FlexStack: Python Data Modeling and Visualization 1 - Playing with Pandas

  • Overview
  • Course Content
  • Requirements & Materials
Overview

FlexStack: Python Data Modeling and Visualization 1 - Playing with Pandas

Course Description

The first course in the FlexStack: Python Data Modeling and Visualization Certificate series introduces essential skills for performing data analysis in Python. It introduces learners to the pandas Python library, which is commonly used to load, inspect, clean, and analyze multiple forms of data. The faculty instructor will introduce learners to the properties of and relationships between panda data structures and also teach participants how to perform efficient operations and automate routine data processing. Through hands-on lab sessions, learners will gain confidence in identifying and describing pandas functionalities, understand the importance of data manipulation, and establish a strong foundation in data analysis and data science techniques using Python. This experience will be further enhanced in the next two courses in the series.

Course Content
  • Key features of pandas
  • Data manipulation and processing
  • Hands-on dataset handling
  • Data structure properties
  • Automation and customization
  • Data integrity validation
  • Custom function development
Requirements & Materials

Requirements

Computer, webcam, internet access, and microphone.

Prerequisites

Successful completion of the FlexStack: Python Fundamentals and FlexStack: SQL Fundamentals Certificates or evidence of equivalent skills.

Materials

Supplemental materials provided

Session Details

Who Should Attend

This course is perfect for data analysts, scientists, aspiring data professionals, researchers, software developers, and students. This course is designed to enhance individual skills and help learners gain foundational knowledge in data manipulation, processing, and automation using pandas.

What You Will Learn

  • Key features of the pandas Python library
  • Data manipulation and processing for data analysis
  • Loading, inspecting, and cleaning datasets from different sources and formats
  • Recognition of the properties and relationships of pandas data structures
  • Efficient pandas operations
  • Customization for automating data processing
  • Validation of data integrity and accuracy within modified data
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How You Will Benefit

  • Identify and describe the key features and functionalities of the pandas library.
  • Explain the importance of data manipulation and processing in data analysis and how pandas facilitates these tasks.
  • Use pandas to load, inspect, and clean datasets from various sources (e.g., CSV, Excel, JSON, XML).
  • Examine and interpret data structures in pandas, such as Series and DataFrames, to understand their properties and relationships.
  • Assess the efficiency and performance of different pandas operations for data manipulation tasks.
  • Develop custom functions and scripts using pandas to automate repetitive data processing tasks.
  • Validate the results of data manipulation and processing to ensure data integrity and accuracy.
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