Here's what I say:

df["rating"] = df["rating"].astype(str, errors='ignore')
df.dtypes

Here's what it prints:

name                object
platform            object
year_of_release      int64
genre               object
na_sales           float64
eu_sales           float64
jp_sales           float64
other_sales        float64
critic_score       float64
user_score         float64
rating              object
total_sales        float64
reviewed              bool
dtype: object

As you can see, rating is still an object and not a string. Why is it so?

CodePudding user response：

As of Pandas 1.0, the extension types, StringDtype was introduced. Per Work with text data docs:

There are two ways to store text data in pandas:

1. object -dtype NumPy array.
2. StringDtype extension type.

We recommend using StringDtype to store text data.

Prior to pandas 1.0, object dtype was the only option.

Currently, with astype(str), you are rendering an object type which can contain any mix of types including numbers and strings. However, since Pandas 1.0 , you can now use a dedicated string type:

df["rating"] = df["rating"].astype("string")

CodePudding user response：

Try using this command

df["rating"]=df["rating"].apply(obj).astype('str')