Obtaining Data from a dataframe at desired timestep

Question

I have a long timeseries with a 15 minute time step. I want to obtain timeseries at 3H time step from the existing series. I have tried different methods including the resample method. But the resample method does not work for me. I decided to run a loop to obtain these value. I used the following piece of code. But I am not sure why it is not working as I expect it to work. I cannot use the resample.mean() since I don't want to miss any actual peak values e.g. that of a flood wave. I want to keep the original data as it is.

station_number = []
timestamp = []
water_level = []
discharge = []
for i in df3.index:
    station_number.append(df3['Station ID'][i])
    timestamp.append(df3['Timestamp'][i])
    water_level.append(df3['Water Level (m)'][i])
    discharge.append(df3['Discharge (m^3/s)'][i])
    i = i + 12
    pass 
df5 = pd.DataFrame(station_number, columns=['Station ID'],)
df5['Timestamp']= timestamp
df5['Water Level (m)']= water_level
df5['Discharge (m^3/s)']= discharge
df5

Running this code returns me the same dateframe. My logic is that the value of i updates by 12 steps and pick up the corresponding values from the dataset. Please guide if I am doing something wrong.