Using: Python 2.7 and Pandas 0.11.0 on Mac OSX Lion
I'm trying to create an empty DataFrame and then populate it from another dataframe, based on a for loop.
I have found that when I construct the DataFrame and then use the for loop as follows:
data = pd.DataFrame()
for item in cols_to_keep:
if item not in dummies:
data = data.join(df[item])
Results in an empty DataFrame, but with the headers of the appropriate columns to be added from the other DataFrame.
That's because you are using join incorrectly.
You can use a list comprehension to restrict the DataFrame to the columns you want:
df[[col for col in cols_to_keep if col not in dummies]]
What about just creating a new frame based off of the columns you know you want to keep, instead of creating an empty one first?
import pandas as pd
import numpy as np
df = pd.DataFrame({'a':np.random.randn(5),
'b':np.random.randn(5),
'c':np.random.randn(5),
'd':np.random.randn(5)})
cols_to_keep = ['a', 'c', 'd']
dummies = ['d']
not_dummies = [x for x in cols_to_keep if x not in dummies]
data = df[not_dummies]
data
a c
0 2.288460 0.698057
1 0.097110 -0.110896
2 1.075598 -0.632659
3 -0.120013 -2.185709
4 -0.099343 1.627839
