The best online Courses & Tutorials to learn Panda for beginners to advanced level.

Pandas DataFrames are the most widely used in-memory representation of complex data collections within Python. Whether in finance, scientific fields, or data science, a familiarity with Pandas is essential.

Today, the demand for Panda is really high in the market. You can find plenty of online courses that will help you learn Panda efficiently. Learn about Panda essentials with these top Panda tutorials and enhance your skills.

Top Panda Courses, Tutorials List

  1. Ultimate Pandas and Python Data Analysis (Complete Course)
  2. The Complete Pandas Bootcamp: Master your Data in Python.
  3. Data Analysis with Pandas
  4. Introduction to Data Science in Python
  5. Complete Data Analysis Course with Pandas & NumPy : Python
  6. Data Wrangling with Pandas for Machine Learning Engineers
  7. Data Science And Analysis: Make DataFrames in Pandas And Python
  8. Python Pandas: connect & import directly any database

1. Ultimate Pandas and Python Data Analysis (Complete Course)

Analyze data quickly and easily with Python's powerful pandas library! All datasets included - beginners welcome!

⭐: 4.6 (5,982 ratings)

With this course, you will:

  • Perform a multitude of data operations in Python's popular "pandas" library including grouping, pivoting, joining and more
  • Learn hundreds of methods and attributes across numerous pandas objects
  • Possess a strong understanding of manipulating 1D, 2D, and 3D data sets
  • Resolve common issues in broken or incomplete data sets

This course will give you insights on how Pandas is a powerhouse tool that allows you to do anything and everything with colossal data sets analyzing, organizing, sorting, filtering, pivoting, aggregating, munging, cleaning, calculating, and more.

You can take Ultimate Pandas and Python Data Analysis (Complete Course)  on Udemy.

2.The Complete Pandas Bootcamp: Master your Data in Python.

Pandas fully explained. Real Data. 150+ Exercises. Must-have skills for Data Science and Finance. Seaborn & Time Series.

In this course, you will:

⭐: 4.6 (303 ratings)

  • Improve your Data Handling skills to an outstanding level
  • Learn and practice all relevant Pandas Methods and workflows based on latest Pandas Version (March 2019)
  • Import, clean and merge messy Data and prepare Data for Machine Learning
  • Analyze, visualize and understand your Data with Matplotlib and Seaborn
  • Import Financial/Stock Data from Web Sources and analyze them with Pandas
  • Practise and Master Pandas skills with Quizzes, 150+ Exercises and comprehensive projects

This course has a goal to bring your Data Handling skills to the next level to build your career in Data Science, Finance & co. This course is structured in four parts, beginning from Zero with all the Pandas Basics (PART I), and finally, testing your skills in a comprehensive Project Challenge that is frequently used in Data Science job applications / assessment centres (PART III). In the last part of this course (PART IV), you will learn how to import, handle and work with (financial) Time Series Data.

You can take Data Analysis with Pandas on Udemy.

3.Data Analysis with Pandas

Learn the basics of Pandas, an industry standard Python library that provides tools for data manipulation and analysis.

In this course, you will learn Pandas, ingest, clean, and aggregate large quantities of data, and then use that data with other Python modules like Scipy (for statistical analysis) or Matplotlib (for visualization).

This course will cover how to create Pandas DataFrames, calculate aggregates, and merge multiple tables.Pandas provides tools for working with tabular data, i.e. data that is organized into tables that have rows and columns. Tabular data has a lot of the same functionality as SQL or Excel, but Pandas adds the power of Python.

You can take Data Analysis with Pandas on Codecademy.

4. Introduction to Data Science in Python

Learn Introduction to Data Science in Python from University of Michigan. This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files.

⭐: 4.5 (11,598 ratings)

In this course, you will:

  • Describe common Python functionality and features used for data science
  • Explain distributions, sampling, and t-tests
  • Query DataFrame structures for cleaning and processing
  • Understand techniques such as lambdas and manipulating csv files

The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively.

You can take Introduction to Data Science in Python on Coursera.

5.Complete Data Analysis Course with Pandas & NumPy : Python

Learn most in demand skill in space of Data Science, Data analytics : Data analysis library Pandas & NumPy - Python

⭐: 4.6 (112 ratings)

In this course, you will:

  • Update your resume with one of the in demand skill : Data analysis Pandas
  • Setting up Python in anaconda environment
  • Refresh Python basics with crash course
  • Learn Most demanded python data analysis library : Pandas
  • Three important data structure of pandas : Series, Data Frame, Panel
  • Learn how to analyse one, two and three dimensional data
  • How to group Data for analysis
  • How to deal with Text Data with Pandas Functions
  • Analyse data having multiple level index.
  • Array and Matrix manipulation Library NumPy

This course is basically designed to get you started with Pandas library at beginner level, covering majority of important concepts of data processing data analysis and a Pandas library and make you feel confident about data processing task with Pandas at advanced level.

You can take Complete Data Analysis Course with Pandas & NumPy : Python  on Udemy.

6.Data Wrangling with Pandas for Machine Learning Engineers

Pandas has become the gold standard for data wrangling in applied machine learning. This course will teach you the basics of data wrangling in Python using Pandas, including basic syntax, functions, and dataframe manipulation.

⭐: 4(22 ratings)

In this course, you will:

  • Create dataframes with pandas
  • Recognize analytical approaches to data
  • Learn game design fundamentals
  • Code in C#

This curse is designed to teach the core of applied machine learning thorough knowledge of data wrangling. In this course, Data Wrangling with Pandas for Machine Learning Engineers, you will learn how to massage data into a modellable state. First, you will discover what data wrangling is and its importance to the machine learning process. Next, you will explore the Pandas DataFrame and see how data is manipulated within the DataFrame. Finally, you will learn how to build an accurate model with the cleansed dataset. When you are finished with this course, you will have a foundational knowledge of data wrangling that will help you as you move forward to becoming a machine learning engineer.

You can take Data Wrangling with Pandas for Machine Learning Engineers on Pluralsight.

7.Data Science And Analysis: Make DataFrames in Pandas And Python

Learn to code in Python and analyze data using the pandas dataframe! Complete with practical projects. Learn to code.

⭐: 4.4 (372 reviews)

This course is designed for beginners because we begin with a complete introduction to coding. Then we delve deep into using pandas, an open source library with high-performance and easy-to-use data structures and data analysis tools written for Python.

In Part 1, you learn how to use Python, a popular coding language used for websites like YouTube and Instagram. You learn the basics of programming, including topics like variables, functions, and if statements. You learn about data structures such as lists, dictionaries, and sets. We cover how to use for and while loops, how to handle user input and output, file input and output. We apply our knowledge to build a fully functional tic-tac-toe game. Learn classes, methods, attributes, instancing, and class inheritance.

In Part 2, you take your Python knowledge and apply it to the pandas framework. You learn how to create and expand a dataframe. You learn how to get values from data and how to handle NaN values. You learn how to read and write data from and to the comma-separated values (CSV) file format. Then we take different approaches to analyzing data.

You can take Data Science And Analysis: Make DataFrames in Pandas And Python  on Eduonix.

8.Python Pandas: connect & import directly any database

ORACLE Database, IBM Db2, MS SQL Server, MySQL, Postgresql, SQLite

⭐: 4.4 (47 ratings)

In this course, you will:

  • Know how to install major database software: Oracle Database, IBM Db2, MS SQL Server, MySQL, PostgreSQL, SQLite
  • Know how to install management tools for each database software: Oracle SQL
  • Learn developer, IBM Data Studio, SSMS, MySQL Workbench, pgAdmin, DB Browser for SQLite
  • Know where to find sample databases for each and how to import them
  • Know how to connect directly with Python to each database
  • Know how to import data directly to Pandas DataFrames

The course is designed to teach you how to connect and import directly from ORACLE Database, IBM DB2, MS SQL Server, MySQL, Postgresql, and SQLite, and you will know how to deal with tricky connection parameter and where to find them. This course is design for you to stand out from the crowd.

You can take Python Pandas: connect & import directly any database on Udemy.

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