[FIXED] TypeError: 'float' object is not subscriptable - Working with Pandas dataframe

Issue

I am trying to convert string values from a column where the values look like this: $200, $6,000, etc. I want to convert these values to float and save them into a new column in my dataframe so I can compute aggregate statistics like .mean() for example.

my_df["Float Values"] = my_df["Value"].apply(lambda x: float(x[1:].replace(',','')) if x != "None" else 0)

But unfortunately I am getting this error:

TypeError: 'float' object is not subscriptable

What am I doing wrong here?

Solution

maybe there are NaN

use following code:

my_df["Float Values"] = my_df["Value"].str[1:].str.replace(',', '').astype('float').fillna(0)

---

make reproducible example

import pandas as pd
s = pd.Series(['$200', '$3,000', float('nan')])

s

0    $200
1    $3,000
2     NaN
dtype: object

run your code:

s.apply(lambda x: float(x[1:].replace(',','')) if x != "None" else 0)

error:

TypeError: 'float' object is not subscriptable

use following code:

s.str[1:].str.replace(',', '').astype('float').fillna(0)

out:

0     200.0
1    3000.0
2       0.0
dtype: float64

Answered By - Panda Kim