IN PYTHON. PLEASE CAREFULLY ANSWER THE QUESTION. WILL LIKE .

A Pandas Series is like a column in a table. It is a one-dimensional array holding data of any type. Read the documentation and create a series that contains 4 items. After that finish the following given cells. In [3]: \# create a four item Series In [10]: \# get value at label 1 In [11]: \# Write a snippet of code that will return a Series with the row with labels 1 and 3 In [5]: \# create the same series but this time using an explicit index In [6]: \# look up items the series having index at first and index at last position In [7]: \# get only the index of the Series In [8]: \# create a Series who's index is a series of dates \# https://pandas.pydata.org/docs/reference/api/pandas.date_range.html \# between the two specified dates (inclusive) \# Dates: September 5, 2022 to September 11, 2022 In [9]: \# create a Series with values (representing temperatures) for each date in the index \# You can give them hardcoded values for now [80,82,85,90,83,87,80,78] \# You can call this series clt_temp In [10]: \# what's the temperation for September 9? In [11]: \# create a second series of values using the same index \# You can give them hardcoded values for now [70,75,69,83,79,77,74,79] \# You can call this series nyctemp In [12]: \# the series clt_temp and nyc_temp are aligned by their index values \# calculates the difference by those matching labels In [13]: \# Write the code to find the temperature difference on September 8? In [14]: \# Write code to find an average difference of temperature between the 2 cities