Data Manipulation with Python, Pandas, R ,SQL and Alteryx

Data Manipulation with Python, Pandas, R ,SQL and Alteryx

Published 6/2023

Created by Bluelime Learning Solutions

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch

Genre: eLearning | Language: English | Duration: 156 Lectures ( 10h 54m ) | Size: 2.9 GB

What you'll learn

Understand the role and importance of data manipulation in data analysis and data science.

Install and set up Python, R, SQL, Pandas, and Alteryx for data manipulation tasks.

Understand the basics of programming with Python and R, and writing SQL queries.

Manipulate data in Python using the Pandas library, including loading, cleaning, transforming, and analyzing data.

Use Python for data cleaning, including handling missing values and formatting data.

Write complex SQL queries to retrieve and manipulate data from relational database

Understand and use SQL operators, indexes, and table joins for effective data manipulation.

Understand the features and functionalities of the Alteryx platform for data manipulation.

Import and export data in various formats using Alteryx.

Use Alteryx for advanced data manipulation tasks, including data blending and spatial analysis.

Handle missing data and format data in Alteryx.

Understand and use data wrangling techniques in Alteryx, including data transformation, pivoting, and binning.

Create calculated fields and perform time series analysis in Alteryx.

Create and use macros in Alteryx to automate repetitive tasks.

Understand the basics of data manipulation with R, including using the dplyr and tidyr packages.

Write R scripts to filter, select, mutate, and arrange data using dplyr.

Reshape data in R using the gather and spread functions in the tidyr package.

Use the integration of Python, R, SQL, Pandas, and Alteryx in a single data manipulation workflow.

Apply the learned skills in real-world data manipulation projects.

Analyze and interpret the results of data manipulation tasks.

Troubleshoot and solve problems related to data manipulation.

Write efficient and reusable code for data manipulation.

Develop a systematic and strategic approach to handle large datasets.

Understand ethical considerations in data manipulation, including data privacy and data integrity.

Requirements

Basic computer skills.

Familiarity with programming concepts would be beneficial but not required.

No prior knowledge of Python, R, SQL, Pandas, or Alteryx is required, as this course will start from the basics.

Access to a computer with an Internet connection to install the necessary software and libraries.

Description

In the era of Big Data, the ability to manipulate and analyze complex datasets is not just an advantage; it's a necessity. The Comprehensive Data Manipulation course offers a deep dive into the world of data manipulation using five potent tools: Python, Pandas, R, SQL, and Alteryx. Whether you're a beginner just embarking on a career in data analysis, or a seasoned professional looking to expand your skillset, this course offers a robust foundation and advanced techniques in data manipulation.This course adopts a project-based approach, reinforcing learning through practical application. Starting with an overview of data manipulation and its role in data analysis, the course progresses to an in-depth exploration of each tool, covering their installation, setup, features, and unique strengths.Python, a versatile language renowned for its readability, is the first tool we tackle. Here, you'll learn the basics of Python programming for data manipulation, moving onto mastering the use of Python's powerful library, Pandas. With Pandas, you'll explore data cleaning, preprocessing, and analysis. Handling missing data, converting data types, parsing dates, and more become straightforward with this handy library.Next, we delve into SQL, a standard language for managing data held in relational databases. Through this section, you'll grasp SQL commands and functions, enabling you to interact with databases, retrieve, and manipulate data with precision.We then transition to R, another popular language for data analysis, with a focus on dplyr and tidyr packages. These packages allow for efficient data transformation, reshaping, and overall manipulation.Finally, we introduce Alteryx, a platform that provides advanced data blending, spatial analysis, and enables the creation of repeatable workflows. The Alteryx section covers all these features and includes how to handle missing data, format data, and perform time series analysis.While each of these tools is powerful in its own right, their true strength comes from their integration. The course culminates in a real-world data manipulation project requiring the use of Python, Pandas, R, SQL, and Alteryx in a unified workflow. This capstone project, focusing on the analysis and prediction of energy consumption, allows you to apply the learned skills in real-time and gives you a taste of real-world data manipulation challenges.With this comprehensive course, you'll not only learn the mechanics of each tool but also when and how to use them most effectively. You'll develop a systematic and strategic approach to handle large datasets, write efficient and reusable code, and understand ethical considerations in data manipulation. By the end of the course, you'll be well-equipped to tackle any data manipulation task, thereby opening new avenues in your data analysis or data science career.

Who this course is for

Beginners who want to start a career in data analysis or data science.

Data professionals looking to expand their skill set by learning new tools and techniques.

Anyone interested in learning how to manipulate and analyze data using Python, R, SQL, and Alteryx.