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

## Features

We use density plots to visualize the distribution of a continuous variable. The plot displays the density or probability of occurrence of data points along the x-axis, with the y-axis representing the probability density. This plot provides a smooth estimate of the data distribution, which helps us identify patterns and trends in the data. It is a valuable tool for exploring data and comparing the distributions of different variables or datasets.



## Density plot with `plot()`

We use two different built-in functions to create a density plot in R. We first process the data in the `density()` function, and we supply it to the `plot()` function. The syntax structure is as follows:
```R
# Syntax structure
plot(density(<data>))
```
Now, we will create a basic density plot using the `mtcars` dataset.



# We use `airquality` dataset in this exercise
head(mtcars)   # Preview of the dataset
plot(density(mtcars$mpg))  # Process the data and then plot the chart

- **Line 3**: We first process the `mpg` column of the `mtcars` dataset and then supply it to the `plot()` function.


Because it is also a line plot, we can customize the density plot using the arguments that we use for the line plot.


- `lwd`: The thickness of the line can be set using the `lwd` argument. The bigger the value, the thicker the line.

- `lty`: The line style is changed using this argument. It takes integer values between 1 and 6, each representing a different line style.

- `col`:  We can change the line color by configuring this argument. It takes string values. The strings can be general color names like `"green"` or hexadecimal values like `"#4682B4"`.

Here is a customized version of the density plot:  

# Features

We use density plots to visualize the distribution of a continuous variable. The plot displays the density or probability of occurrence of data points along the x-axis, with the y-axis representing the probability density. This plot provides a smooth estimate of the data distribution, which helps us identify patterns and trends in the data. It is a valuable tool for exploring data and comparing the distributions of different variables or datasets.



# Density plot with `plot()`

We use two different built-in functions to create a density plot in R. We first process the data in the `density()` function, and we supply it to the `plot()` function. The syntax structure is as follows:
```R
# Syntax structure
plot(density(<data>))
```
Now, we will create a basic density plot using the `mtcars` dataset.



Learn how to create density plots using ggplot and density functions.

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

Density Plots

Features

Density plot with `plot()`