Copy all values in a column to a new column in a pandas dataframe

Question

This is a very basic question, I just can not seem to find an answer.

I have a dataframe like this, called df:

  A     B     C  a.1   b.1   c.1  a.2   b.2   c.2  a.3   b.3   c.3 

Then I extract all the rows from df, where column 'B' has a value of 'b.2'. I assign these results to df_2.

df_2 = df[df['B'] == 'b.2'] 

df_2 becomes:

  A     B     C  a.2   b.2   c.2 

Then, I copy all the values in column 'B' to a new column named 'D'. Causing df_2 to become:

  A     B     C     D  a.2   b.2   c.2   b.2 

When I preform an assignment like this:

df_2['D'] = df_2['B'] 

I get the following warning:

A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead

See the the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy

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I have also tried using .loc when creating df_2 like this:

df_2 = df.loc[df['B'] == 'b.2'] 

However, I still get the warning.

Any help is greatly appreciated.

Answer 1

You can simply assign the B to the new column , Like -

df['D'] = df['B'] 

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Example/Demo -

In [1]: import pandas as pd  In [2]: df = pd.DataFrame([['a.1','b.1','c.1'],['a.2','b.2','c.2'],['a.3','b.3','c.3']],columns=['A','B','C'])  In [3]: df Out[3]:      A    B    C 0  a.1  b.1  c.1 1  a.2  b.2  c.2 2  a.3  b.3  c.3  In [4]: df['D'] = df['B']                  #<---What you want.  In [5]: df Out[5]:      A    B    C    D 0  a.1  b.1  c.1  b.1 1  a.2  b.2  c.2  b.2 2  a.3  b.3  c.3  b.3  In [6]: df.loc[0,'D'] = 'd.1'  In [7]: df Out[7]:      A    B    C    D 0  a.1  b.1  c.1  d.1 1  a.2  b.2  c.2  b.2 2  a.3  b.3  c.3  b.3