Datasets in R: Joining & Visualizing Data
R Programming 4.0+
6 Videos | 48m 42s - Includes Assessment
- Earns a Badge
Data for the same entity is often stored in multiple locations. Your analysis may require bringing this data together in a single location. Doing this forms a core part of data preprocessing. Another core task is recognizing the relationships in your data. In this course, you'll practice methods to merge data to prepare for statistical and predictive modeling and identify relationships in your data using charts and graphs. You'll combine data in different data frames (or tibbles) based on the values in common columns. You'll use the merge() function to perform join operations and implement joins using functions from the tidyverse. You'll also examine the plotting systems available in R and use the plot() functionality and the ggplot2 package to visualize and explore your data. Upon completion of this course, you'll be able to combine your data in a meaningful way and uncover data relationships.
WHAT YOU WILL LEARN
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discover the key concepts covered in this course
perform joins on data frames using the merge() function
use the dplyr inner_join() function and perform filtering joins -
create histograms and KDE curves using plot() and ggplot2
visualize data using scatter plots, box plots, and line charts
summarize the key concepts covered in this course
IN THIS COURSE
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1.Course Overview1m 57sUP NEXT
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2.Joining Data Frames Using merge()11m 1s
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3.Joining Tibbles Using Joins and Filtering Joins8m 54s
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4.Creating Histograms and Density Curves11m 33s
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5.Using Plots and Charts to Visualize Data10m 54s
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6.Course Summary2m 23s
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