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R Programming

R Programming

Workshop Overview:




What is Big Data & Why Hadoop?

  • Big Data Characteristics, Challenges with traditional system

Introduction to R

  • History of R
  • An Insight into R
  • Data Structure and Data Type

Data Management and Data Cleaning

  • Missing Value Treatment
  • Outlier Treatment
  • Sorting Datasets
  • Merging Datasets
  • Creating new variables
  • Binning variables
  • Reading datasets from other environments into R ( importing )
  • Writing datasets from R environment to other environments (exporting )

Data Visualization in R

  • Bar Chart
  • Dot Plot
  • Scatter Plot ( 3D )
  • Spinning Scatter Plots
  • Pie Chart
  • Histogram ( 3D ) [including colourful ones ]
  • Overlapping Histograms
  • Boxplot
  • Plotting with Base and Lattice Graphics
  • Plotting and Colouring
  • Geo Charts
  • Motion Charts

Using functions in R:

  • Sapply function
  • Apply function
  • Tapply function

Basic statistics in R

  • Summarizing data
  • Measures of Central Tendency.
  • Measures of Variability and Distributions
  • Hypothesis Testing
  • Performing Anova ( One – Way and Two – Way )

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