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Data Analysis and Visualization with Pandas and Matplotlib
Transforming Raw Data into Actionable Insights using :Python, Pandas, Matplotlib, Pyplot, Juypyter Notebook
This Course Includes
udemy
4.6 (22 reviews )
2 total hours 
english
Online - Self Paced
course
Udemy
About Data Analysis and Visualization with Pandas and Matplotlib
Unlock the full potential of data analysis and visualization with "Data Analysis and Visualization with Pandas and Matplotlib." This course is designed to take you from the very basics of Python setup to financial data insights, equipping you with the skills necessary to thrive in the data-driven world.
Introduction to Pandas
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.
Financial Data 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.
What You Will Learn?
- Successfully install Python on both Windows and macOS systems..
- Create and Manage Virtual Environments.
- Install and set up Jupyter Notebook and navigate its interface efficiently..
- Create and manage Jupyter Notebooks for interactive data analysis..
- Gain an understanding of the Pandas library and its capabilities..
- Create Pandas Series from lists and dictionaries and understand their structure and functionality..
- Access data in Series using labels and positions, and perform slicing operations..
- Create and manipulate DataFrames from various data structures such as dictionaries and lists of dictionaries..
- Efficiently access and manipulate data within DataFrames..
- Download datasets from the internet and load them into Pandas DataFrames for analysis..
- Conduct thorough data inspections and clean data to prepare it for analysis..
- Apply data transformation techniques to reshape and modify datasets..
- Perform detailed analysis on financial data to extract meaningful insights..
- Create compelling visualizations of data using Pandas.
- Apply data analysis skills to real-world datasets and derive actionable insights..
- Implement techniques to improve the quality and reliability of data..
- Develop problem-solving skills to address various data-related challenges..
- Build confidence in your ability to handle complex data analysis tasks independently..