Creating multiple dataframe in faster way with function?

Asked Jul 19 '23 at 13:34

Active Jul 19 '23 at 13:34

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I need to create multiple dataframe (let say 30 dataframe) in faster way rather manually create one-by-one dataframe. anyone has answer or reference links? Thank you in advance

def dvd(y):
    df = port_type.where(port_type['DATE']==y).dropna()
    return df

df_0 = dvd(date_0)
df_1 = dvd(date_1)
df_2 = dvd(date_2)
df_3 = dvd(date_3)
df_4 = dvd(date_4)
df_5 = dvd(date_5)

asked Jul 19 '23 at 13:34

stvlam22

Don't. Use a list or dictionary as container: `dvds = [dvd(date) for date in dates]` or `dvds = {date: dvd(date) for date in dates}` – mozway Jul 19 '23 at 13:37
Ok mozway , i understand so i just create list of dates = [date[0],date[1],date[2]]. Thanks mozway – stvlam22 Jul 19 '23 at 14:06
in this case `dates = date[:3]`, if `date` is already a list, no? – mozway Jul 19 '23 at 14:12
it is already a list, mozway, edit my first comment so no need to create list of dates again. am i correct ? – stvlam22 Jul 19 '23 at 14:17
just like this dvds = [dvd(date) for date in date] – stvlam22 Jul 19 '23 at 14:19
Yes, **but** then you should change the looping variable to avoid conflict: `dvds = [dvd(x) for x in date]`. Or `dvds = list(map(dvd, date))` – mozway Jul 19 '23 at 14:26
1

ok understand, thanks mozway ,it is really very helpful answer. – stvlam22 Jul 19 '23 at 14:29

Creating multiple dataframe in faster way with function?

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