Swap String part in all dataframe columns

Question

I have a dataframe in the following template:

lista = []
lista.append(['A1','2','A3'])
lista.append(['4','A5','6'])
lista.append(['A7','8','9'])

df = pd.DataFrame(lista, columns=['A', 'B', 'C'])

df:

What I want is to remove the character 'To' of all columns. I know I can get it out by going column by column with the command (df. Series):

df.A.replace('A', '', regex = True)
df.B.replace('A', '', regex = True)
df.C.replace('A', '', regex = True)

Upshot:

However, I would like to set up a function that goes through my dataframe removing this specific character.

I tried to perform an iteration on the columns and pick each one up as follows:

for column in df.columns[1:]:
    print(column)
    df[column] = df.column.replace('A', '', regex = True)

But the following error returns to me:

Attributeerror: 'Dataframe' Object has no attribute 'column'

Any idea?

Answer 1

You can use the predefined function replace, as follows:

df.replace({'A': ''}, regex=True, inplace=True) 

Given your dataframe, the result will be:

   A  B  C
0  1  2  3
1  4  5  6
2  7  8  9