Read certain column in excel to dataframe

there is a solution but csv are not treated the same way excel does.

from documentation, for csv:

usecols : list-like or callable, default None

For example, a valid list-like usecols parameter would be [0, 1, 2] or [‘foo’, ‘bar’, ‘baz’].

for excel:

usecols : int or list, default None

• If None then parse all columns,
• If int then indicates last column to be parsed
• If list of ints then indicates list of column numbers to be parsed
• If string then indicates comma separated list of Excel column letters and column ranges (e.g. “A:E” or “A,C,E:F”). Ranges are inclusive of both sides

so you need to call it like this:

xl_file = pd.read_excel('D:/SnapPython/TestDF.xlsx', sheet_name='Sheet 2', usecols='ForeignKey')

and if you need also 'number':

xl_file = pd.read_excel('D:/SnapPython/TestDF.xlsx', sheet_name='Sheet 2', usecols='number,ForeignKey')

EDIT: you need to put the name of the excel column not the name of the data. the other answer solve this. however you won't need 'B:B', 'B' will do the trick BUT that won't improve the usecols with numbers.

if you can load all the datas in not time maybe the best way to solve this is to parse all columns and then select the desired columns:

xl_file = pd.read_excel('D:/SnapPython/TestDF.xlsx', sheet_name='Sheet 2')['ForeignKey']

You need to pass excel column name, that too in a format of range e.g. colname:colname.

For instance, if the ForeignKey appears in column B of your excel sheet 2, then do -

xl_file = pd.read_excel('D:/SnapPython/TestDF.xlsx', sheet_name='Sheet 2', usecols='B:B') 

Refer to Github issue and prescribed solution for the same.