TypeError: Cannot index by location index with a non-integer key in for loop

While touring the "class" column, I want to change the value to "01" if the data value is "one", "02" if it is "two", and "03" if it is "three", what’s the problem?

# Import Packages
import pandas as pd 
import numpy as np
import seaborn as sns

# dataset upload
df = sns.load_dataset("titanic")
df = df.rename(columns={'pclass':'passenger_class','sex':'gender','age':'old'})
for x in df['class']:
    if df.iloc[x] == 'First':
      print('01')
    elif df.iloc[x] == 'Second':
      x = '02'
    elif df.iloc[x] =='Third':
      x = '03'
df

Get an error:

TypeError: Cannot index by location index with a non-integer key

>Solution :

As outlined in comment, pandas.DataFrame.iloc only takes integers as indexers. Or, given how you iterate over df['class'], it turns out that your xs are strings of characters. Hence the TypeError you get.

That being said, if you want to replace your occurrence by something else, what about using pandas.Series.map, as follows:

>>> df['class'].map({'First': '01', 'Second': '02', 'Third': '03'})
0      03
1      01
2      03
3      01
4      03
       ..
886    02
887    01
888    03
889    01
890    03
Name: class, Length: 891, dtype: category
Categories (3, object): ['01', '02', '03']