Creating new pandas dataframe from certain columns of existing dataframe

Question

I have read loaded a csv file into a pandas dataframe and want to do some simple manipulations on the dataframe. I can not figure out how to create a new dataframe based on selected columns from my original dataframe. My attempt:

names = ['A','B','C','D'] dataset = pandas.read_csv('file.csv', names=names) new_dataset = dataset['A','D'] 

I would like to create a new dataframe with the columns A and D from the original dataframe.

Answer 1

It is called subset - passed list of columns in []:

dataset = pandas.read_csv('file.csv', names=names)  new_dataset = dataset[['A','D']] 

what is same as:

new_dataset = dataset.loc[:, ['A','D']] 

If need only filtered output add parameter usecols to read_csv:

new_dataset = pandas.read_csv('file.csv', names=names, usecols=['A','D']) 

EDIT:

If use only:

new_dataset = dataset[['A','D']] 

and use some data manipulation, obviously get:

A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

If you modify values in new_dataset later you will find that the modifications do not propagate back to the original data (dataset), and that Pandas does warning.

As pointed EdChum add copy for remove warning:

new_dataset = dataset[['A','D']].copy()