SEDF creation using from_df fails if geometry column contains Shapely geometries (instead of strings)

**Describe the bug**
A common workflow I use is to create spatially enabled dataframes (SEDFs) from Shapely geometries in a Pandas DataFrame. However, if the geometry column is left as Shapely geometries when trying to convert to an SEDF, then `from_df` will fail with an error similar to: `TypeError: argument of type 'Point' is not iterable`.

**To Reproduce**
Steps to reproduce the behavior:
```python
from shapely.geometry import Point, LineString
from arcgis.features import GeoAccessor

points = [Point(40, 40), Point(30,30)]
# points = [str(x) for x in points] ## works if this line is included

df = pd.DataFrame({
'id' : ['point1', 'point2'],
'points' : points
})

sedf = pd.DataFrame().spatial.from_df(df, geometry_column = 'points')
```
error:
```python
TypeError: argument of type 'Point' is not iterable
```
**Screenshots**
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**Expected behavior**
Ideally we can just check whether the DataFrame column contains Shapely geometries, and if so, then convert those Shapely geometries to strings before trying to make the SEDF from a geometry column.

**Platform (please complete the following information):**
- OS: Windows
- Browser Chrome
- Python API Version 1.9.1

**Additional context**
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