Concatenate Pandas DataFrames Generated With A Loop


Answer :

Pandas concat takes a list of dataframes. If you can generate a list of dataframes with your looping function, once you are finished you can concatenate the list together:



data_day_list = []
for i, day in enumerate(list_day):
  data_day = df[df.day==day]
  data_day_list.append(data_day)
final_data_day = pd.concat(data_day_list)


Exhausting a generator is more elegant (if not more efficient) than appending to a list. For example:


def yielder(df, list_day):
    for i, day in enumerate(list_day):
        yield df[df['day'] == day]

final_data_day = pd.concat(list(yielder(df, list_day))


Appending or concatenating pd.DataFrames is slow. You can use a list in the interim and then create the final pd.DataFrame at the end with pd.DataFrame.from_records() e.g.:



interim_list = []
for i,(k,g) in enumerate(df.groupby(['[*name of your date column here*'])):
    if i % 1000 == 0 and i != 0:
        print('iteration: {}'.format(i)) # just tells you where you are in iteration
    # add your "new features" here...
    for v in g.values:
        interim_list.append(v)

# here you want to specify the resulting df's column list...
df_final = pd.DataFrame.from_records(interim_list,columns=['a','list','of','columns'])


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