Calcule la media en el marco de datos dada una frecuencia usando pandas

Tengo un marco de datos donde los valores se miden cada 30 minutos, como se muestra a continuación:

2015-01-01 00:00:00   94.50
2015-01-01 00:30:00   78.75
2015-01-01 01:00:00   85.87
2015-01-01 01:30:00   85.88
2015-01-01 02:00:00   84.75
2015-01-01 02:30:00   87.50

Entonces, cada día tiene 48 valores. La primera columna es el índice de tiempo creado mediante:

date= pd.date_range( '1/1/2015', periods=len(series),freq='30min' )
series=series.values.reshape(-1,1)
df=pd.DataFrame(series, index=date)

Lo que me gustaría hacer es obtener la media para cada hora del día y día de la semana. Algo como esto:

Mi idea inicial era agrupar por día de la semana y frecuencia (30 min.) De la siguiente manera:

df= df.groupby([ df.index.weekday,df.index.freq])
print(df.describe())


       count    mean std     min     25%     50%     75%   
0 2015-01-05 00:30:00   1.0   93.75 NaN   93.75   93.75   93.75   93.75   
  2015-01-05 01:00:00   1.0  110.25 NaN  110.25  110.25  110.25  110.25   
  2015-01-05 01:30:00   1.0  110.88 NaN  110.88  110.88  110.88  110.88   
  2015-01-05 02:00:00   1.0   90.12 NaN   90.12   90.12   90.12   90.12   
  2015-01-05 02:30:00   1.0   91.50 NaN   91.50   91.50   91.50   91.50   
  2015-01-05 03:00:00   1.0   94.13 NaN   94.13   94.13   94.13   94.13   
  2015-01-05 03:30:00   1.0   90.62 NaN   90.62   90.62   90.62   90.62   
  2015-01-05 04:00:00   1.0   91.88 NaN   91.88   91.88   91.88   91.88   
  2015-01-05 04:30:00   1.0   92.50 NaN   92.50   92.50   92.50   92.50   
  2015-01-05 05:00:00   1.0   98.12 NaN   98.12   98.12   98.12   98.12   
  2015-01-05 05:30:00   1.0  105.75 NaN  105.75  105.75  105.75  105.75   
  2015-01-05 06:00:00   1.0  100.50 NaN  100.50  100.50  100.50  100.50   
  2015-01-05 06:30:00   1.0   82.25 NaN   82.25   82.25   82.25   82.25   
  2015-01-05 07:00:00   1.0   81.75 NaN   81.75   81.75   81.75   81.75   
  2015-01-05 07:30:00   1.0   90.50 NaN   90.50   90.50   90.50   90.50   
  2015-01-05 08:00:00   1.0   89.50 NaN   89.50   89.50   89.50   89.50   
  2015-01-05 08:30:00   1.0   89.63 NaN   89.63   89.63   89.63   89.63   
  2015-01-05 09:00:00   1.0   84.62 NaN   84.62   84.62   84.62   84.62   
  2015-01-05 09:30:00   1.0   86.63 NaN   86.63   86.63   86.63   86.63   
  2015-01-05 10:00:00   1.0   96.12 NaN   96.12   96.12   96.12   96.12   
  2015-01-05 10:30:00   1.0  104.13 NaN  104.13  104.13  104.13  104.13   
  2015-01-05 11:00:00   1.0  101.12 NaN  101.12  101.12  101.12  101.12   
  2015-01-05 11:30:00   1.0   85.88 NaN   85.88   85.88   85.88   85.88   
  2015-01-05 12:00:00   1.0   77.12 NaN   77.12   77.12   77.12   77.12   
  2015-01-05 12:30:00   1.0   78.88 NaN   78.88   78.88   78.88   78.88   
  2015-01-05 13:00:00   1.0   76.62 NaN   76.62   76.62   76.62   76.62   
  2015-01-05 13:30:00   1.0   78.63 NaN   78.63   78.63   78.63   78.63   
  2015-01-05 14:00:00   1.0   85.37 NaN   85.37   85.37   85.37   85.37   
  2015-01-05 14:30:00   1.0  103.63 NaN  103.63  103.63  103.63  103.63   
  2015-01-05 15:00:00   1.0  112.87 NaN  112.87  112.87  112.87  112.87   
...                     ...     ...  ..     ...     ...     ...     ...   
6 2016-10-02 09:30:00   1.0   84.75 NaN   84.75   84.75   84.75   84.75   
  2016-10-02 10:00:00   1.0   60.49 NaN   60.49   60.49   60.49   60.49   
  2016-10-02 10:30:00   1.0   76.25 NaN   76.25   76.25   76.25   76.25   
  2016-10-02 11:00:00   1.0   68.13 NaN   68.13   68.13   68.13   68.13   
  2016-10-02 11:30:00   1.0   54.15 NaN   54.15   54.15   54.15   54.15   
  2016-10-02 12:00:00   1.0   79.91 NaN   79.91   79.91   79.91   79.91   
  2016-10-02 12:30:00   1.0   72.79 NaN   72.79   72.79   72.79   72.79   
  2016-10-02 13:00:00   1.0   77.49 NaN   77.49   77.49   77.49   77.49   
  2016-10-02 13:30:00   1.0   77.65 NaN   77.65   77.65   77.65   77.65   
  2016-10-02 14:00:00   1.0   70.44 NaN   70.44   70.44   70.44   70.44   
  2016-10-02 14:30:00   1.0   82.47 NaN   82.47   82.47   82.47   82.47   
  2016-10-02 15:00:00   1.0   41.53 NaN   41.53   41.53   41.53   41.53   
  2016-10-02 15:30:00   1.0   66.65 NaN   66.65   66.65   66.65   66.65   
  2016-10-02 16:00:00   1.0   55.23 NaN   55.23   55.23   55.23   55.23   
  2016-10-02 16:30:00   1.0   59.45 NaN   59.45   59.45   59.45   59.45   
  2016-10-02 17:00:00   1.0   79.92 NaN   79.92   79.92   79.92   79.92   
  2016-10-02 17:30:00   1.0   58.48 NaN   58.48   58.48   58.48   58.48   
  2016-10-02 18:00:00   1.0   92.56 NaN   92.56   92.56   92.56   92.56   
  2016-10-02 18:30:00   1.0   86.92 NaN   86.92   86.92   86.92   86.92   
  2016-10-02 19:00:00   1.0   88.61 NaN   88.61   88.61   88.61   88.61   
  2016-10-02 19:30:00   1.0   99.21 NaN   99.21   99.21   99.21   99.21   
  2016-10-02 20:00:00   1.0   81.02 NaN   81.02   81.02   81.02   81.02   
  2016-10-02 20:30:00   1.0   84.83 NaN   84.83   84.83   84.83   84.83   
  2016-10-02 21:00:00   1.0   59.29 NaN   59.29   59.29   59.29   59.29   
  2016-10-02 21:30:00   1.0   95.99 NaN   95.99   95.99   95.99   95.99   
  2016-10-02 22:00:00   1.0   76.95 NaN   76.95   76.95   76.95   76.95   
  2016-10-02 22:30:00   1.0  112.49 NaN  112.49  112.49  112.49  112.49   
  2016-10-02 23:00:00   1.0   88.85 NaN   88.85   88.85   88.85   88.85   
  2016-10-02 23:30:00   1.0  122.40 NaN  122.40  122.40  122.40  122.40   
  2016-10-03 00:00:00   1.0   82.84 NaN   82.84   82.84   82.84   82.84 

Al mirar esto, puede verlo solo agrupar por día de la semana. Así que esta no es la forma correcta de agrupar para calcular la media como quería.