25, name=None):
+                    chunksize=25):
     """
     Returns DataFrame/Panel of historical stock prices from symbols, over date
     range, start to end. To avoid being penalized by Google Finance servers,
@@ -436,7 +432,7 @@ def get_data_google(symbols=None, start=None, end=None, retry_count=3,
     hist_data : DataFrame (str) or Panel (array-like object, DataFrame)
     """
     return _get_data_from(symbols, start, end, retry_count, pause,
-                          adjust_price, ret_index, chunksize, 'google', name)
+                          adjust_price, ret_index, chunksize, 'google')
 
 
 _FRED_URL = "http://research.stlouisfed.org/fred2/series/"
diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index 76f630082aa15..8d2ca794be6b8 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -685,13 +685,6 @@ def select_as_coordinates(
         return self.get_storer(key).read_coordinates(where=where, start=start,
                                                      stop=stop, **kwargs)
 
-    def unique(self, key, column, **kwargs):
-        warnings.warn("unique(key,column) is deprecated\n"
-                      "use select_column(key,column).unique() instead",
-                      FutureWarning)
-        return self.get_storer(key).read_column(column=column,
-                                                **kwargs).unique()
-
     def select_column(self, key, column, **kwargs):
         """
         return a single column from the table. This is generally only useful to
diff --git a/pandas/stats/moments.py b/pandas/stats/moments.py
index 523f055eaf605..f98c06a4d63a1 100644
--- a/pandas/stats/moments.py
+++ b/pandas/stats/moments.py
@@ -54,8 +54,7 @@
     (otherwise result is NA).
 freq : string or DateOffset object, optional (default None)
     Frequency to conform the data to before computing the statistic. Specified
-    as a frequency string or DateOffset object. `time_rule` is a legacy alias
-    for `freq`.
+    as a frequency string or DateOffset object.
 center : boolean, default False
     Set the labels at the center of the window.
 """
@@ -83,7 +82,6 @@
     beginning)
 freq : None or string alias / date offset object, default=None
     Frequency to conform to before computing statistic
-    time_rule is a legacy alias for freq
 adjust : boolean, default True
     Divide by decaying adjustment factor in beginning periods to account for
     imbalance in relative weightings (viewing EWMA as a moving average)
@@ -109,8 +107,7 @@
     (otherwise result is NA).
 freq : string or DateOffset object, optional (default None)
     Frequency to conform the data to before computing the statistic. Specified
-    as a frequency string or DateOffset object. `time_rule` is a legacy alias
-    for `freq`.
+    as a frequency string or DateOffset object.
 """
 
 
@@ -151,7 +148,7 @@
 """
 
 
-def rolling_count(arg, window, freq=None, center=False, time_rule=None):
+def rolling_count(arg, window, freq=None, center=False):
     """
     Rolling count of number of non-NaN observations inside provided window.
 
@@ -163,8 +160,7 @@ def rolling_count(arg, window, freq=None, center=False, time_rule=None):
         calculating the statistic.
     freq : string or DateOffset object, optional (default None)
         Frequency to conform the data to before computing the statistic. Specified
-        as a frequency string or DateOffset object. `time_rule` is a legacy alias
-        for `freq`
+        as a frequency string or DateOffset object.
     center : boolean, default False
         Whether the label should correspond with center of window
 
@@ -178,7 +174,7 @@ def rolling_count(arg, window, freq=None, center=False, time_rule=None):
     frequency by resampling the data. This is done with the default parameters
     of :meth:`~pandas.Series.resample` (i.e. using the `mean`).
     """
-    arg = _conv_timerule(arg, freq, time_rule)
+    arg = _conv_timerule(arg, freq)
     window = min(window, len(arg))
 
     return_hook, values = _process_data_structure(arg, kill_inf=False)
@@ -197,7 +193,7 @@ def rolling_count(arg, window, freq=None, center=False, time_rule=None):
               _roll_kw+_pairwise_kw, _flex_retval, _roll_notes)
 @Appender(_doc_template)
 def rolling_cov(arg1, arg2=None, window=None, min_periods=None, freq=None,
-                center=False, time_rule=None, pairwise=None):
+                center=False, pairwise=None):
     if window is None and isinstance(arg2, (int, float)):
         window = arg2
         arg2 = arg1
@@ -205,8 +201,8 @@ def rolling_cov(arg1, arg2=None, window=None, min_periods=None, freq=None,
     elif arg2 is None:
         arg2 = arg1
         pairwise = True if pairwise is None else pairwise  # only default unset
-    arg1 = _conv_timerule(arg1, freq, time_rule)
-    arg2 = _conv_timerule(arg2, freq, time_rule)
+    arg1 = _conv_timerule(arg1, freq)
+    arg2 = _conv_timerule(arg2, freq)
     window = min(window, len(arg1), len(arg2))
 
     def _get_cov(X, Y):
@@ -222,7 +218,7 @@ def _get_cov(X, Y):
               _roll_kw+_pairwise_kw, _flex_retval, _roll_notes)
 @Appender(_doc_template)
 def rolling_corr(arg1, arg2=None, window=None, min_periods=None, freq=None,
-                 center=False, time_rule=None, pairwise=None):
+                 center=False, pairwise=None):
     if window is None and isinstance(arg2, (int, float)):
         window = arg2
         arg2 = arg1
@@ -230,17 +226,17 @@ def rolling_corr(arg1, arg2=None, window=None, min_periods=None, freq=None,
     elif arg2 is None:
         arg2 = arg1
         pairwise = True if pairwise is None else pairwise  # only default unset
-    arg1 = _conv_timerule(arg1, freq, time_rule)
-    arg2 = _conv_timerule(arg2, freq, time_rule)
+    arg1 = _conv_timerule(arg1, freq)
+    arg2 = _conv_timerule(arg2, freq)
     window = min(window, len(arg1), len(arg2))
 
     def _get_corr(a, b):
         num = rolling_cov(a, b, window, min_periods, freq=freq,
-                          center=center, time_rule=time_rule)
+                          center=center)
         den = (rolling_std(a, window, min_periods, freq=freq,
-                           center=center, time_rule=time_rule) *
+                           center=center) *
                rolling_std(b, window, min_periods, freq=freq,
-                           center=center, time_rule=time_rule))
+                           center=center))
         return num / den
     return _flex_binary_moment(arg1, arg2, _get_corr, pairwise=bool(pairwise))
 
@@ -296,16 +292,16 @@ def _flex_binary_moment(arg1, arg2, f, pairwise=False):
               _roll_kw, _pairwise_retval, _roll_notes)
 @Appender(_doc_template)
 def rolling_corr_pairwise(df1, df2=None, window=None, min_periods=None,
-                          freq=None, center=False, time_rule=None):
+                          freq=None, center=False):
     import warnings
     warnings.warn("rolling_corr_pairwise is deprecated, use rolling_corr(..., pairwise=True)", FutureWarning)
     return rolling_corr(df1, df2, window=window, min_periods=min_periods,
-                        freq=freq, center=center, time_rule=time_rule,
+                        freq=freq, center=center,
                         pairwise=True)
 
 
 def _rolling_moment(arg, window, func, minp, axis=0, freq=None, center=False,
-                    time_rule=None, args=(), kwargs={}, **kwds):
+                    args=(), kwargs={}, **kwds):
     """
     Rolling statistical measure using supplied function. Designed to be
     used with passed-in Cython array-based functions.
@@ -322,7 +318,6 @@ def _rolling_moment(arg, window, func, minp, axis=0, freq=None, center=False,
         Frequency to conform to before computing statistic
     center : boolean, default False
         Whether the label should correspond with center of window
-    time_rule : Legacy alias for freq
     args : tuple
         Passed on to func
     kwargs : dict
@@ -332,7 +327,7 @@ def _rolling_moment(arg, window, func, minp, axis=0, freq=None, center=False,
     -------
     y : type of input
     """
-    arg = _conv_timerule(arg, freq, time_rule)
+    arg = _conv_timerule(arg, freq)
     calc = lambda x: func(x, window, minp=minp, args=args, kwargs=kwargs,
                           **kwds)
     return_hook, values = _process_data_structure(arg)
@@ -417,10 +412,10 @@ def _get_center_of_mass(com, span, halflife):
 @Substitution("Exponentially-weighted moving average", _unary_arg, _ewm_kw,
               _type_of_input_retval, _ewm_notes)
 @Appender(_doc_template)
-def ewma(arg, com=None, span=None, halflife=None, min_periods=0, freq=None, time_rule=None,
+def ewma(arg, com=None, span=None, halflife=None, min_periods=0, freq=None,
          adjust=True):
     com = _get_center_of_mass(com, span, halflife)
-    arg = _conv_timerule(arg, freq, time_rule)
+    arg = _conv_timerule(arg, freq)
 
     def _ewma(v):
         result = algos.ewma(v, com, int(adjust))
@@ -442,9 +437,9 @@ def _first_valid_index(arr):
               _ewm_kw+_bias_kw, _type_of_input_retval, _ewm_notes)
 @Appender(_doc_template)
 def ewmvar(arg, com=None, span=None, halflife=None, min_periods=0, bias=False,
-           freq=None, time_rule=None):
+           freq=None):
     com = _get_center_of_mass(com, span, halflife)
-    arg = _conv_timerule(arg, freq, time_rule)
+    arg = _conv_timerule(arg, freq)
     moment2nd = ewma(arg * arg, com=com, min_periods=min_periods)
     moment1st = ewma(arg, com=com, min_periods=min_periods)
 
@@ -458,9 +453,8 @@ def ewmvar(arg, com=None, span=None, halflife=None, min_periods=0, bias=False,
 @Substitution("Exponentially-weighted moving std", _unary_arg,
               _ewm_kw+_bias_kw, _type_of_input_retval, _ewm_notes)
 @Appender(_doc_template)
-def ewmstd(arg, com=None, span=None, halflife=None, min_periods=0, bias=False,
-           time_rule=None):
-    result = ewmvar(arg, com=com, span=span, halflife=halflife, time_rule=time_rule,
+def ewmstd(arg, com=None, span=None, halflife=None, min_periods=0, bias=False):
+    result = ewmvar(arg, com=com, span=span, halflife=halflife,
                     min_periods=min_periods, bias=bias)
     return _zsqrt(result)
 
@@ -470,8 +464,8 @@ def ewmstd(arg, com=None, span=None, halflife=None, min_periods=0, bias=False,
 @Substitution("Exponentially-weighted moving covariance", _binary_arg_flex,
               _ewm_kw+_pairwise_kw, _type_of_input_retval, _ewm_notes)
 @Appender(_doc_template)
-def ewmcov(arg1, arg2=None, com=None, span=None, halflife=None, min_periods=0, bias=False,
-           freq=None, time_rule=None, pairwise=None):
+def ewmcov(arg1, arg2=None, com=None, span=None, halflife=None, min_periods=0,
+           bias=False, freq=None, pairwise=None):
     if arg2 is None:
         arg2 = arg1
         pairwise = True if pairwise is None else pairwise
@@ -479,8 +473,8 @@ def ewmcov(arg1, arg2=None, com=None, span=None, halflife=None, min_periods=0, b
         com = arg2
         arg2 = arg1
         pairwise = True if pairwise is None else pairwise
-    arg1 = _conv_timerule(arg1, freq, time_rule)
-    arg2 = _conv_timerule(arg2, freq, time_rule)
+    arg1 = _conv_timerule(arg1, freq)
+    arg2 = _conv_timerule(arg2, freq)
 
     def _get_ewmcov(X, Y):
         mean = lambda x: ewma(x, com=com, span=span, halflife=halflife, min_periods=min_periods)
@@ -498,7 +492,7 @@ def _get_ewmcov(X, Y):
               _ewm_kw+_pairwise_kw, _type_of_input_retval, _ewm_notes)
 @Appender(_doc_template)
 def ewmcorr(arg1, arg2=None, com=None, span=None, halflife=None, min_periods=0,
-            freq=None, time_rule=None, pairwise=None):
+            freq=None, pairwise=None):
     if arg2 is None:
         arg2 = arg1
         pairwise = True if pairwise is None else pairwise
@@ -506,8 +500,8 @@ def ewmcorr(arg1, arg2=None, com=None, span=None, halflife=None, min_periods=0,
         com = arg2
         arg2 = arg1
         pairwise = True if pairwise is None else pairwise
-    arg1 = _conv_timerule(arg1, freq, time_rule)
-    arg2 = _conv_timerule(arg2, freq, time_rule)
+    arg1 = _conv_timerule(arg1, freq)
+    arg2 = _conv_timerule(arg2, freq)
 
     def _get_ewmcorr(X, Y):
         mean = lambda x: ewma(x, com=com, span=span, halflife=halflife, min_periods=min_periods)
@@ -547,13 +541,7 @@ def _prep_binary(arg1, arg2):
 # Python interface to Cython functions
 
 
-def _conv_timerule(arg, freq, time_rule):
-    if time_rule is not None:
-        import warnings
-        warnings.warn("time_rule argument is deprecated, replace with freq",
-                      FutureWarning)
-
-        freq = time_rule
+def _conv_timerule(arg, freq):
 
     types = (DataFrame, Series)
     if freq is not None and isinstance(arg, types):
@@ -584,13 +572,12 @@ def _rolling_func(func, desc, check_minp=_use_window):
     @Appender(_doc_template)
     @wraps(func)
     def f(arg, window, min_periods=None, freq=None, center=False,
-          time_rule=None, **kwargs):
+          **kwargs):
         def call_cython(arg, window, minp, args=(), kwargs={}, **kwds):
             minp = check_minp(minp, window)
             return func(arg, window, minp, **kwds)
-        return _rolling_moment(arg, window, call_cython, min_periods,
-                               freq=freq, center=center,
-                               time_rule=time_rule, **kwargs)
+        return _rolling_moment(arg, window, call_cython, min_periods, freq=freq,
+                               center=center, **kwargs)
 
     return f
 
@@ -612,7 +599,7 @@ def call_cython(arg, window, minp, args=(), kwargs={}, **kwds):
 
 
 def rolling_quantile(arg, window, quantile, min_periods=None, freq=None,
-                     center=False, time_rule=None):
+                     center=False):
     """Moving quantile.
 
     Parameters
@@ -628,8 +615,7 @@ def rolling_quantile(arg, window, quantile, min_periods=None, freq=None,
         (otherwise result is NA).
     freq : string or DateOffset object, optional (default None)
         Frequency to conform the data to before computing the statistic. Specified
-        as a frequency string or DateOffset object. `time_rule` is a legacy alias
-        for `freq`
+        as a frequency string or DateOffset object.
     center : boolean, default False
         Whether the label should correspond with center of window
 
@@ -650,12 +636,12 @@ def rolling_quantile(arg, window, quantile, min_periods=None, freq=None,
     def call_cython(arg, window, minp, args=(), kwargs={}):
         minp = _use_window(minp, window)
         return algos.roll_quantile(arg, window, minp, quantile)
-    return _rolling_moment(arg, window, call_cython, min_periods,
-                           freq=freq, center=center, time_rule=time_rule)
+    return _rolling_moment(arg, window, call_cython, min_periods, freq=freq,
+                           center=center)
 
 
 def rolling_apply(arg, window, func, min_periods=None, freq=None,
-                  center=False, time_rule=None, args=(), kwargs={}):
+                  center=False, args=(), kwargs={}):
     """Generic moving function application.
 
     Parameters
@@ -671,8 +657,7 @@ def rolling_apply(arg, window, func, min_periods=None, freq=None,
         (otherwise result is NA).
     freq : string or DateOffset object, optional (default None)
         Frequency to conform the data to before computing the statistic. Specified
-        as a frequency string or DateOffset object. `time_rule` is a legacy alias
-        for `freq`.
+        as a frequency string or DateOffset object.
     center : boolean, default False
         Whether the label should correspond with center of window
     args : tuple
@@ -696,13 +681,12 @@ def rolling_apply(arg, window, func, min_periods=None, freq=None,
     def call_cython(arg, window, minp, args, kwargs):
         minp = _use_window(minp, window)
         return algos.roll_generic(arg, window, minp, func, args, kwargs)
-    return _rolling_moment(arg, window, call_cython, min_periods,
-                           freq=freq, center=center, time_rule=time_rule,
-                           args=args, kwargs=kwargs)
+    return _rolling_moment(arg, window, call_cython, min_periods, freq=freq,
+                           center=center, args=args, kwargs=kwargs)
 
 
 def rolling_window(arg, window=None, win_type=None, min_periods=None,
-                   freq=None, center=False, mean=True, time_rule=None,
+                   freq=None, center=False, mean=True,
                    axis=0, **kwargs):
     """
     Applies a moving window of type ``window_type`` and size ``window``
@@ -721,8 +705,7 @@ def rolling_window(arg, window=None, win_type=None, min_periods=None,
         (otherwise result is NA).
     freq : string or DateOffset object, optional (default None)
         Frequency to conform the data to before computing the statistic. Specified
-        as a frequency string or DateOffset object. `time_rule` is a legacy alias
-        for `freq`.
+        as a frequency string or DateOffset object.
     center : boolean, default False
         Whether the label should correspond with center of window
     mean : boolean, default True
@@ -778,7 +761,7 @@ def rolling_window(arg, window=None, win_type=None, min_periods=None,
 
     minp = _use_window(min_periods, len(window))
 
-    arg = _conv_timerule(arg, freq, time_rule)
+    arg = _conv_timerule(arg, freq)
     return_hook, values = _process_data_structure(arg)
 
     f = lambda x: algos.roll_window(x, window, minp, avg=mean)
@@ -816,16 +799,14 @@ def _expanding_func(func, desc, check_minp=_use_window):
     @Substitution(desc, _unary_arg, _expanding_kw, _type_of_input_retval, "")
     @Appender(_doc_template)
     @wraps(func)
-    def f(arg, min_periods=1, freq=None, center=False, time_rule=None,
-          **kwargs):
+    def f(arg, min_periods=1, freq=None, center=False, **kwargs):
         window = len(arg)
 
         def call_cython(arg, window, minp, args=(), kwargs={}, **kwds):
             minp = check_minp(minp, window)
             return func(arg, window, minp, **kwds)
-        return _rolling_moment(arg, window, call_cython, min_periods,
-                               freq=freq, center=center,
-                               time_rule=time_rule, **kwargs)
+        return _rolling_moment(arg, window, call_cython, min_periods, freq=freq,
+                               center=center, **kwargs)
 
     return f
 
@@ -849,7 +830,7 @@ def call_cython(arg, window, minp, args=(), kwargs={}, **kwds):
     check_minp=_require_min_periods(4))
 
 
-def expanding_count(arg, freq=None, center=False, time_rule=None):
+def expanding_count(arg, freq=None, center=False):
     """
     Expanding count of number of non-NaN observations.
 
@@ -858,8 +839,7 @@ def expanding_count(arg, freq=None, center=False, time_rule=None):
     arg :  DataFrame or numpy ndarray-like
     freq : string or DateOffset object, optional (default None)
         Frequency to conform the data to before computing the statistic. Specified
-        as a frequency string or DateOffset object. `time_rule` is a legacy alias
-        for `freq`.
+        as a frequency string or DateOffset object.
     center : boolean, default False
         Whether the label should correspond with center of window.
 
@@ -873,12 +853,11 @@ def expanding_count(arg, freq=None, center=False, time_rule=None):
     frequency by resampling the data. This is done with the default parameters
     of :meth:`~pandas.Series.resample` (i.e. using the `mean`).
     """
-    return rolling_count(arg, len(arg), freq=freq, center=center,
-                         time_rule=time_rule)
+    return rolling_count(arg, len(arg), freq=freq, center=center)
 
 
 def expanding_quantile(arg, quantile, min_periods=1, freq=None,
-                       center=False, time_rule=None):
+                       center=False):
     """Expanding quantile.
 
     Parameters
@@ -891,8 +870,7 @@ def expanding_quantile(arg, quantile, min_periods=1, freq=None,
         (otherwise result is NA).
     freq : string or DateOffset object, optional (default None)
         Frequency to conform the data to before computing the statistic. Specified
-        as a frequency string or DateOffset object. `time_rule` is a legacy alias
-        for `freq`.
+        as a frequency string or DateOffset object.
     center : boolean, default False
         Whether the label should correspond with center of window.
 
@@ -907,14 +885,14 @@ def expanding_quantile(arg, quantile, min_periods=1, freq=None,
     of :meth:`~pandas.Series.resample` (i.e. using the `mean`).
     """
     return rolling_quantile(arg, len(arg), quantile, min_periods=min_periods,
-                            freq=freq, center=center, time_rule=time_rule)
+                            freq=freq, center=center)
 
 
 @Substitution("Unbiased expanding covariance.", _binary_arg_flex,
               _expanding_kw+_pairwise_kw, _flex_retval, "")
 @Appender(_doc_template)
 def expanding_cov(arg1, arg2=None, min_periods=1, freq=None, center=False,
-                  time_rule=None, pairwise=None):
+                  pairwise=None):
     if arg2 is None:
         arg2 = arg1
         pairwise = True if pairwise is None else pairwise
@@ -925,14 +903,14 @@ def expanding_cov(arg1, arg2=None, min_periods=1, freq=None, center=False,
     window = max(len(arg1), len(arg2))
     return rolling_cov(arg1, arg2, window,
                        min_periods=min_periods, freq=freq,
-                       center=center, time_rule=time_rule, pairwise=pairwise)
+                       center=center, pairwise=pairwise)
 
 
 @Substitution("Expanding sample correlation.", _binary_arg_flex,
               _expanding_kw+_pairwise_kw, _flex_retval, "")
 @Appender(_doc_template)
 def expanding_corr(arg1, arg2=None, min_periods=1, freq=None, center=False,
-                   time_rule=None, pairwise=None):
+                   pairwise=None):
     if arg2 is None:
         arg2 = arg1
         pairwise = True if pairwise is None else pairwise
@@ -943,8 +921,7 @@ def expanding_corr(arg1, arg2=None, min_periods=1, freq=None, center=False,
     window = max(len(arg1), len(arg2))
     return rolling_corr(arg1, arg2, window,
                         min_periods=min_periods,
-                        freq=freq, center=center, time_rule=time_rule,
-                        pairwise=pairwise)
+                        freq=freq, center=center, pairwise=pairwise)
 
 
 @Substitution("Deprecated. Use expanding_corr(..., pairwise=True) instead.\n\n"
@@ -952,16 +929,15 @@ def expanding_corr(arg1, arg2=None, min_periods=1, freq=None, center=False,
               _expanding_kw, _pairwise_retval, "")
 @Appender(_doc_template)
 def expanding_corr_pairwise(df1, df2=None, min_periods=1, freq=None,
-                            center=False, time_rule=None):
+                            center=False):
     import warnings
     warnings.warn("expanding_corr_pairwise is deprecated, use expanding_corr(..., pairwise=True)", FutureWarning)
     return expanding_corr(df1, df2, min_periods=min_periods,
-                          freq=freq, center=center, time_rule=time_rule,
-                          pairwise=True)
+                          freq=freq, center=center, pairwise=True)
 
 
 def expanding_apply(arg, func, min_periods=1, freq=None, center=False,
-                    time_rule=None, args=(), kwargs={}):
+                    args=(), kwargs={}):
     """Generic expanding function application.
 
     Parameters
@@ -974,8 +950,7 @@ def expanding_apply(arg, func, min_periods=1, freq=None, center=False,
         (otherwise result is NA).
     freq : string or DateOffset object, optional (default None)
         Frequency to conform the data to before computing the statistic. Specified
-        as a frequency string or DateOffset object. `time_rule` is a legacy alias
-        for `freq`.
+        as a frequency string or DateOffset object.
     center : boolean, default False
         Whether the label should correspond with center of window.
     args : tuple
@@ -995,5 +970,4 @@ def expanding_apply(arg, func, min_periods=1, freq=None, center=False,
     """
     window = len(arg)
     return rolling_apply(arg, window, func, min_periods=min_periods, freq=freq,
-                         center=center, time_rule=time_rule, args=args,
-                         kwargs=kwargs)
+                         center=center, args=args, kwargs=kwargs)
diff --git a/pandas/stats/tests/test_moments.py b/pandas/stats/tests/test_moments.py
index 97f08e7052c87..22661ea7cacda 100644
--- a/pandas/stats/tests/test_moments.py
+++ b/pandas/stats/tests/test_moments.py
@@ -485,27 +485,6 @@ def _check_structures(self, func, static_comp,
             assert_series_equal(series_xp, series_rs)
             assert_frame_equal(frame_xp, frame_rs)
 
-    def test_legacy_time_rule_arg(self):
-        # suppress deprecation warnings
-        sys.stderr = StringIO()
-
-        rng = bdate_range('1/1/2000', periods=20)
-        ts = Series(np.random.randn(20), index=rng)
-        ts = ts.take(np.random.permutation(len(ts))[:12]).sort_index()
-
-        try:
-            result = mom.rolling_mean(ts, 1, min_periods=1, freq='B')
-            expected = mom.rolling_mean(ts, 1, min_periods=1,
-                                        time_rule='WEEKDAY')
-            tm.assert_series_equal(result, expected)
-
-            result = mom.ewma(ts, span=5, freq='B')
-            expected = mom.ewma(ts, span=5, time_rule='WEEKDAY')
-            tm.assert_series_equal(result, expected)
-
-        finally:
-            sys.stderr = sys.__stderr__
-
     def test_ewma(self):
         self._check_ew(mom.ewma)
 
diff --git a/pandas/tseries/frequencies.py b/pandas/tseries/frequencies.py
index 7988b01af8c48..a75d30c3323d6 100644
--- a/pandas/tseries/frequencies.py
+++ b/pandas/tseries/frequencies.py
@@ -239,21 +239,6 @@ def get_period_alias(offset_str):
 _legacy_reverse_map = dict((v, k) for k, v in
                            reversed(sorted(compat.iteritems(_rule_aliases))))
 
-
-def inferTimeRule(index):
-    from pandas.tseries.index import DatetimeIndex
-    import warnings
-    warnings.warn("This method is deprecated, use infer_freq or inferred_freq"
-                  " attribute of DatetimeIndex", FutureWarning)
-
-    freq = DatetimeIndex(index).inferred_freq
-    if freq is None:
-        raise Exception('Unable to infer time rule')
-
-    offset = to_offset(freq)
-    return get_legacy_offset_name(offset)
-
-
 def to_offset(freqstr):
     """
     Return DateOffset object from string representation
diff --git a/pandas/tseries/index.py b/pandas/tseries/index.py
index c58447acec621..353f5f1c472ba 100644
--- a/pandas/tseries/index.py
+++ b/pandas/tseries/index.py
@@ -158,10 +158,6 @@ def __new__(cls, data=None,
         dayfirst = kwds.pop('dayfirst', None)
         yearfirst = kwds.pop('yearfirst', None)
         infer_dst = kwds.pop('infer_dst', False)
-        warn = False
-        if 'offset' in kwds and kwds['offset']:
-            freq = kwds['offset']
-            warn = True
 
         freq_infer = False
         if not isinstance(freq, DateOffset):
@@ -173,14 +169,6 @@ def __new__(cls, data=None,
                 freq_infer = True
                 freq = None
 
-        if warn:
-            import warnings
-            warnings.warn("parameter 'offset' is deprecated, "
-                          "please use 'freq' instead",
-                          FutureWarning)
-
-        offset = freq
-
         if periods is not None:
             if com.is_float(periods):
                 periods = int(periods)
@@ -188,12 +176,12 @@ def __new__(cls, data=None,
                 raise ValueError('Periods must be a number, got %s' %
                                  str(periods))
 
-        if data is None and offset is None:
+        if data is None and freq is None:
             raise ValueError("Must provide freq argument if no data is "
                              "supplied")
 
         if data is None:
-            return cls._generate(start, end, periods, name, offset,
+            return cls._generate(start, end, periods, name, freq,
                                  tz=tz, normalize=normalize, closed=closed,
                                  infer_dst=infer_dst)
 
@@ -211,11 +199,11 @@ def __new__(cls, data=None,
 
             # try a few ways to make it datetime64
             if lib.is_string_array(data):
-                data = _str_to_dt_array(data, offset, dayfirst=dayfirst,
+                data = _str_to_dt_array(data, freq, dayfirst=dayfirst,
                                         yearfirst=yearfirst)
             else:
                 data = tools.to_datetime(data, errors='raise')
-                data.offset = offset
+                data.offset = freq
                 if isinstance(data, DatetimeIndex):
                     if name is not None:
                         data.name = name
@@ -226,7 +214,7 @@ def __new__(cls, data=None,
                     return data
 
         if issubclass(data.dtype.type, compat.string_types):
-            data = _str_to_dt_array(data, offset, dayfirst=dayfirst,
+            data = _str_to_dt_array(data, freq, dayfirst=dayfirst,
                                       yearfirst=yearfirst)
 
         if issubclass(data.dtype.type, np.datetime64):
@@ -238,8 +226,8 @@ def __new__(cls, data=None,
 
                 subarr = data.values
 
-                if offset is None:
-                    offset = data.offset
+                if freq is None:
+                    freq = data.offset
                     verify_integrity = False
             else:
                 if data.dtype != _NS_DTYPE:
@@ -287,13 +275,13 @@ def __new__(cls, data=None,
 
         subarr = subarr.view(cls)
         subarr.name = name
-        subarr.offset = offset
+        subarr.offset = freq
         subarr.tz = tz
 
         if verify_integrity and len(subarr) > 0:
-            if offset is not None and not freq_infer:
+            if freq is not None and not freq_infer:
                 inferred = subarr.inferred_freq
-                if inferred != offset.freqstr:
+                if inferred != freq.freqstr:
                     raise ValueError('Dates do not conform to passed '
                                      'frequency')
 
diff --git a/pandas/tseries/tests/test_timeseries_legacy.py b/pandas/tseries/tests/test_timeseries_legacy.py
index 3155f0f6e1a80..0315cb598b88a 100644
--- a/pandas/tseries/tests/test_timeseries_legacy.py
+++ b/pandas/tseries/tests/test_timeseries_legacy.py
@@ -262,28 +262,6 @@ def setUp(self):
         # suppress deprecation warnings
         sys.stderr = StringIO()
 
-    def test_inferTimeRule(self):
-        from pandas.tseries.frequencies import inferTimeRule
-
-        index1 = [datetime(2010, 1, 29, 0, 0),
-                  datetime(2010, 2, 26, 0, 0),
-                  datetime(2010, 3, 31, 0, 0)]
-
-        index2 = [datetime(2010, 3, 26, 0, 0),
-                  datetime(2010, 3, 29, 0, 0),
-                  datetime(2010, 3, 30, 0, 0)]
-
-        index3 = [datetime(2010, 3, 26, 0, 0),
-                  datetime(2010, 3, 27, 0, 0),
-                  datetime(2010, 3, 29, 0, 0)]
-
-        # LEGACY
-        assert inferTimeRule(index1) == 'EOM'
-        assert inferTimeRule(index2) == 'WEEKDAY'
-
-        self.assertRaises(Exception, inferTimeRule, index1[:2])
-        self.assertRaises(Exception, inferTimeRule, index3)
-
     def test_time_rule(self):
         result = DateRange('1/1/2000', '1/30/2000', time_rule='WEEKDAY')
         result2 = DateRange('1/1/2000', '1/30/2000', timeRule='WEEKDAY')