Here's an example of how to import data using the Yahoo Finance API into a Pandas dataframe:

import pandas as pd
import numpy as np

# Define the ticker symbol and the desired start and end dates
ticker = "BTC-USD"
start_date = "2010-07-17"
end_date = "2022-07-17"

# Use the Yahoo Finance API to import the data into a Pandas dataframe
df = pd.DataFrame(pd.read_html("https://finance.yahoo.com/quote/BTC-USD/history?p=BTC-USD", parse_dates=True)[0])

# Clean the data by removing unneeded columns and setting the date column as the index
df.drop(columns=['Open', 'High', 'Low', 'Adj Close*', 'Volume'], inplace=True)
df.set_index('Date', inplace=True)

# Filter the data by the desired start and end dates
df = df[(df.index >= start_date) & (df.index <= end_date)]

In this example, the read_html method of the Pandas library is used to extract the data from the Yahoo Finance API and store it in a Pandas dataframe. The parse_dates argument is set to True to ensure that the date column is automatically converted to a datetime data type. The data is then cleaned by removing unneeded columns and setting the date column as the index. Finally, the data is filtered by the desired start and end dates.
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