How to add column based on another column value in Pandas dataframe?

Question

How do I take data frame, like the following:

      col1    col2
row0   abc      3
row1   bcd     2.4

And produce a dataframe with new column which value based on col2, is number has dot in it or not, like the following:

      col1    col2    col3
row0   abc      3     No dot
row1   bcd     2.4    Has dot

Any help is appreciated.

IoaTzimas · Accepted Answer · 2020-10-02 12:14:32Z

4

The following should work:

df['col3']=df['col2'].apply(lambda x: 'No dot' if int(x)==x else 'Has dot')

answered Oct 2, 2020 at 12:14

IoaTzimas

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Comments

jezrael · Accepted Answer · 2020-10-02 12:13:34Z

3

Use numpy.where with Series.str.contains, because . is special regex character escape it by \:

df['col3'] = np.where(df['col2'].astype(str).str.contains('\.'), 'Has dot', 'No dot')

Or use regex=False parameter:

df['col3'] = np.where(df['col2'].astype(str).str.contains('.', regex=False), 
                      'Has dot', 'No dot')

print (df)

     col1 col2     col3
row0  abc    3   No dot
row1  bcd  2.4  Has dot

answered Oct 2, 2020 at 12:13

jezrael

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