Saving to new csv after using replace() (pandas)

Question

I am working with a set of data in a jupyter notebook and trying to replace numbered variables with names, and then save to a new file afterwards so I can use value_counts() and receive the values in names.

numbered = [1,2,3,4]
fullname = [a,b,c,d]
df.replace(numbered, fullname)
df.to_csv('fullname.csv')

df_fullname = pd.read_csv('fullname.csv')
df_fullname

The replace works fine, but when I go to save it to a new csv and read it, it is back to the numbered version.

`df = df.replace(numbered, fullname)` you did not assign it to a variable and `replace` does not occur `inplace` unless you set that value to true: `df.replace(numbered, fullname, inplace=True)` — It_is_Chris, May 19 '21 at 20:19

score 0 · Answer 1 · answered May 19 '21 at 20:22

0

Umar you must do the replace inplace. Try:

df.replace(numbered, fullname, inplace = True)

answered May 19 '21 at 20:22

Lucas Corbanez

107
10

Worked like a charm! – Umar Shaikh May 19 '21 at 21:12

Saving to new csv after using replace() (pandas)

1 Answers1