1. Introduction For this post, we will use the data about the Great American Beer Festival. Specifically, three kinds of visualization would be created to reveal the geological information in this data.
1. Introduction This week’s data records every attempt people have made to climb the mountains in Himalaya. As an amature hiker, I really hope one day in the future I could step my feet on the groud of Everest which is probably the most famous mountain in Himalaya.
1. Introduction This week’s #TidyTuesday data concerns about the US spending on kids. Since I’m currently in a K12 education tutoring program, I’m really excited about the data and can’t wait to see the final result of the analysis.
1. Introduction Several days ago, I went to a bar to celebrate one of my friends’ birthday. We ordered some cocktails. However, when my drink was served, since I am not an alcoholic person, I couldn’t really recognize what was in my margarita after a few sippings, which makes me wonder if I could develop some interactive web application so that people would know what are the ingredients added to their booze.
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library(tidyverse) ## Warning: package 'ggplot2' was built under R version 4.0.2 ## Warning: package 'tibble' was built under R version 4.0.2 library(extrafont) ## Warning: package 'extrafont' was built under R version 4.
1. Introduction Today, we will analyze the data on campus recruitment. The data is simulated for MBA students at XYZ campus and includes the students’ performance from middle school all the way to MBA.
In this project, we will analyze the tweeter data of Donald Trump and Hillary Clinton. The data contains detailed information about their tweets from January 2016 to Nov 29 2016 (for Clinton, the data spans from April 14 2016 to Nov 29 2016).