read_excel return empty dataframe when using usecols

In [3]: data = pd.read_excel("A.xlsx")

In [4]: data
Out[4]:
   A  B
0  1  2
1  3  4

In [5]: data1 = pd.read_excel("A.xlsx",usecols=['B'])

In [6]: data1
Out[6]:
Empty DataFrame
Columns: []
Index: []

In [7]: pd.__version__
Out[7]: '0.21.0'

Problem description

Having a excel file name A.xlsx(or A.xls) with column A,B read_excel return empty dataframe if usecols used

[LISHITING]

For me Instead of typing usecols=['B'], try usecols='B'

[chris-b1]

Copying my comment from #20480, welcome any feedback on how this api should work

#18273 is actually two somewhat separate problems and we have a bit of an API tangle here

1. passing a list of Excel column letters doesn’t work (this fixes that)
2. passing a list column names (e.g. column title 'foo' in the spreadsheet) to usecols doesn’t work anymore

Number 2 wasn’t part of the read_excel documented args, but once worked, because this param used to be called parse_cols (#17774), and if you passed something to usecols it would get passed down to the TextParser logic and do the right thing https://github.com/pandas-dev/pandas/blob/1915ffc53ea60494f24d83844bbff00efa392c82/pandas/io/excel.py#L529

Not sure what the solution is, there could be ambiguous cases (column titled'A' in spreadsheet column B), that would be easiest to handle with separate kwargs. Or could just have usecols do everything and warn in cases of ambiguity.