Since there are a lot of functions in the package to use, I will mainly focus on the functions related to my topic. There are other ways to obtain the data, such as scraping data from NBA official website using python, which I am also investing on. The thing needed to be noticed that the package might not satisfy your all needs for the project. Hence, while I am trying to explore the package in R, it is also great to complete this tutorial to share the information and help others who are also interested in NBA or basketball analysis in R. Fortunately, there is a useful package in R called ‘nbastatR’. Having a great dataset is a prerequisite for the project but the official dataset is only viewable on NBA.com but not available for downloading as csv file. My final project for this course is analysis on professional basketball, more specifically, the transformation of game style of professional basketball. 135 Building a Dashboard in R for Data Analysis and Visualization using shiny package.134 Alluvial diagrams and their implementation using GGalluvial in R.132 Introduction to analytics consulting at Accenture.126 An introduction to pyecharts package in Python.123 Python Altair Visualization Method Tutorial.116 3D data and potential relationship visualization.115 Tutorial for scatter plot with marginal distribution.106 3D Visualization with rgl and scatterplot3d.104 Using PostgreSQL Databse in R with MacOS Environment.102 rdoc - An Alfred Worflow to Search R Documentation. 98 Predictive Analytics using Data Visualization in R.96 A brief instruction for the half semester of EDAV5702.90 Comparing Excel Chart Making with R’s.89 Urca: Unit Root Test and Cointegration Test.83 Common git command lines tutorial when working on studio.81 R based data organization and visualization.76 Tutorial for ggvis and its Comparison with ggplot2.75 A Step by Step Tutorial for Natural Language Processing in R.74 Tutorial of three ggplot2 based packages.73 Recursive codes and self-organized map with R.72 EDAV Tutorials: Correlogram, Calendar Heatmap and Slopegram.69 Introduction to Time Series Analysis in R.65 Introduction to Interactive Time Series Visualizations with dygraphs in R.64 Introduction to models and prediction evaluation.62 Introduction to exploratory spatial data analysis and visualization using QGIS.58 Introduction to XAI (Explainable AI) in R.57 Hive plots with the ggraph and hiver packages.54 Raincloud plot 101: density plot or boxplot?Why not do both!.53 Comparison among base R, tidyverse, and datatable.52 Video introduction to maps with ggmap.45 Introduction to interactive graphs in R.35 Base R, ggplot2, & Python Graphing Performances.34 A cheatsheet from pandas to base r and tidyverse.31 Animate Time Series : the goyav package.30 Learning SQL with Its R dplyr Translation.21 R note and Mathematics in Rmd cheatsheet.19 review sheet for r code and data transformation.13 Statistical Tests and Parameter Estimations in R Cheatsheet.10 Interactive web visualizations for R cheatsheet".He also ran for a team-leading 97 yards on 23 attempts as the Bulls gained 177 on the ground. We need to fix all those things.”īyrum Brown completed 14 of 28 passes for 87 yards and one interception for USF. A kickoff return today, a touchdown run today and two last week. “We’ve had four touchdowns this season negated by penalties. “I know we’ve got the SEC (conference play) coming up next week and obviously we’ve got a lot of things to fix and we’ll work on it,” Saban said. Alabama amassed 203 yards on the ground, with Jase McClellan gaining 70 of his 74 yards in the first half. He capped the victory by ending an an 11-play, 80-yard drive in the closing minutes with a 1-yard TD run. Simpson finished 5 of 9 passing for 73 yards without an interception. We were a little flat in the beginning, but after the rain delay I thought we competed better.”Īlabama hurt itself early, with Kool-Aid McKinstry’s losing a fumble on a first-quarter punt return to set up John Cannon’s 44-yard field goal for USF and Jeremiah Alexander’s holding penalty that wiped out what would have been Terrion Arnold’s 100-yard return for a TD on the ensuing kickoff. I need to do a better job of getting them ready to play in games like this. I’m really proud of our players for the way they competed. “We ran the ball fairly well, better in the second half than we did in the first. “I know we struggled a little bit on offense,” Saban said.
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