[FIXED] Iterate through different dataframes and apply a function to each one

Issue

I have 4 different dataframes containing time series data that all have the same structure.

My goal is to take each individual dataframe and pass it through a function I have defined that will group them by datestamp, sum the columns and return a new dataframe with the columns I want. So in total I want 4 new dataframes that have only the data I want.

I just looked through this post: Loop through different dataframes and perform actions using a function but applying this did not change my results.

Here is my code:

I am putting the dataframes in a list so I can iterate through them

dfs = [vds, vds2, vds3, vds4]

This is my function I want to pass each dataframe through:

def VDS_pre(df):
    df = df.groupby(['datestamp','timestamp']).sum().reset_index()
    df = df.rename(columns={'datestamp': 'Date','timestamp':'Time','det_vol': 'VolumeVDS'})
    df = df[['Date','Time','VolumeVDS']]
    
    return df

This is the loop I made to iterate through my dataframe list and pass each one through my function:

for df in dfs:
    df = VDS_pre(df)

However once I go through my loop and go to print out the dataframes, they have not been modified and look like they initially did. Thanks for the help!

Solution

However once I go through my loop and go to print out the dataframes, they have not been modified and look like they initially did.

Yes, this is actually the case. The reason why they have not been modified is:

Assignment to an item in a for item in lst: loop does not have any effect on both the lst and the identifier/variables from which the lst items got their values as it is demonstrated with following code:

v1=1; v2=2; v3=3
lst = [v1,v2,v3]
for item in lst:
    item = 0
print(lst, v1, v2, v3) # gives: [1, 2, 3] 1 2 3

To achieve the result you expect to obtain you can use a list comprehension and the list unpacking feature of Python:

vds,vds2,vds3,vds4=[VDS_pre(df) for df in [vds,vds2,vds3,vds4]]

or following code which is using a list of strings with the identifier/variable names of the dataframes:

sdfs = ['vds', 'vds2', 'vds3', 'vds4']
for sdf in sdfs:
    exec(str(f'{sdf} = VDS_pre(eval(sdf))'))

Now printing vds, vds2, vds3 and vds4 will output the modified dataframes.

Answered By - Claudio