Q: Pivoting a Series in Pandas I have a series that looks like this:
Area        Classification         Samples
88          500m-1bi               34
94          500m-1bi               112
09          500m-1bi               912
            >1bi                   31
81          <1m                    6574
87          100-500m               12
...

I want that the 'Classification' labels become columns and that 'Samples' become the values, so it looks like this:
Area       <1m    100-500m     500-1bi      >1bi  
88                             34
94                             112
09                             912          31
81         6574
87                12
...

I've tried:
df.pivot(columns='Classification', values='Samples')

But when I do that, I get AttributeError: 'Series' object has no attribute 'pivot'.
So I tried to turn it into a Dataframe:
df.to_frame().pivot(columns='Classification', values='Samples')

In this case I get:
KeyError: 'Classification'

Any idea on how to solve it?
** EDIT **
This series was obtained from a groupby function:
df=df.groupby(['Area','Classification']).agg('count').sort_values('Samples')['Samples']


A: A slightly modified df for this example. Added the 10 in Area to fill in the gap:
Area        Classification         Samples
88          500m-1bi               34
94          500m-1bi               112
09          500m-1bi               912
10          >1bi                   31
81          <1m                    6574
87          100-500m               12

You need to set the index then unstack:    
df.set_index(['Area', 'Classification']).unstack()

Output:
                Samples                       
Classification 100-500m 500m-1bi     <1m  >1bi
Area                                          
9                   NaN    912.0     NaN   NaN
10                  NaN      NaN     NaN  31.0
81                  NaN      NaN  6574.0   NaN
87                 12.0      NaN     NaN   NaN
88                  NaN     34.0     NaN   NaN
94                  NaN    112.0     NaN   NaN


A: Just in case you have more columns in your dataframe and you want to unstack just with respect to 'Samples' feature:
copy = df.set_index(['Area', 'Classification']) # Multi-Index
result = copy['Samples'].unstack() # unstack separately

Then you can put everything together (adding untouched columns) by using concat (since you worked with a copy of your df you don't have trouble in dealing with the index now).
df = pd.concat([df, result], axis=1)

'ignore_index' is False by defult so you're done.
