python - 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

---

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']

---

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