Python: Find String In Multiple Columns And Return It In New Column

Hi I have an excel data with multiple columns and i need to fined specific word and return it in new column the table look like this: ID col0 col1 col2 col3 col4 col5 1

Solution 1:

Here is a way using stack and str.contains with df.where:

cols = ['col1', 'col2', 'col3', 'col4']
df['b'] = (df[cols].where(df[cols].stack().str.contains('b')
         .unstack(fill_value=False)).ffill(1).iloc[:,-1])

---

print(df)

   ID  col0 col1 col2 col3 col4  col5    b
0   1  jack  a/h  t/m  w/n  y/h    56  NaN
1   2   sam  z/n  b/w  NaN  NaN    93  b/w
2   3  john  b/i  y/d  p/d  NaN    33  b/i

Solution 2:

I would use DataFrame.stack with callable:

cols = ['col1', 'col2', 'col3', 'col4']
df['b']=(df[cols].stack()
                 .loc[lambda x: x.str.contains('b')]
                 .reset_index(level=1,drop=1)
                #.fillna('-') #for the expected output
        )

Output

   ID  col0 col1 col2 col3 col4  col5    b
0   1  jack  a/h  t/m  w/n  y/h    56  NaN
1   2   sam  z/n  b/w  NaN  NaN    93  b/w
2   3  john  b/i  y/d  p/d  NaN    33  b/i

Solution 3:

In a bid to avoid selecting the columns, I used melt:

M = (df.copy()
     .melt(id_vars='ID')
     .loc[lambda x:x['value'].astype('str').str.contains('b')]
     .drop('variable',axis=1))

pd.merge(df,M,how='left',on='ID').rename({'value':'b'},axis=1)

    D   col0    col1    col2    col3    col4    col5     b
0   1   jack    a/h     t/m     w/n     y/h      56     NaN
1   2   sam     z/n     b/w     NaN     NaN      93     b/w
2   3   john    b/i     y/d     p/d     NaN      33     b/i