Merge tag 'v0.19.1' into debian

Version 0.19.1

* tag 'v0.19.1': (43 commits)
  RLS: v0.19.1
  DOC: update whatsnew/release notes for 0.19.1 (pandas-dev#14573)
  [Backport pandas-dev#14545] BUG/API: Index.append with mixed object/Categorical indices (pandas-dev#14545)
  DOC: rst fixes
  [Backport pandas-dev#14567] DEPR: add deprecation warning for com.array_equivalent (pandas-dev#14567)
  [Backport pandas-dev#14551] PERF: casting loc to labels dtype before searchsorted (pandas-dev#14551)
  [Backport pandas-dev#14536] BUG: DataFrame.quantile with NaNs (GH14357) (pandas-dev#14536)
  [Backport pandas-dev#14520] BUG: don't close user-provided file handles in C parser (GH14418) (pandas-dev#14520)
  [Backport pandas-dev#14392] BUG: Dataframe constructor when given dict with None value (pandas-dev#14392)
  [Backport pandas-dev#14514] BUG: Don't parse inline quotes in skipped lines (pandas-dev#14514)
  [Bacport pandas-dev#14543] BUG: tseries ceil doc fix (pandas-dev#14543)
  [Backport pandas-dev#14541] DOC: Simplify the gbq integration testing procedure for contributors (pandas-dev#14541)
  [Backport pandas-dev#14527] BUG/ERR: raise correct error when sql driver is not installed (pandas-dev#14527)
  [Backport pandas-dev#14501] BUG: fix DatetimeIndex._maybe_cast_slice_bound for empty index (GH14354) (pandas-dev#14501)
  [Backport pandas-dev#14442] DOC: Expand on reference docs for read_json() (pandas-dev#14442)
  BLD: fix 3.4 build for cython to 0.24.1
  [Backport pandas-dev#14492] BUG: Accept unicode quotechars again in pd.read_csv
  [Backport pandas-dev#14496] BLD: Support Cython 0.25
  [Backport pandas-dev#14498] COMPAT/TST: fix test for range testing of negative integers to neg powers
  [Backport pandas-dev#14476] PERF: performance regression in Series.asof (pandas-dev#14476)
  ...

Author: yarikoptic

asv_bench/benchmarks/algorithms.py

@@ -15,6 +15,14 @@ def setup(self):
         self.int = pd.Int64Index(np.arange(N).repeat(5))
         self.float = pd.Float64Index(np.random.randn(N).repeat(5))
 
+        # Convenience naming.
+        self.checked_add = pd.core.nanops._checked_add_with_arr
+
+        self.arr = np.arange(1000000)
+        self.arrpos = np.arange(1000000)
+        self.arrneg = np.arange(-1000000, 0)
+        self.arrmixed = np.array([1, -1]).repeat(500000)
+
     def time_int_factorize(self):
         self.int.factorize()
 
@@ -29,3 +37,21 @@ def time_int_duplicated(self):
 
     def time_float_duplicated(self):
         self.float.duplicated()
+
+    def time_add_overflow_pos_scalar(self):
+        self.checked_add(self.arr, 1)
+
+    def time_add_overflow_neg_scalar(self):
+        self.checked_add(self.arr, -1)
+
+    def time_add_overflow_zero_scalar(self):
+        self.checked_add(self.arr, 0)
+
+    def time_add_overflow_pos_arr(self):
+        self.checked_add(self.arr, self.arrpos)
+
+    def time_add_overflow_neg_arr(self):
+        self.checked_add(self.arr, self.arrneg)
+
+    def time_add_overflow_mixed_arr(self):
+        self.checked_add(self.arr, self.arrmixed)

asv_bench/benchmarks/attrs_caching.py

@@ -20,4 +20,4 @@ def setup(self):
         self.cur_index = self.df.index
 
     def time_setattr_dataframe_index(self):
-        self.df.index = self.cur_index
+        self.df.index = self.cur_index

asv_bench/benchmarks/ctors.py

@@ -49,4 +49,4 @@ def setup(self):
         self.s = Series(([Timestamp('20110101'), Timestamp('20120101'), Timestamp('20130101')] * 1000))
 
     def time_index_from_series_ctor(self):
-        Index(self.s)
+        Index(self.s)

asv_bench/benchmarks/frame_ctor.py

@@ -1703,4 +1703,4 @@ def setup(self):
         self.dict_list = [dict(zip(self.columns, row)) for row in self.frame.values]
 
     def time_series_ctor_from_dict(self):
-        Series(self.some_dict)
+        Series(self.some_dict)

asv_bench/benchmarks/groupby.py

@@ -548,6 +548,32 @@ def time_groupby_sum(self):
         self.df.groupby(['a'])['b'].sum()
 
 
+class groupby_period(object):
+    # GH 14338
+    goal_time = 0.2
+
+    def make_grouper(self, N):
+        return pd.period_range('1900-01-01', freq='D', periods=N)
+
+    def setup(self):
+        N = 10000
+        self.grouper = self.make_grouper(N)
+        self.df = pd.DataFrame(np.random.randn(N, 2))
+
+    def time_groupby_sum(self):
+        self.df.groupby(self.grouper).sum()
+
+
+class groupby_datetime(groupby_period):
+    def make_grouper(self, N):
+        return pd.date_range('1900-01-01', freq='D', periods=N)
+
+
+class groupby_datetimetz(groupby_period):
+    def make_grouper(self, N):
+        return pd.date_range('1900-01-01', freq='D', periods=N,
+                             tz='US/Central')
+
 #----------------------------------------------------------------------
 # Series.value_counts
 

asv_bench/benchmarks/hdfstore_bench.py

@@ -348,4 +348,4 @@ def remove(self, f):
         try:
             os.remove(self.f)
         except:
-            pass
+            pass

asv_bench/benchmarks/index_object.py

@@ -344,4 +344,4 @@ def setup(self):
         self.mi = MultiIndex.from_product([self.level1, self.level2])
 
     def time_multiindex_with_datetime_level_sliced(self):
-        self.mi[:10].values
+        self.mi[:10].values

asv_bench/benchmarks/io_sql.py

@@ -212,4 +212,4 @@ def setup(self):
         self.df = DataFrame({'float1': randn(10000), 'float2': randn(10000), 'string1': (['foo'] * 10000), 'bool1': ([True] * 10000), 'int1': np.random.randint(0, 100000, size=10000), }, index=self.index)
 
     def time_sql_write_sqlalchemy(self):
-        self.df.to_sql('test1', self.engine, if_exists='replace')
+        self.df.to_sql('test1', self.engine, if_exists='replace')

asv_bench/benchmarks/packers.py

@@ -547,6 +547,31 @@ def remove(self, f):
             pass
 
 
+class packers_write_json_lines(object):
+    goal_time = 0.2
+
+    def setup(self):
+        self.f = '__test__.msg'
+        self.N = 100000
+        self.C = 5
+        self.index = date_range('20000101', periods=self.N, freq='H')
+        self.df = DataFrame(dict([('float{0}'.format(i), randn(self.N)) for i in range(self.C)]), index=self.index)
+        self.remove(self.f)
+        self.df.index = np.arange(self.N)
+
+    def time_packers_write_json_lines(self):
+        self.df.to_json(self.f, orient="records", lines=True)
+
+    def teardown(self):
+        self.remove(self.f)
+
+    def remove(self, f):
+        try:
+            os.remove(self.f)
+        except:
+            pass
+
+
 class packers_write_json_T(object):
     goal_time = 0.2
 

asv_bench/benchmarks/panel_ctor.py

@@ -61,4 +61,4 @@ def setup(self):
             self.data_frames[x] = self.df
 
     def time_panel_from_dict_two_different_indexes(self):
-        Panel.from_dict(self.data_frames)
+        Panel.from_dict(self.data_frames)