为 Pandas DataFrame 中的特定行组合行索引和行值（字符串）

Question

Let's say that I have a Pandas DataFrame:

df = pd.DataFrame({'col1': range(10), 'col2': ['a', 'b', 'c', 'a', 'e', 'f', 'g', 'a', 'h', 'i']})

and it looks like:

   col1 col2
0     0    a
1     1    b
2     2    c
3     3    a
4     4    e
5     5    f
6     6    g
7     7    a
8     8    h
9     9    i

I want to update all values where df['col2'] == 'a' and append the row index to a so that we get:

   col1 col2
0     0    a_0
1     1    b
2     2    c
3     3    a_3
4     4    e
5     5    f
6     6    g
7     7    a_7
8     8    h
9     9    i

Answer 1

Use series.mask with series.eq to compare if value equals a and add col1/index after converting to string

df['col2']=df['col2'].mask(df['col2'].eq('a'),df['col2'].add('_'+df.index.astype(str)))

#df['col2']=df['col2'].mask(df['col2'].eq('a'),df['col2'].add('_'+df['col1'].astype(str)))

print(df)

---

   col1 col2
0     0  a_0
1     1    b
2     2    c
3     3  a_3
4     4    e
5     5    f
6     6    g
7     7  a_7
8     8    h
9     9    i

Answer 2

Comprehension

df.assign(col2=[f'{v}_{i}' if v == 'a' else v for i, v in df.col2.iteritems()])

   col1 col2
0     0  a_0
1     1    b
2     2    c
3     3  a_3
4     4    e
5     5    f
6     6    g
7     7  a_7
8     8    h
9     9    i

---

A very low memory footprint loop that edits in place

for i, v in df.col2.iteritems():
    if v == 'a':
        df.at[i, 'col2'] = f'a_{i}'