How to modify (correct) values that are poorly written in a DataFrame with python

Question

I have a csv file that contains values that are badly written. I want to correct these mistakes. for example replace Toyouta by toyota, maxda by mazda, in the column named carCompany. example .

The job I need to do is to predict the car price using these independent variables the beginning of my code

Possible duplicate of [Set value for particular cell in pandas DataFrame using index](https://stackoverflow.com/questions/13842088/set-value-for-particular-cell-in-pandas-dataframe-using-index) — Rishabh Deep Singh, Jun 14 '19 at 11:11
you could use this package : https://pypi.org/project/pyspellchecker/ very helpful — Kaies LAMIRI, Jun 14 '19 at 11:11

score 1 · Accepted Answer · answered Jun 14 '19 at 11:15

1

DataFrame.replace(to_replace=None, value=None, inplace=False, limit=None, regex=False, method='pad')

eg.
>>> df = pd.DataFrame({'A': [0, 1, 2, 3, 4],
...                    'B': [5, 6, 7, 8, 9],
...                    'C': ['a', 'b', 'c', 'd', 'e']})
>>> df.replace(0, 5)
   A  B  C
0  5  5  a
1  1  6  b
2  2  7  c
3  3  8  d
4  4  9  e

df.replace('Toyouta','toyota')

should work.

answered Jun 14 '19 at 11:15

Kacper

394
2
8

it works but the change is not preserved. how can I keep it to continue my analyzes – sarra el filali Jun 14 '19 at 11:37
just overwrite DataFrame: df = df.replace('Toyouta','toyota'), or create new one: df_new=df.replace('Toyouta','toyota') – Kacper Jun 14 '19 at 11:40
df.replace({'Toyouta':'toyota', 'vw': 'volkswagen'}, inplace = True) – qaiser Jun 14 '19 at 11:45

How to modify (correct) values that are poorly written in a DataFrame with python

1 Answers1