In pandas I have created a dataframe from importing from CSV.
data = pd.read_csv('pathToCSV', index_col=[0],usecols=[0,2,3],names=['Date','High','Low'])
Output looks like this-
2009.09.18 112 111
2009.09.19 114 222
Now what if I want to calculate an average of the two columns, row by row, and then add the value as a new column? What I did was
average = (data[1]+data[2])/2
Then
data.join(average)
But I get an error! I am doing this correct?
I think you're just looking for the mean function, which you want to apply row-wise (axis = 1) to the columns High and Low:
# starting with frame:
>>> data
Date High Low
0 2009.09.18 112 111
1 2009.09.19 114 222
# Use:
data['row_average'] = data[['High','Low']].mean(axis=1)
# and you end up with the frame:
>>> data
Date High Low row_average
0 2009.09.18 112 111 111.5
1 2009.09.19 114 222 168.0
While sacul is absolutely correct, you may consider the following solution as well.
def avg(x,y):
return (x+y)/2
df['row_avg'] = df[['High','Low']].apply(lambda x:avg(*x),axis=1)
The advantage of this approach is you can define any function and then apply to DataFrame rows.
