Converting Categorical Variable with % Sign to Numerical Variable Python Pandas

Question

dt = {'tensile_strength': ['15%', '15%', '20%', '20%', '25%', '25%', '30%', '30%'], 
      'cotton_pct': [7, 7, 12, 17, 14, 18, 19, 25]}
mydt = pd.DataFrame(dt, columns = ['tensile_strength', 'cotton_pct'])

In my above dataset, 'cotton_pct' is a categorical variable. For 'cotton_pct', how do I create a new variable that is a numerical representation of cotton_pct?

Answer 1

You can access an entire column by .str , after which you can apply .replace() to all elements of that column. Convert to 'int' , and save back into the df

mydt['tensile_strength'] = mydt['tensile_strength'].str.replace("%", '').astype('int')

Answer 2

You can use:

mydt['new_col'] = pd.to_numeric(mydt['tensile_strength'].str.strip('%'))

NB. using a new column here, but you can of course overwrite tensile_strength

output:

  tensile_strength  cotton_pct  new_col
0              15%           7       15
1              15%           7       15
2              20%          12       20
3              20%          17       20
4              25%          14       25
5              25%          18       25
6              30%          19       30
7              30%          25       30