How to add a new column to a hierarchical dataframe grouped by groupby

[glez_b]

The following script try to calculate the resulting average of the direction and magnitude of the wind well as daily averages of Temperature, Moisture and Sum of Precipitation. My monthly dataframe has the following column:

data

Fecha            Hora    DirViento  MagViento Temperatura  Humedad  PreciAcu    
0   2011/07/01  00:00        318        6.6        21.22      100       1.7    
1   2011/07/01  00:15        342        5.5        21.20      100       1.7    
2   2011/07/01  00:30        329        6.6        21.15      100       4.8    
3   2011/07/01  00:45        279        7.5        21.11      100       4.2   
4   2011/07/01  01:00        318        6.0        21.16      100       2.5  

The first thing I do is convert to radians the DirViento column

dir_rad=[]
for i in range(0, len(data['DirViento'])):
    dir_rad.append(data['DirViento'][i]*(pi/180.0))
data['DirViento']=around(dir_rad,1) 

Now get the columns of the components: u and v wind and add to data

Uviento=[]
Vviento=[]
for i in range(0,len(data['MagViento'])):
    Uviento.append(data['MagViento'][i]*sin(data[DirViento][i]))
    Vviento.append(data['MagViento'][i]*cos(data[DirViento][i]))
data['u']=around(Uviento,1)   
data['v']=around(Vviento,1)  


data
Data columns:
Fecha           51  non-null values
Hora            51  non-null values
DirViento       51  non-null values
MagViento       51  non-null values
Temperatura     51  non-null values
Humedad         51  non-null values
PreciAcu        51  non-null values
u               51  non-null values
v               51  non-null values
dtypes: float64(6), int64(2), object(2)

Now using "pandas" and we indexed the dataframe and grouped

index=data.set_index(['Fecha','Hora'],inplace=True)

grouped = index.groupby(level=0)

for example

data['u']

Fecha       Hora 
2011/07/01  00:00    -4.4
            00:15    -1.7
            00:30    -3.4
            00:45    -7.4
            01:00    -4.0
2011/07/02  00:00    -4.5
            00:15    -4.2
            00:30    -7.6
            00:45    -3.8
            01:00    -2.0
2011/07/03  00:00    -6.3
            00:15   -13.7
            00:30    -0.3
            00:45    -2.5
            01:00    -2.7

Now get resultant wind direction for each day

grouped.apply(lambda x: ((scipy.arctan2(mean(x['uu']),mean(x['vv'])))/(pi/180.0)))

 Fecha
 2011/07/01   -55.495677
 2011/07/02   -39.176537
 2011/07/03   -51.416339

The result obtained, I need to apply the following conditions

for i in grouped.apply(lambda x: ((scipy.arctan2(mean(x['uu']),mean(x['vv'])))/(pi/180.0))):
    if i < 180:
        i=i+180
    else:
        if i > 180:
            i=i-180
        else:
            i=i
    print i

124.504323033
140.823463279
128.5836605

Why not display the column for dates? how this is achieved?
How to include the above result to a column that is called DirRes? Once the DirRes column was created, how add it to the following dictionary:

stat_cea = grouped.agg({'MagRes':np.mean,'DirRes':np.mean,'Temperatura':np.mean,'Humedad':np.mean,'PreciAcu':np.sum})

stat_cea

Fecha        DirRes     Humedad          PreciAcu  Temperatura

2011/07/01             100.000000          30.4      21.367059              
2011/07/02             99.823529           18.0      21.841765    
2011/07/03             99.823529            4.0      21.347059

Your help is vital