Create a new column named 'date' in the data frame "tweet_df" (from Question 1), using "panda.to_datetime()" function with only the years extracted from the 'created_at' column.

Using the date column created in Question 3A, write code to analyse the yearly change (if any) of the number of Scott Morrison favorite_count, which is the number of people who liked each tweet.You should group your dataframe by date and calculate the median of the number of people who liked each tweet. Save this grouped dataframe as a new dataframe called "grouped".Plot the number of people who liked each tweet versus date.PLEASE LEAVE THE COMMENT ### edTest(test_q3b) ### in the code box below for auto-marking.HintsImport the required library/librariesRemember to properly label your axisYour plot should look like this:

t = Time.new(1991, 07, 5, 9, 15, 33, "+09:00")   puts t.friday? #=> false   puts t.year #=> 1993   puts t.dst? #=> false   puts t + (60*60*24*365) #=> 1994-02-24 12:00:00 +0900   puts t.to_i #=> 730522800     t1 = Time.new(2017)   t2 = Time.new(2015)     puts t1 == t2 #=> false   puts t1 == t1 #=> true   puts t1 <  t2 #=> true   puts t1 >  t2 #=> false     puts Time.new(2010,10,31).between?(t1, t2) #=> true

The file ScottMorrisonMP.json contains tweets from April 10th, 2015 until August 3rd, 2020. The data are organised as following:'created_at', 'favorite_count', 'followers_count', 'full_text', 'id', 'retweet_count', 'source'created_at: this column contains information about the date and time the tweet was createdfavorite_count: number of people who liked the tweetfollowers_count: number of Twitter users that follow Scott Morrisonfull_text: full text of the tweetid: tweet IDretweet_count: number of times a tweet has been retweetedsource: the device used to send the tweetQuestion 1Write a Python script to:import the required librariesload the data (ScottMorrisonMP.json)convert to a data frame called tweet_dffind the 5 most retweeted tweets and order them by the most likes and display only the tweet text (full_text), number of times the tweet has been retweeted (retweet_count), the date and time of the tweet (created_at) and number of people who liked the tweet (favorite_count) in this order. Save this into a dataframe called top5.The data are in your working directory.PLEASE LEAVE THE COMMENT ### edTest(test_q1) ### in the code box below for auto-marking.Hintimport jsonuse "open("ScottMorrisonMP.json")" and "json.load()" functionsuse "panda.DataFrame.from_records()" function

# Split the sample along the time dimension:# * Data from 2008 to 2017 will be used for training # * Data from 2018 to 2022 will be used for testingX_train=X.loc[pd.IndexSlice[:,'2008-01-01':'2017-12-31'],:]X_test=X.loc[pd.IndexSlice[:,'2018-01-01':'2022-12-31'],:]y_train=y.loc[pd.IndexSlice[:,'2008-01-01':'2017-12-31'],:]y_train=y.loc[pd.IndexSlice[:,'2018-01-01':'2017-12-31'],:]

Which temporal function extracts the year from a date in SQL?