Why is Pandas replace() method not working?

Question

I am trying to replace all columns in my df with prices to ints however for some reason the replace() method isn't working:

df = pd.read_csv(f_name, dtype="string")
df = df[df.columns.dropna()]
df[cols_int] = df[cols_int].replace({"[\$]": "", "[,]": ""}, regex=True)
df[cols_int] = df[cols_int].astype(int)

Error:

ValueError: invalid literal for int() with base 10: '$499,000'

I'd appreciate any help!

you need to use the replace for the string represenation of the series: df[cols_int].str.replace({"[\$]": "", "[,]": ""}, regex=True) -> place .str.in between. — Andreas
– Andreas, Commented May 5, 2021 at 22:23

tdy · Accepted Answer · 2024-11-12 03:05:18Z

4

As of pandas 1.3, this bug should not occur anymore.

If you are still using pandas <1.3, this bug was caused by the "string" dtype, so use dtype=str or dtype="str" instead:

df = pd.read_csv(f_name, dtype=str)
#                              ---
df = df[df.columns.dropna()]
df[cols_int] = df[cols_int].replace({"[\$]": "", "[,]": ""}, regex=True)
df[cols_int] = df[cols_int].astype(int)

edited Nov 12, 2024 at 3:05

answered May 5, 2021 at 22:54

tdy

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