The Ultimate Python Library Pandas Training Course

The Ultimate Python Library Pandas Training Course

This course will teach you how to tackle modern data problems and derive value from complex datasets using pandas.

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You'll learn  The Ultimate Python Library Pandas Training Course

• Up and running with pandas
• Pandas and Data Science and Analysis
• Representing univariate data with the Series
• Representing tabular and multivariate data with the DataFrame
• Manipulation and indexing of DataFrame objects
• Indexing Data
• Categorical Data
• Numeric and Statistical Methods
• Grouping and Aggregating Data
• Combining, Relating and Reshaping Data

Welcome to this course. The pandas library is massive

, and it’s common for frequent users to be unaware of many of its more impressive features. Pandas is a popular Python library used by data scientists and analysts worldwide to manipulate and analyze their data. This course presents useful data manipulation techniques in pandas to perform complex data analysis in various domains. This course will teach you how to be more productive with data and generate real business insights to inform your decision-making. You will be guided through real-world data science problems and shown how to apply key techniques in the context of realistic examples and exercises. Engaging activities will then challenge you to apply your new skills in a way that prepares you for real data science projects.

You’ll see how experienced data scientists tackle a wide range of problems using data analysis with pandas. You will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance.

In this course, you'll learn:

Learn How to Access and load data from different sources using pandas

Master the fundamentals of pandas to quickly begin exploring any dataset

Isolate any subset of data by properly selecting and querying the data

Work with a range of data types and structures to understand your data

Split data into independent groups before applying aggregations and transformations to each group

Restructure data into tidy form to make data analysis and visualization easier

Perform data transformation to prepare it for analysis

Prepare real-world messy datasets for machine learning

Combine and merge data from different sources through pandas SQL-like operations

Use Matplotlib for data visualization to create a variety of plots

Create data models to find relationships and test hypotheses

Manipulate time-series data to perform date-time calculations

Utilize pandas unparalleled time series functionality

Create beautiful and insightful visualizations through pandas direct hooks to Matplotlib and Seaborn

Optimize your code to ensure more efficient business data analysis

At the end of this course, you’ll have the knowledge, skills, and confidence you need to solve your own challenging data science problems with pandas.