Improve the error message when usecols cannot match all columns

[AaronCritchley]

Code Sample

import pandas as pd
# Where example.csv is:
# column1,column2
# 1, 2

pd.read_csv('example.csv', usecols=['column1', 'column2', ' column3'])

Problem description

The error when all of the columns provided in usecols are not found isn't currently very useful. I think it would be much better if it detailed which fields it could not find - this is really useful when you're reading a large file with many required columns.

Current Output

MYPATH\Local\Continuum\Anaconda3\lib\site-packages\pandas\io\parsers.py in __init__(self, src, **kwds)
   1432 
   1433             if len(self.names) < len(self.usecols):
-> 1434                 raise ValueError("Usecols do not match names.")
   1435 
   1436         self._set_noconvert_columns()

ValueError: Usecols do not match names.

Expected Output

A ValueError with the fields that are missing, something like:
ValueError: Usecols do not match columns in file, columns expected but not found: ['column3']

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.6.0.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.19.2
nose: 1.3.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.11.3
scipy: 0.18.1
statsmodels: 0.6.1
xarray: None
IPython: 5.1.0
sphinx: 1.5.1
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: 1.2.0
tables: 3.2.2
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: 4.5.3
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.1.5
pymysql: None
psycopg2: None
jinja2: 2.9.4
boto: 2.45.0
pandas_datareader: 0.3.0.post

[AaronCritchley]

If there are no objections to this, I'm happy to pick this up and implement.

Also happy to take on any suggestions from people on a different error message.

[gfyoung]

@AaronCritchley : Go right ahead! I would also suggest, if possible, that you upgrade your pandas installation too. We're at 0.20.3 right now, though your issue still persists on master.

[AaronCritchley]

Great, will take this on over the next few days, thanks!