How to build and fill pandas dataframe from for loop? [duplicate]

Question

Here is a simple example of the code I am running, and I would like the results put into a pandas dataframe (unless there is a better option):

for p in game.players.passing():     print p, p.team, p.passing_att, p.passer_rating()  R.Wilson SEA 29 55.7 J.Ryan SEA 1 158.3 A.Rodgers GB 34 55.8 

Using this code:

d = [] for p in game.players.passing():     d = [{'Player': p, 'Team': p.team, 'Passer Rating':         p.passer_rating()}]  pd.DataFrame(d) 

I can get:

    Passer Rating   Player      Team   0 55.8            A.Rodgers   GB 

Which is a 1x3 dataframe, and I understand why it is only one row but I can't figure out how to make it multi-row with the columns in the correct order. Ideally the solution would be able to deal with n number of rows (based on p) and it would be wonderful (although not essential) if the number of columns would be set by the number of stats requested. Any suggestions? Thanks in advance!

Answer 1

The simplest answer is what Paul H said:

d = [] for p in game.players.passing():     d.append(         {             'Player': p,             'Team': p.team,             'Passer Rating':  p.passer_rating()         }     )  pd.DataFrame(d) 

But if you really want to "build and fill a dataframe from a loop", (which, btw, I wouldn't recommend), here's how you'd do it.

d = pd.DataFrame()  for p in game.players.passing():     temp = pd.DataFrame(         {             'Player': p,             'Team': p.team,             'Passer Rating': p.passer_rating()         }     )      d = pd.concat([d, temp]) 

Answer 2

Try this using list comprehension:

import pandas as pd  df = pd.DataFrame(     [p, p.team, p.passing_att, p.passer_rating()] for p in game.players.passing() )