How Pandas read_html can get only selected columns from entire DataFrame

Question

I'm trying to extract the particular columns from the html page where my html data looks like below.

1) HTML DATA Format

            VM Name           User Name        Image Name                           Network  VCPUS  Memory(GB)  Disk(GB) Tenant     Region      KVM Host Power State                          URL               Created
0      dbsw-powerbi  anokhe@ezy.com           unknown   {u'VLAN181': [u'192.168.57.91']}      4          16       100    APP  DBS-AP-IN  dbs-appkvm03          On  https://compute.ezy.com  2018-08-02T10:30:07Z
1           pciedip  anokhe@ezy.com     dbsVDI-RHEL65   {u'VLAN181': [u'192.168.57.37']}      4          32       200    APP  DBS-AP-IN  dbs-appkvm01          On  https://compute.ezy.com  2018-04-18T06:39:38Z
2  dbs-spbdatasync1  anokhe@ezy.com    dbsVDI-RHEL510  {u'VLAN181': [u'192.168.57.156']}      1           8        50    APP  DBS-AP-IN     dbs-kvm13          On  https://compute.ezy.com  2018-04-05T09:51:29Z
3      dbsw-russian  anokhe@ezy.com  dbsVDI-WIN764-V1  {u'VLAN181': [u'192.168.57.216']}      1           4       100    APP  DBS-AP-IN  dbs-appkvm01          On  https://compute.ezy.com  2018-04-02T06:25:25Z
4   dbs-spbdatasync  anokhe@ezy.com    dbsVDI-RHEL510  {u'VLAN181': [u'192.168.57.233']}      1           8        50    APP  DBS-AP-IN     dbs-kvm13          On  https://compute.ezy.com  2018-04-02T05:03:03Z

I'm simply trying pandas read_html to get the DataFrame but unable to get the understanding to get the particular columns from the DataFrame. I need to selected columns ['VM Name', 'User Name', 'Network', 'Region'] out of the 13 column.

2) code snippet

from __future__ import print_function
from signal import signal, SIGPIPE, SIG_DFL
signal(SIGPIPE,SIG_DFL)
import pandas as pd
##### Python pandas, widen output display to see more columns. ####
pd.set_option('display.height', None)
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.width', None)
pd.set_option('expand_frame_repr', True)

# print(pd.read_excel('ssd.xlsx'))
# Data = pd.read_html('http://openstacksearch/vm_list.html', header=0, flavor='bs4', index_col=['VM Name', 'User Name', 'Network', 'Region'])
Data = pd.read_html('http://openstacksearch/vm_list.html', header=0, flavor='bs4')
print(Data[0].head())

Answer 1

to select a subset of columns you could use

Data = pd.read_html('http://openstacksearch/vm_list.html', header=0, flavor='bs4')
Data = Data[['VM Name', 'User Name', 'Network', 'Region']]

Answer 2

I got solution while selecting the DataFrame from the processed read_html and then choosing the desired columns with multi-index based approach. Thanks to the Adrew for driving ideas around this..

So, code looks like below ... may be helpful for someone

import pandas as pd
##### Python pandas, widen output display to see more columns. ####
pd.set_option('display.height', None)
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.width', None)
pd.set_option('expand_frame_repr', True)
###### Data Extraction ##################
'''
pd.read_html returns you a list with one element and that 
element is the pandas dataframe, i.e.
Data = pd.read_html('url') will produce a list
Data[0]  Will return a pandas DataFrame
'''
Data = pd.read_html('http://openstacksearch/vm_list.html', header=0, flavor='bs4')[0]
Data1 = Data[['VM Name', 'User Name', 'Network', 'Region']]
print(Data1)