update values in one dataframe based on another dataframe - Pandas

[iliasb]

Hello everyone

I have a simple problem but for the life of me I can't find any straightforward answer on how to do it. So l have one dataframe with a column email and a column acronym. Another dataframe has the same columns. My goal is now to update the acronym in the first dataframe based on a match between the email in the first and the second dataframe. To visually illustrate:

df1:
Email - Acronym
a@a.com A
b@b.com Nan

df2:
Email - Acronym
a@a.com A
b@b.com B
c@c.com C

My goal is to update df1's Acronym on the second row, based on whats found in df2. I have been delving in the documentation of pandas for a while, to no avail. Any helpers? Thanks!

[iliasb]

Update: as if this forum gave me an epiphany, as soon as I posted the thread, the SQL lightbulb lit up. For the ones interested, the solution:

>>> pd.merge(df1,df2,on='Email',how='left')

Closed!

edit: not closed, it did not do what I expected. Open!

[jefsummers]

Assuming that the email values in one are present in the other

1 2 3 4 5 6 7 8 9

import pandas as pd   d = {'email': ['joe@schmoe.com', 'fred@flintstonetire.com', 'foo@fighter.com'], 'acronym': ['radar', 'laser', 'cia']} df1 = pd.DataFrame(data=d) d2 = {'email': ['joe@schmoe.com', 'fred@flintstonetire.com', 'foo@fighter.com'], 'acronym': ['radar', 'fbi','jupyter']} df2 = pd.DataFrame(data=d2)   df1['acronym'] = df2[df2['email'] == df1['email']]['acronym'] df1

Output:
	email	acronym
0	joe@schmoe.com	radar
1	fred@flintstonetire.com	fbi
2	foo@fighter.com	jupyter