Convert frame pandas in python

Question

I receive the output from my pandas datareader as the following:

       Date        AAPL         ACN
0 2016-11-21  111.730003  119.680000
1 2016-11-22  111.800003  119.480003
2 2016-11-23  111.230003  119.820000
3 2016-11-25  111.790001  120.739998
4 2016-11-28  111.570000  120.760002

What I that the frame looks like:

       Date   Minor   Adj Close
0 2016-11-21  AAPL    111.730003  
1 2016-11-22  AAPL    111.800003  
2 2016-11-23  AAPL    111.230003  
3 2016-11-25  AAPL    111.790001  
4 2016-11-28  AAPL    111.570000  
0 2016-11-21  ACN     119.680000
1 2016-11-22  ACN     119.480003
2 2016-11-23  ACN     119.820000
3 2016-11-25  ACN     120.739998
4 2016-11-28  ACN     120.760002

How can I converte my code that I receive the output mentioned above? The code looks like:

import pandas_datareader.data as pdr

DataLevels = pdr.DataReader(['ACN','AAPL'], 'yahoo', '2016-11-19', '2016-12-1')
DataLevels = DataLevels['Adj Close'].reset_index()
DataLevels.rename(columns={'minor': ['ACN','AAPL'], 'Adj Close': 'Adj Close'}, inplace=True)
print(DataLevels)

@MaxU I receive the following error message:SyntaxError: invalid character in identifier — MCM
– MCM, Commented Dec 11, 2016 at 21:50

Nickil Maveli · Accepted Answer · 2016-12-11 21:48:20Z

4

Use melt to reshape the DF from wide to long format:

pd.melt(df, id_vars=['Date'], value_name='Adj Close', var_name='Minor')

answered Dec 11, 2016 at 21:48

Nickil Maveli

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11 Comments

MaxU - stand with Ukraine Over a year ago

This solution is much better ;)

Nickil Maveli Over a year ago

@MaxU, Thanks for that.

MaxU - stand with Ukraine Over a year ago

@MCM, you can simply replace df with your "DataLevels": pd.melt(DataLevels['Adj Close'].reset_index(), id_vars='Date', value_name='Adj Close', var_name='Minor')

Nickil Maveli Over a year ago

@MCM, If you want to rename the column after melting, you could then do -

pd.melt(DataLevels['Adj Close'].reset_index(), id_vars=['Date'], value_name='Adj Close', var_name='Minor').rename(columns={'Minor': 'Ticker'})

. Since you haven't accepted answers before, you may want to do that so that it indicates to the wider community that this solution has solved your problem successfully.

MCM Over a year ago

@NickilMaveli Thanks a lot. I just figured it faster out as I could delete my post :). I think the post can be closed.

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