replace row values in a single column pandas - python-3.x

Question

I keep getting warning "A value is trying to be set on a copy of a slice from a DataFrame".
How could I fix it? Any alternative
//check for NAN
//capitalise first letter
//assign 'Male' for 'm',
//assign 'Female for 'f'
myDataFrame.to_csv('new_H.csv')
genderList = myDataFrame.loc[:,"Gender"] //extract Gender column
for i in range(0, len(genderList)):
if type(genderList[i]) == float: #check for empty spaces
genderList[i] = 'NAN'
elif genderList[i].startswith('f'):
genderList[i] = 'Female'
elif genderList[i].startswith('m'):
genderList[i] = 'Male'

Answer 1

for row in myDataFrame.itertuples():
if type(row["Gender"]) == float:
row["Gender"] = 'NAN'
elif row["Gender"].startswith('f'):
row["Gender"] = 'Female'
elif row["Gender"].startswith('m'):
row["Gender"] = 'Male'
The line genderList = myDataFrame.loc[:,"Gender"] cause warning since you are assigning a piece of your data frame, which could result a copy so update may not be applied to original dataframe. In code above, I used itertuples method which is a more "correct" way to iterate through rows in pandas. If you want to perform an action on a specific row, you do need to create a slice of it first - you just update the value of this column in every row.
From what I see, you goal is to replace values on Gender based on previous values. In that case I recommend to check pandas's replace method which is made for that exact reason together with filter. But, since your filter is quite simple, you can do the following:
myDataFrame[myDataFrame["Gender"].str.contains('^f')] = "Female"
To update all female. I used slicing of dataframe (myDataFrame[...]) and the condition is myDataFrame["Gender"].str.contains('^f').