Closes pandas-dev#22477

Add a check so if the dtype is str is will create
an empty array type object and then pass the values.

Add test for an empty series. To chech that it fills the series
with NaN and not with 'n'.

Also add a test for cases that no string values are given.

Author: Nikoleta-v3

pandas/core/dtypes/cast.py

@@ -1217,11 +1217,14 @@ def construct_1d_arraylike_from_scalar(value, length, dtype):
             dtype = dtype.dtype
 
         # coerce if we have nan for an integer dtype
-        # GH 22858: only cast to float if an index
-        # (passed here as length) is specified
-        if length and is_integer_dtype(dtype) and isna(value):
-            dtype = np.float64
-        subarr = np.empty(length, dtype=dtype)
+        if is_integer_dtype(dtype) and isna(value):
+            dtype = np.dtype('float64')
+        if isinstance(dtype, np.dtype) and dtype.kind in ("U", "S"):
+            subarr = np.empty(length, dtype=object)
+            if not isna(value):
+                value = str(value)
+        else:
+            subarr = np.empty(length, dtype=dtype)
         subarr.fill(value)
 
     return subarr

pandas/core/series.py

@@ -148,7 +148,6 @@ class Series(base.IndexOpsMixin, generic.NDFrame):
 
     def __init__(self, data=None, index=None, dtype=None, name=None,
                  copy=False, fastpath=False):
-
         # we are called internally, so short-circuit
         if fastpath:
 
@@ -4210,7 +4209,6 @@ def _sanitize_array(data, index, dtype=None, copy=False,
     """ sanitize input data to an ndarray, copy if specified, coerce to the
     dtype if specified
     """
-
     if dtype is not None:
         dtype = pandas_dtype(dtype)
 

pandas/tests/series/test_constructors.py

@@ -137,7 +137,7 @@ def test_constructor_no_data_index_order(self):
     def test_constructor_no_data_string_type(self):
         result = pd.Series(index=[1], dtype=str)
         assert result.isna().all()
-    
+
     def test_constructor_single_element_string_type(self):
         result = pd.Series(13, index=[1], dtype=str)
         assert result.values.tolist() == ['13']