Use DataFrame.transform() function to find the square root and the result of euler's number raised to each element of the dataframe.

Sure, here is how you can use the transform() function in pandas to find the square root and the result of Euler's number raised to each element of a DataFrame.

First, let's create a simple DataFrame:

import pandas as pd
import numpy as np

# Create a simple dataframe
df = pd.DataFrame({
    'A': [1, 2, 3, 4, 5],
    'B': [4, 5, 6, 7, 8],
    'C': [9, 10, 11, 12, 13]
})

Now, let's use the transform() function to find the square root of each element:

# Find the square root of each element in the dataframe
df_sqrt = df.transform(np.sqrt)
print(df_sqrt)

Next, let's use the transform() function to find the result of Euler's number raised to each element:

# Find the result of Euler's number raised to each element in the dataframe
df_exp = df.transform(np.exp)
print(df_exp)

In the above code, np.sqrt and np.exp are the functions passed to transform(). These functions are applied to each element of the DataFrame. The np.sqrt function returns the square root of each element, and the np.exp function returns Euler's number (approximately 2.71828) raised to the power of each element.