Adding overrides for default values

Author: kushagr96

pandas/core/arrays/sparse/accessor.py

@@ -313,7 +313,18 @@ def from_spmatrix(cls, data, index=None, columns=None) -> DataFrame:
         indices = data.indices
         indptr = data.indptr
         array_data = data.data
-        dtype = SparseDtype(array_data.dtype)
+
+        default_fill_value_override = None
+
+        # Default values for float type is NaN. Hence, in order to create a
+        # Sparse matrix of type float, we need override this default value as 0.0.
+        if array_data.dtype.kind in "f":
+            default_fill_value_override = 0.0
+        # Similarly, default value needs to be overridden for complex type arrays.
+        elif array_data.dtype.kind in "c":
+            default_fill_value_override = 0.0 + 0.0j
+
+        dtype = SparseDtype(array_data.dtype, fill_value=default_fill_value_override)
         arrays = []
         for i in range(n_columns):
             sl = slice(indptr[i], indptr[i + 1])