I have 238 dataframes that look like this:

I would like to have a for loop which would drop all of the rows where before and after values are the same (leave only those rows where they are different). Example

Right now, I just have 238 of these: onlydiffs_dfi = dfi[dfi['before'] != dfi['after']]

Which is obviously not great, and can be accomplished with a for loop but I but figure out how to write it. Please help!

CodePudding user response：

Make a list containing the dataframes and iterate:

df_list =[*list of dfs]

for df in df_list:
    new_df = df[df['before'] != df['after']]

Then you can append it to a new list... or whatever you want to do with it If all your dfs are in a dictionary, you iterate as well just index into it:

df_dict = {key0:df0,key1:df1 ....}
for key,df in df_dict.items():
   new_df = df[df['before'] != df['after']]

or even less pythonic:

for key in df_dict.keys():
    df = df_dict[key]
    new_df = df[df['before'] != df['after']]

You can even convert you dictionary values to a list and use the first method:

df_list = list(df_dict.values())