CODEWITHSUNDEEP
pythonpandasdictionary
Thodoris P
Thodoris P

Reputation: 563

Get index of rows which column matches certain value

There is a much similar post in the forum POST but i just cant figure out what how to do it in my exaple.

My code now with explanation below

for i in dfuser.appid :
  print i
  d = dfbinary.loc[dfbinary['appid'] == i]
  print d
  glist = dfbinary.columns[dfbinary.loc[i]==1] 
  print glist

I have a dataframe with a list of users with their apps (dfuser) and i have another dataframe with the genres of all the apps(an app may have more than one genre). So i want to see which genre is more popular in each user.

My code is fine except that glist is not finding the appid that i want but finds the appid with index i. For example i=10 , so it will find the app that is at row 11(10).

This is what it prints

   10
   appid  Accounting  Action  Adventure  Animation&Modeling  AudioProduction... 
0   10.0         0.0     1.0        0.0                 0.0              0.0  
[1 rows x 23 columns]
Index([u'Action'], dtype='object')

(And this just happens to be correct)

Upvotes: 1

Views: 392

Answers (1)

simon
simon

Reputation: 2831

Firstly whenever you have a loop with pandas you are probably doing it wrong!

You need to use merge to combine the two dataframes and select only the user and genre columns. It works just like SQL. Then you have a table keyed on user/genre. Now you can groupby("user").count(). No explicit loops.

Upvotes: 1

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