Efficient way to concatenate dataframe with its columns reversed

Question

One fairly recurring pattern I have is creating a dataframe that combines another dataframe with its columns reversed. Here's a small example:

import pandas as pd

df = pd.DataFrame({"a": range(5), "b": range(6, 1, -1)})
combined = pd.concat([df, df.rename(columns={"a": "b", "b": "a"})], ignore_index=True)

Is there a more efficient approach to achieving this operation (esp. with many, many rows)?

Answer 1

You can use the underlying numpy array and vstack on the array and its reversed version, then generate a new DataFrame:

import numpy as np

a = df.to_numpy()
pd.DataFrame(np.vstack([a, a[:, ::-1]]), columns=df.columns)