<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def props_to_DataFrame(regionprops):
 r""" Returns a Pandas DataFrame containing all the scalar metrics for each region, such as volume, sphericity, and so on, calculated by ``regionprops_3D``. Parameters regionprops : list This is a list of properties for each region that is computed by ``regionprops_3D``. Because ``regionprops_3D`` returns data in the same ``list`` format as the ``regionprops`` function in **Skimage** you can pass in either. Returns ------- DataFrame : Pandas DataFrame A Pandas DataFrame with each region corresponding to a row and each column corresponding to a key metric. All the values for a given property (e.g. 'sphericity') can be obtained as ``val = df['sphericity']``. Conversely, all the key metrics for a given region can be found with ``df.iloc[1]``. See Also -------- props_to_image regionprops_3d """

    # Parse the regionprops list and pull out all props with scalar values
    metrics = []
    reg = regionprops[0]
    for item in reg.__dir__():
        if not item.startswith('_'):
            try:
                if sp.shape(getattr(reg, item)) == ():
                    metrics.append(item)
            except (TypeError, NotImplementedError, AttributeError):
                pass
    # Create a dictionary of all metrics that are simple scalar propertie
    d = {}
    for k in metrics:
        try:
            d[k] = sp.array([r[k] for r in regionprops])
        except ValueError:
            print('Error encountered evaluating ' + k + ' so skipping it')
    # Create pandas data frame an return
    df = DataFrame(d)
    return df