data-science Tutorials

1. What is Scrapy and how to use it.

By: Lawrence : 2023-03-17

Description: Scrapy is a web scraping framework that is legal to use under certain circumstances. Web scraping is the process of extracting data from websites using automated tools or software, and it is generally considered legal if done ethically and in compliance with applicable laws.

2. Manipulating Data with dplyr in R

By: Emiley J : 2020-04-04

Description: In this tutorial, you'll learn how to manipulate data using dplyr. dplyr is a fast and powerful R package written by Hadley Wickham and Romain Francois that provides a consistent and concise grammar for manipulating tabular data.

3. Graphics basics in R - Plot()

By: Emiley J : 2020-04-04

Description: One of the greatest strengths of R, relative to other programming languages, is the ease with which we can create publication-quality graphics. In this tutorial, you'll learn about base graphics in R

4. Introduction to logical operations in R

By: Emiley J : 2020-04-04

Description: luate to either TRUE or FALSE.

5. Types of Analysis - Data Science Questions?

By: Emiley J : 2020-04-04

Description: Data is the second most important thing in data science. the first most important is the question that you want to solve.

6. Using make.names() in R

By: Karthik Janar : 2018-05-22

Description: While doing data analysis, it is highly recommended to use proper naming conventions for files, variables and especially column names. This is very important for two reasons

7. Handling Date and Time in R

By: Karthik Janar : 2018-05-07

Description: R has a special way of representing dates and times, which can be helpful if you're working with data that show how something changes over time (i.e. time-series data) or if your data contain some other temporal information, like dates of birth.

8. Functions in R - Creating your first R function

By: Karthik Janar : 2018-05-06

Description: Functions are one of the fundamental building blocks of the R language. They are small pieces of reusable code that can be treated like any other R object. Functions are usually characterized by the name of the function followed by parentheses.

9. Subset Vectors in R

By: Karthik Janar : 2018-05-01

Description: In this tutorial, we'll see how to extract elements from a vector based on some conditions that we specify. For example, we may only be interested in the first 20 elements of a vector, or only the elements that are not NA, or only those that are positive or correspond to a specific variable of interest. By the end of this tutorial, you'll know how to handle each of these scenarios.

10. Matrices and Data Frames in R

By: Karthik Janar : 2018-05-01

Description: In this tutorial, we'll cover matrices and data frames. Both represent ‘rectangular' data types, meaning that they are used to store tabular data, with rows and columns. The main difference, as you'll see, is that matrices can only contain a single class of data, while data frames can consist of many different classes of data.