Change time windows in pivot table

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Hello :slight_smile: I have the following code and wonder how to tell python to export a pivot table with the time windows 0.5 to 1, 1 to 1.5, 1.5 to 2, 2 to 2.5 (so in 0.5 steps). At the moment the table labels 0.5 to 1 as Sec 1, 1 to 2 as Sec 2 and 2.5 to 3 to Sec 3. So it does 1.0 steps.

    power_cspre=power_cspre.crop(tmin=0.5, tmax=2.5,fmin=8, fmax=12, include_tmax=True)
    #power_cspre=power_cspre[0]
    alpha=np.mean(power_cspre.data, axis=1) #average electrode
    alpha=np.mean(alpha.data, axis=0) #average electrode
    freqs=np.mean(alpha.data, axis=0) #average frequencies
    timeS=power_cspre.times[0:]
    data = np.dstack((timeS,freqs))
    data = data.reshape(501, 2)
    index=power_cspre.times[0:]
    columns=['time','value']
    
    df_data_CSplusR = pd.DataFrame(data=data ,    # values
                              index=index,
                              columns=columns)  # 1st row as the column names
    df_data_CSplusR['pptID'] = subject 
    df_data_CSplusR['condition'] = 'CPR'
    df_data_CSplusR['shock'] = 'P'
    df_data_CSplusR['memory'] = 'R'
    
    baseline_CPR = baseline_CPR.append(pd.DataFrame(data = df_data_CSplusR), ignore_index=True)
    
    del power_cspre, alpha,freqs, df_data_CSplusR

**#Averages values to 1 value each sec**
**    baseline_CPR=baseline_CPR[baseline_CPR['time']!=0]**
**    baseline_CPR['Sec']= baseline_CPR['time'].apply(np.ceil)**
**    baseline_CPR_summary=pd.pivot_table(baseline_CPR,values='value',index=['pptID'],columns=['Sec'],aggfunc=np.mean)**

It probably has something to to with the definition of the variable “Sec”, I guess
Thank you :slight_smile:
Franzi