Gain insights into data manipulation, analysis, and visualization with R. Learn statistical concepts, create insightful visualizations, and empower decision-making to excel in data-centric roles.

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This course delves into data manipulation, analysis, and visualization with R. It demonstrates the power of R as open-source statistical software, unlocking valuable insights for decision-making across diverse fields.

You'll begin by mastering the basics of R programming, fundamental data structures in R, and file management. You will learn fundamental statistical concepts such as hypothesis testing and regression analysis. You will also learn to leverage well-structured data for creating insightful visualizations using R's robust graphics libraries.

After completing this course, you'll confidently approach data-driven challenges. With proficiency in R, you can efficiently manipulate and analyze data, positioning yourself as a sought-after asset in data-centric roles. Your ability to interpret statistical results and create compelling data visualizations will empower improved decision-making, paving the way for new opportunities for career growth and success across various industries.

Introduction to Data Analysis and Visualization with R

String manipulation is ubiquitous in datasets and is a critical skill for analysts to have. Data is often contained within blocks of text, requiring us to tease out the information contained in it with rigorous effort. 
A range of techniques for string manipulation exists in data analysis. This lesson focuses on the most widely used methods.
Please note that some of the functions in this lesson come from the `stringr` library. 


## Find the length of strings
Finding the length of strings is helpful in filters and categorization. 
There are different ways to see the number of characters in a string.
Both the built-in `nchar()` and the `str_count()` functions from the `stringr` library return the number of characters in a string.
```R
# Use of nchar() function
myString <- "Education is vital"
nchar(myString)
# Use of str_count() function
str_count(myString)
```

## Change the letter casing of strings


Explore fundamental string analysis techniques in R.

Getting Started

File Management

Data Structures

Data Cleaning

Statistical Analysis

Data Transformation

Data Visualization

Uber Data Analysis Using the R Language

Conclusion

Evaluation

Netflix Shows

Strings in R

Processing string (character) data

Find the length of strings