How to add a suffix (or prefix) to each column name?

Question

I want to add _x suffix to each column name like so:

featuresA = myPandasDataFrame.columns.values + \'_x\'

How do I do this? A

Answer 1

Elegant In-place Concatenation

If you're trying to modify df in-place, then the cheapest (and simplest) option is in-place addition directly on df.columns (i.e., using Index.__iadd__).

df = pd.DataFrame({"A": [9, 4, 2, 1], "B": [12, 7, 5, 4]})
df

   A   B
0  9  12
1  4   7
2  2   5
3  1   4

df.columns += '_some_suffix'
df

   A_some_suffix  B_some_suffix
0              9             12
1              4              7
2              2              5
3              1              4

To add a prefix, you would similarly use

df.columns = 'some_prefix_' + df.columns
df

   some_prefix_A  some_prefix_B
0              9             12
1              4              7
2              2              5
3              1              4

---

Another cheap option is using a list comprehension with f-string formatting (available on python3.6+).

df.columns = [f'{c}_some_suffix' for c in df]
df

   A_some_suffix  B_some_suffix
0              9             12
1              4              7
2              2              5
3              1              4

And for prefix, similarly,

df.columns = [f'some_prefix{c}' for c in df]

---

Method Chaining

It is also possible to do add *fixes while method chaining. To add a suffix, use DataFrame.add_suffix

df.add_suffix('_some_suffix')

   A_some_suffix  B_some_suffix
0              9             12
1              4              7
2              2              5
3              1              4

This returns a copy of the data. IOW, df is not modified.

Adding prefixes is also done with DataFrame.add_prefix.

df.add_prefix('some_prefix_')

   some_prefix_A  some_prefix_B
0              9             12
1              4              7
2              2              5
3              1              4

Which also does not modify df.

---

Critique of add_*fix

These are good methods if you're trying to perform method chaining:

df.some_method1().some_method2().add_*fix(...)

However, add_prefix (and add_suffix) creates a copy of the entire dataframe, just to modify the headers. If you believe this is wasteful, but still want to chain, you can call pipe:

def add_suffix(df):
    df.columns += '_some_suffix'
    return df

df.some_method1().some_method2().pipe(add_suffix)