Python Pandas daily average

Question

I'm having problems getting the daily average in a Pandas database. I've checked here Calculating daily average from irregular time series using pandas and it doesn't help. csv files look like this: ``` Date/Time,Value 12/08/13 12:00:01,5.553 12/08/13 12:30:01,2.604 12/08/13 13:00:01,2.604 12/08/13 13:30:01,2.604 12/08/13 14:00:01,2.101 12/08/13 14:30:01,2.666 ``` and so on. My code looks like this: ``` # Import iButton temperatures flistloc = '../data/iButtons/Readings/edit' flist = os.listdir(flistloc) # Create empty dictionary to store db for each file pdib = {} for file in flist: file = os.path.join(flistloc,file) # Calls function to return only name fname,_,_,_= namer(file) # Read each file to db pdib[fname] = pd.read_csv(file, parse_dates=0, dayfirst=True, index_col=0) pdibkeys = sorted(pdib.keys()) # # Calculate daily average for each iButton for name in pdibkeys: pdib[name]['daily'] = pdib[name].resample('D', how = 'mean') ``` The database seems ok but the averaging doesn't wo…

Accepted Answer

The question is somewhat old, but i want to contribute anyway since i had to deal with this over and over again (and i think it's not really pythonic...).

The best solution, i have come up so far is to use the original index to create a new dataframe with mostly NA and fill it up at the end.

```
davg = df.resample('D', how='mean')
davg_NA = davg.loc[df.index]
davg_daily = davg_NA.fillna(method='ffill')
```

One can even cramp this in one line

```
df.resample('D', how='mean').loc[df.index].fillna(method='ffill')
```

Python Pandas daily average

Solution

Problem