2 Task Create a single Jupyter/IPython notebook (see the Artefacts section below for all the re the whole task specification first!), where you perform what follows. The use of pandas is forbidden. You can use scipy, though. Do not use for loops or list comprehensions - this is an exercise on numpy. 1. Download the latest daily close BTC-to-USD data, from 2023-01-01 up to this tps://finance.yahoo.com/quote/BTC-USD (the Historical Data tab). Use a spreadsheet application such as Libreoffice Calc or MS Excel to manually except the numeric values in the Close column. The column labels should also Export these observations to a CSV file (which should only contain numbers, 2. Use numpy . genfromtxt or numpy . loadtxt to read the above BTC-to-USD dat named rates 3. For the third quarter of the year only (Q3 2023; days 182-273 inclusive), determin a readable manner) the following aggregates: . arithmetic mean, . minimum, . the first quartile, . median, . the third quartile, . maximum, . standard deviation, . interquartile range. Reference result (yours can be prettier): ## arithmetic mean : 28091.33 ## minimum: 25162.65 ## Q1: 26225. 56