Filter out rows of the last available date of the quarter pandas

I have a dataset that looks like this

data = {'Date': ['2022-01-01', '2022-02-15', '2022-03-10', '2022-04-20', '2022-05-05', '2022-06-30', '2022-07-15', '2022-08-10', '2022-09-25', '2022-09-25'],
        'Value': [10, 15, 20, 25, 30, 35, 40, 45, 50, 50]}

What I want to do is get the last available date of each quarter so that the result would look like

        Date  Value
0 2022-03-10     20
1 2022-06-30     35
2 2022-09-25     50
3 2022-09-25     50

What I have done is something like this

import pandas as pd

# Create sample DataFrame
data = {'Date': ['2022-01-01', '2022-02-15', '2022-03-10', '2022-04-20', '2022-05-05', '2022-06-30', '2022-07-15', '2022-08-10', '2022-09-25', '2022-09-25'],
        'Value': [10, 15, 20, 25, 30, 35, 40, 45, 50, 50]}

df = pd.DataFrame(data)

# Convert 'Date' column to datetime format
df['Date'] = pd.to_datetime(df['Date'])

# Create a new DataFrame with last dates of quarters
last_dates = df.resample('Q', on='Date').last().reset_index()

# Merge the original DataFrame with the last_dates DataFrame
df = pd.merge(df, last_dates, on='Date')

print(df)

But it keeps throwing me the error

ValueError: cannot insert Date, already exists

How can I resolve this issue?

A possible solution:

df['Date'] = pd.to_datetime(df['Date'])

(df.groupby(df['Date'].dt.to_period('Q'))
 .agg({'Date': 'last', 'Value': 'last'})
 .reset_index(drop=True).merge(df))

Output:

        Date  Value
0 2022-03-10     20
1 2022-06-30     35
2 2022-09-25     50
3 2022-09-25     50