# Category: Analysis

### Plotting with base R

An intuitive introduction to plots and how R deals with them

### Second Weekend straight, obsessed with R — Part IV

The final section of our recap (for the time being at least)!

### Second Weekend straight, obsessed with R — Part III

Next stop in our revising tour: data frames!

### Let’s spend the weekend to consolidate our skills in R — Part II

Finalizing this adventurous weekend

### Let’s spend the weekend to consolidate our skills in R — Part I

A refresher for beginners

### Functions in R (a bit deeper)

Accounting for missing values and creating your own custom functions

### Dates and Strings in R

Experimenting with some of the language’s core functionalities

### Support Vector Machines in Python

Using the cancer data set from the sklearn library

### Principal Component Analysis in Python

A smooth introduction to dimensionality reduction

### Accounting for the style and color, when using in the Seaborn library

Gaining full control of our visualizations

### (De-)Aggregations in R

Clarifying some important steps when dealing with aggregation functions

### k Means Algorithm in Python

Implementing the algorithm in Jupyter Notebook

### Matrix and Regression plots in Python

Using the Seaborn library is quite an eye-refresher

### Seaborn… visualize with style!

I was really impressed by the capabilities of the Seaborn library

### Seaborn library is another library to visualize data in Python

Suited better for statistical analysis

### Matplotlib in Jupyter

Object-oriented plotting was quite exciting

### Matplotlib is the most popular plotting library for Python

The gallery tab provides many useful examples

### If, switch and functions in R

More introductory examples for acing the language

### Introduction to ggplot2 package in R

Code for visualizing data sets for beginners

### Pandas Data Analysis Part II

More advanced data manipulations using the popular library

### Functions, loops, ifelse and apply in R

More introductory examples using the powerful vectorized nature of the language

### Data Analysis in Python using Pandas

Introductory code using the Pandas library

### Loops in R

More examples in R using loops (for, while, repeat)

### NumPy introduction in Jupyter Notebook

Some examples of manipulating arrays using the NumPy library

### More code in Jupyter Notebook

The continuation of the introductory section in Jupyter

### Lists and Data Frames in R

Code for creating and manipulating lists and data frames

### Jupyter, Anaconda and Python

“Project Jupyter is a non-profit, open-source project, born out of the IPython Project in 2014 as it evolved to support interactive data science and scientific computing across all programming languages…”

### Creating a game using the Python programming language

It proved to be quite a challenge