Data Analysis and Visualization with Pandas and Matplotlib

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Bluelime Learning Solutions

1:53:17

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1 - Introduction to Pandas

1 - Introduction.html

2 - Overview of Pandas.html

3 - What is Python.html

4 - Python Installation on Windows.mp4

03:48

5 - What are virtual environments.mp4

01:51

6 - Creating and activating a virtual environment on Windows.mp4

06:43

7 - Python Installation on macOS.html

8 - Creating and activating a virtual environment on macOS.html

9 - What is Jupyter Notebook.html

10 - Installing Pandas and Jupyter Notebook in the Virtual Environment.mp4

01:06

11 - Starting Jupyter Notebook.mp4

05:23

12 - Exploring Jupyter Notebook Server Dashboard Interface.mp4

04:00

13 - Creating a new Notebook.mp4

02:55

14 - Exploring Jupyter Notebook Source and Folder Files.mp4

04:37

15 - Exploring the Notebook Interface.mp4

08:41

2 - Pandas Data Structures

16 - Introduction.html

17 - What is a Series.html

18 - Creating a Pandas Series from a List.mp4

06:04

19 - Creating a Pandas Series from a List with Custom Index.mp4

02:28

20 - Creating a pandas series from a Python Dictionary.mp4

03:34

21 - Accessing Data in a Series using the index by label.mp4

02:14

22 - Accessing Data in a Series By position.mp4

02:15

23 - Slicing a Series by Label.mp4

02:41

24 - What is a DataFrame.html

25 - Creating a DataFrame from a dictionary of lists.mp4

06:32

26 - Creating a DataFrame From a list of dictionaries.mp4

05:03

27 - Accessing data in a DataFrame.mp4

07:45

28 - Manipulating Data in a DataFrame.mp4

04:29

3 - Financial Data Analysis and Visualization

29 - AAPL.csv

29 - Download Dataset.mp4

01:23

30 - Loading Dataset into a DataFrame.mp4

03:40

31 - Inspecting the data.mp4

03:09

32 - Data Cleaning.mp4

06:30

33 - Data transformation and analysis.mp4

07:24

34 - Visualizing data.mp4

09:02

Description

Transforming Raw Data into Actionable Insights using :Python, Pandas, Matplotlib, Pyplot, Juypyter Notebook

What You'll 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.

Who is this for?

Aspiring Data Analysts

Beginners in Programming and Data Science

Professionals Looking to Upskill

Students and Academics

Business Analysts and Managers

Anyone Interested in Data

What You Need to Know?

Basic Computer Skills

Understanding of Basic Programming Concepts (Optional)

A Windows or macOS computer with internet access.

More details

Description
Unlock the full potential of data analysis and visualization with "Data Analysis and Visualization with Pandas and Matplotlib." This course isÂ designed to take you from the very basics of Python setup toÂ financial data insights, equipping you with the skills necessary to thrive in the data-driven world.
Introduction to Pandas
Weâ€™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. Youâ€™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, weâ€™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
Professionals Looking to Upskill
Students and Academics
Business Analysts and Managers
Anyone Interested in Data

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