Data Analysis and Visualization with Pandas and Matplotlib

Data Analysis and Visualization with Pandas and Matplotlib, available at $54.99, has an average rating of 4.52, with 34 lectures, based on 22 reviews, and has 815 subscribers.

You will learn about 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. This course is ideal for individuals who are Aspiring Data Analysts or Beginners in Programming and Data Science or Professionals Looking to Upskill or Students and Academics or Business Analysts and Managers or Anyone Interested in Data It is particularly useful for Aspiring Data Analysts or Beginners in Programming and Data Science or Professionals Looking to Upskill or Students and Academics or Business Analysts and Managers or Anyone Interested in Data.

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Summary

Title: Data Analysis and Visualization with Pandas and Matplotlib

Price: $54.99

Average Rating: 4.52

Number of Lectures: 34

Number of Published Lectures: 34

Number of Curriculum Items: 34

Number of Published Curriculum Objects: 34

Original Price: $27.99

Quality Status: approved

Status: Live

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.

Who Should Attend

• Aspiring Data Analysts
• Beginners in Programming and Data Science
• Professionals Looking to Upskill
• Students and Academics
• Business Analysts and Managers
• Anyone Interested in Data

Target Audiences

• Aspiring Data Analysts
• Beginners in Programming and Data Science
• Professionals Looking to Upskill
• Students and Academics
• Business Analysts and Managers
• Anyone Interested in Data