Pd.series.map performance

pandas/core/series.py

@@ -354,15 +354,18 @@ def _init_dict(self, data, index=None, dtype=None):
         # Looking for NaN in dict doesn't work ({np.nan : 1}[float('nan')]
         # raises KeyError), so we iterate the entire dict, and align
         if data:
-            keys, values = zip(*data.items())
-            values = list(values)
+            # GH:34717
+            # Using the below way for generating keys and values
+            # increasing the performance by 50%, instead of zip
+            keys = tuple(data.keys())
+            values = list(data.values())  # Generating list of values- faster way
         elif index is not None:
             # fastpath for Series(data=None). Just use broadcasting a scalar
             # instead of reindexing.
             values = na_value_for_dtype(dtype)
             keys = index
         else:
-            keys, values = [], []
+            keys, values = tuple([]), []
 
         # Input is now list-like, so rely on "standard" construction: