On the line that's failing, your code is this:
combinedX=combinedX+dframe['tf']
which uses combinedX on both sides of the assignment statement - note that
Python is reporting a 'MemoryError", which may be happening due to this
"double use" (maybe). What happens if you create a new dataframe, like
this:
newX = combinedX + dframe['tf']
Regardless, it looks like you are doing a dataframe merge. Jake V's book
has an excellent section on it here:
http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.07-Merge-and-Join.ipynb
- this should take about 20 minutes to read, and may be of use to you.
Paul.
On 28 June 2017 at 12:19, Bhaskar Dhariyal <dhariyalbhas...@gmail.com>
wrote:
> On Wednesday, 28 June 2017 14:43:48 UTC+5:30, Paul Barry wrote:
> > This should do it:
> >
> > >>> import pandas as pd
> > >>>
> > >>> df1 = pd.DataFrame(['bhaskar', 'Rohit'], columns=['first_name'])
> > >>> df1
> > first_name
> > 0 bhaskar
> > 1 Rohit
> > >>> df2 = pd.DataFrame(['dhariyal', 'Gavval'], columns=['last_name'])
> > >>> df2
> > last_name
> > 0 dhariyal
> > 1 Gavval
> > >>> df = pd.DataFrame()
> > >>> df['name'] = df1['first_name'] + ' ' + df2['last_name']
> > >>> df
> > name
> > 0 bhaskar dhariyal
> > 1 Rohit Gavval
> > >>>
> >
> > Again, I draw your attention to Jake VanderPlas's excellent book, which
> is
> > available for free on the web. All of these kind of data manipulations
> are
> > covered there: https://github.com/jakevdp/PythonDataScienceHandbook -
> the
> > hard copy is worth owning too (if you plan to do a lot of work using
> > numpy/pandas).
> >
> > I'd also recommend the upcoming 2nd edition of Wes McKinney's "Python for
> > Data Analysis" book - I've just finished tech reviewing it for O'Reilly,
> > and it is very good, too - highly recommended.
> >
> > Regards.
> >
> > Paul.
> >
> > On 28 June 2017 at 07:11, Bhaskar Dhariyal <dhariyalbhas...@gmail.com>
> > wrote:
> >
> > > Hi!
> > >
> > > I have 2 dataframe i.e. df1['first_name'] and df2['last_name']. I want
> to
> > > make it as df['name']. How to do it using pandas dataframe.
> > >
> > > first_name
> > > ----------
> > > bhaskar
> > > Rohit
> > >
> > >
> > > last_name
> > > -----------
> > > dhariyal
> > > Gavval
> > >
> > > should appear as
> > >
> > > name
> > > ----------
> > > bhaskar dhariyal
> > > Rohit Gavval
> > >
> > >
> > >
> > > Thanks
> > > --
> > > https://mail.python.org/mailman/listinfo/python-list
> > >
> >
> >
> >
> > --
> > Paul Barry, t: @barrypj <https://twitter.com/barrypj> - w:
> > http://paulbarry.itcarlow.ie - e: paul.ba...@itcarlow.ie
> > Lecturer, Computer Networking: Institute of Technology, Carlow, Ireland.
>
> https://drive.google.com/open?id=0Bw2Avni0DUa3aFJKdC1Xd2trM2c
> link to code
> --
> https://mail.python.org/mailman/listinfo/python-list
>
--
Paul Barry, t: @barrypj <https://twitter.com/barrypj> - w:
http://paulbarry.itcarlow.ie - e: paul.ba...@itcarlow.ie
Lecturer, Computer Networking: Institute of Technology, Carlow, Ireland.
--
https://mail.python.org/mailman/listinfo/python-list
