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in the last video we covered the essentials of dplyr and looked at some basic built-in functions in this video weamp;#39;re going to cover a few additional packages you can load into your art project to do even more data wrangling weamp;#39;ll specifically look at data cleaning reshaping data and joining data sets weamp;#39;ll be using the same data set as last time the billboard hot 100 songs and iamp;#39;ll leave a link to it in the description anyway letamp;#39;s get started so weamp;#39;re first going to start by loading in our dplyr and reader libraries and then loading in our billboard 100 data set weamp;#39;re also going to grab our code from last time to select the date up to the artist columns and then rename the weekamp;#39;s on board columns to week popular letamp;#39;s just go ahead and run that and see what our output looks like we have our date our rank our song our artist and then weeks popular and this is all going to be in our music df data frame now looking a
