In Python, the ‘str’ object does not have an ‘astype’ attribute because ‘astype’ is a method specific to NumPy arrays and pandas DataFrames.
The ‘astype’ method is used to explicitly convert one data type to another. It is commonly used in cases where you want to convert data in a DataFrame column or a NumPy array from one data type to another.
Here’s an example using ‘astype’ with a NumPy array:
“`python
import numpy as np
arr = np.array([1, 2, 3, 4, 5])
arr_float = arr.astype(float)
print(arr_float)
“`
This code creates a NumPy array with integers and then uses the ‘astype’ method to convert the array to floating point numbers. The output will be:
“`
[1. 2. 3. 4. 5.]
“`
Here’s an example using ‘astype’ with a pandas DataFrame:
“`python
import pandas as pd
data = {‘Name’: [‘John’, ‘Mike’, ‘Sarah’, ‘Emily’],
‘Age’: [28, 32, 25, 29]}
df = pd.DataFrame(data)
df[‘Age’] = df[‘Age’].astype(str)
print(df.dtypes)
“`
This code creates a pandas DataFrame with two columns: ‘Name’ and ‘Age’. The ‘Age’ column initially contains integers. Then, using the ‘astype’ method, the ‘Age’ column is converted to strings. The output will be:
“`
Name object
Age object
dtype: object
“`
As you can see, the ‘Age’ column data type has changed from ‘int64’ to ‘object’ (which is the pandas representation of strings).
Make sure you are using the ‘astype’ method on a NumPy array or a pandas DataFrame, as it is not available for ‘str’ objects.