Learn how to use the Python pandas library for Data Science with: Python,Pandas,Matplotlib,Jupyter Notebook
Note: Course Free for limited time and limited users(500 limit) so Enroll ASAP. If not free it means you are late. Scroll Down and click Enroll Now button to get enrolled
What You will Learn
- Build confidence in your ability to handle complex data analysis tasks independently.
- Apply data analysis skills to real-world datasets and derive actionable insights.
- install Python on both Windows and macOS systems
- Create and Manage Virtual Environments
- Create and manage Jupyter Notebooks for interactive data analysis.
- Create compelling visualizations of data using Pandas
- Perform detailed analysis on financial data to extract meaningful insights.
- Apply data transformation techniques to reshape and modify datasets
- Conduct thorough data inspections and clean data to prepare it for analysis.
- Gain an understanding of the Pandas library and its capabilities.
- Create Pandas Series from lists and dictionaries and understand their structure and functionality.
- Efficiently access and manipulate data within DataFrames
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Requirements
- Basic Computer Skills
- Understanding of Basic Programming Concepts (Optional)
- A Windows or macOS computer with internet access.
Description
With this course, you’ll learn why pandas is the world’s most popular Python library, used for everything from data manipulation to data analysis. You’ll explore how to manipulate DataFrames, as you extract, filter, and transform real-world datasets for analysis.
We’ll start by understanding what Python is and how to install it on both Windows and macOS platforms. You’ll learn the importance of virtual environments, how to create and activate them, ensuring a clean and organized workspace for your projects.
We’ll then introduce you to Jupyter Notebook, a powerful tool that enhances the data analysis experience. You’ll learn how to install Pandas and Jupyter Notebook within your virtual environment, start the Jupyter Notebook server, and navigate its intuitive interface. By the end of this section, you’ll be proficient in creating and managing notebooks, setting the stage for your data analysis journey.
Pandas Data Structures
With your environment set up, we dive into the heart of Pandas: its core data structures. You’ll discover the power of Series and DataFrame, the fundamental building blocks of data manipulation in Pandas. You’ll learn to create Series from lists and dictionaries, access data using labels and positions, and perform slicing operations.
The course then progresses to DataFrames, where you’ll master creating DataFrames from dictionaries and lists of dictionaries. You’ll gain practical experience in accessing and manipulating data within DataFrames, preparing you for more complex data analysis tasks.
Pandas Data Manipulation, Analysis and Visualization
Armed with a solid understanding of Pandas, we venture into the realm of financial data analysis. You’ll learn to download datasets, load them into DataFrames, and conduct thorough data inspections. We’ll guide you through essential data cleaning techniques to ensure your datasets are ready for analysis.
Data transformation and analysis take center stage as you uncover insights from your financial data. You’ll apply various Pandas operations to transform raw data into meaningful information. Finally, we’ll explore data visualization, teaching you how to create compelling visual representations of your analysis.
Conclusion
By the end of this course, you will have a deep understanding of Pandas and its capabilities in data analysis and visualization. You’ll be equipped with the skills to handle and analyze complex datasets, transforming them into actionable insights. Whether you’re a beginner or looking to enhance your data science skills, this course will empower you to harness the power of Pandas for financial data analysis and beyond. Embark on this transformative learning journey and become a proficient data analyst with Pandas.
Who this course is for:
- Aspiring Data Analysts
- Beginners in Programming and Data Science
- Anyone Interested in Data
- Professionals Looking to Upskill
- Students and Academics
- Business Analysts and Managers
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Course content
4 sections • 32 lectures • 1h 57m total lengthCollapse all sections
Introduction to Python Pandas
- Introduction
- Overview of Python for data analysis
- Introduction to pandas library
Installation and setup
- Python Installation on Windows
- What are virtual environments
- Creating and activating a virtual environment on Windows
- Python Installation on macOS
- Creating and activating a virtual environment on macOS
- What is Jupyter Notebook
- Installing Pandas and Jupyter Notebook in the Virtual Environment
- Starting Jupyter Notebook
- Exploring Jupyter Notebook Server Dashboard Interface
- Creating a new Notebook
- Exploring Jupyter Notebook Source and Folder Files
- Exploring the Notebook Interface
Data Structures in pandas
- Series and DataFrame objects
- Creating a Pandas Series from a List
- Creating a Pandas Series from a List with Custom Index
- Creating a pandas series from a Python Dictionary
- Accessing Data in a Series using the index by label
- Accessing Data in a Series By position
- Slicing a Series by Label
- Creating a DataFrame from a dictionary of lists
- Creating a DataFrame From a list of dictionaries
- Accessing data in a DataFrame
- Manipulating Data in a DataFrame
Data Manipulation and Visualization with pandas
- Download Dataset
- Loading Dataset into a DataFrame
- Inspecting the data
- Data Cleaning
- Data transformation and analysis
- Visualizing data
Note: Course Free for limited time and limited users(500 limit) so Enroll ASAP. If not free it means you are late.
