Multiple column names in Pandas DataFrame

Question

I am currently moving some data from a numpy array to a Pandas DataFrame so that I can refer to columns by their name, rather than their index. The problem that I have is that I would like to allow for multiple names to refer to the same column.

data = np.array([[1, 2, 3],
                 [4, 5, 6],
                 [7, 8, 9]])
df = pd.DataFrame(data, columns=('Sensor1231', 'Sensor4221', 'Sensor4673'))

Sensor4221, for example, is an accelerometer on the 5th level of a structure. I want to add an additional label so (eg. AccLevel5) so that I can refer to the column without having to remember an obscure sensor number.

Therefore, both of the following will provide the same output.

Accel = df['Sensor4221']

and

Accel = df['AccLevel5']

both give:

2
5
8

Answer 1

the dataframe is a wrapper on the numpy array. You can assign another dataframe pointing to the same array to accomplish your goal.

data = np.array([[1, 2, 3],
                 [4, 5, 6],
                 [7, 8, 9]])
df = pd.DataFrame(data, columns=('Sensor1231', 'Sensor4221', 'Sensor4673'))

df2 = pd.DataFrame(df.values, df.index,
                   columns=('Sensor1231', 'AccLevel5', 'Sensor4673'))

---

df

df2

---

now reasign an element in df and see the change in df2

df.loc[1, 'Sensor4221'] = 999

df2