#Your ability to performn a correct C-SAT analysis will be evaluated, as well as your ability to identify valuable insights from text analytics techniques.

##We are going to work with data from itunes so we can both analyse the customer satisfaction regarding some app and zoom into the comments to try to understand why the app has been rating this way.

#The data set contains 2.627 reviews from Zoom app from multiple countries (remember there is a limit of 500 reviews that can be pulled for each country) #You need to Load the Rdata file into the environment so the data frame will be available for you

#Step 2: Make sure the date column has the correct type and also transform the column review to lower case. #Explore the dataframe and mentioned the highlights in at least 5 lines #Visualizing the numbers of reviews per day, identify the day with most reviews created (1.5pt)

#Step 3: Perform a cleaning over the review column to prepare the data to apply "one-token-per-row" format #Consider the need to eliminate puntuation marks, numbers, stop words etc #Hint: use the filter() and str_detect() functions along with regex and stop_words() #You can also use udpipe to make sure you're only working with relevant words like adjectives, verbs, etc. (2pts)