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I'm making analyses of different files with userinformationer (from AD dumps and Excel files), and i need to exchange data between them. And i would like to learn it the Pandas way.

I have been searching the net, and i can not find a way to do it - probably because i do not use the proper terminology

Or do i have to export to a dictionary and then fetch values from there?

... and how do i do that?

or even worse ... do i have to parse the csv file line for line to achieve this goal?

It would make my day to now how to do that

pseudo example code

if df1["Username"] == df2["User"]:
   insert df2["Email"] in df1["Email"]
else:
   do nothing

or practical example:

df1 = pd.DataFrame({
    "UserName":["B-01","B-02","B-03","B-04","B-05"],
    "RealName":["Ann","Bono","Cara","Dylan","Eva"],
    })

df2 = pd.DataFrame({
    "User":["B-02","B-04","B-05"],
    "Email":["mail1@example.org","mail2@example.org","mail3@example.org"]
})

OUTPUT:

   UserName RealName
 0     B-01      Ann
 1     B-02     Bono
 2     B-03     Cara
 3     B-04    Dylan
 4     B-05      Eva

    User              Email
 0  B-02  mail1@example.org
 1  B-04  mail2@example.org
 2  B-05  mail3@example.org,

Result from code

   UserName RealName              Email
 0     B-01      Ann                NaN
 1     B-02     Bono  mail1@example.org
 2     B-03     Cara                NaN
 3     B-04    Dylan  mail2@example.org
 4     B-05      Eva  mail3@example.org
thj001
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  • 3
  • `df1.merge(df2,left_on='UserName',right_on='User',how='left')` – Anurag Dabas Jul 22 '21 at 09:04
  • Brilliant ... That does the trick - THANK YOU I have seen that page, and now i start to see how it applies. Made som changes in the question, to make the output better :) – thj001 Jul 22 '21 at 09:37

0 Answers0