Description
Code Sample, a copy-pastable example if possible
import pandas as pd
empty_frame=pd.read_excel('pandas/tests/io/data/test1.xlsx', parse_cols=['A','B','C'])
print(empty_frame)
useful_frame=pd.read_csv('pandas/tests/io/data/test1.csv', usecols=['A','B','C'])
print(useful_frame)
Problem description
based on making the argument naming consistent for various read_*
functions (#4988), the functionality should also be consistent as well. ideally, keeping the read_excel ability to parse a string as well. a continuation of #16488.
Expected Output
expected output to using parse_col=
/usecols=['A','B','C']
is a dataFrame containing the data in excel columns A, B, & C.
Output of pd.show_versions()
pandas: 0.19.2
nose: None
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.11.3
scipy: 0.18.1
statsmodels: None
xarray: None
IPython: 5.1.0
sphinx: 1.5.1
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.0
tables: 3.3.0
numexpr: 2.6.1
matplotlib: 2.0.0
openpyxl: 2.4.1
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.2
bs4: 4.3.2
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.1.5
pymysql: 0.7.9.None
psycopg2: None
jinja2: 2.9.6
boto: None
pandas_datareader: None