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Python Pandas

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Beginner

Enroll in this Python Pandas course to improve your Python skills and learn about Pandas and Dataframes. Gain knowledge on Dataframe methods and operations to effectively manipulate and analyze data.

What you learn in Python Pandas ?

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Introduction to Pandas and DataFrames
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Understanding the Usage of DataFrames
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Various DataFrame methods and Operations
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Selecting and Indexing Operations
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Pandas Aggregation Operations

About this Free Certificate Course

Python Pandas is the focus of this course, where you'll dive into the powerful and widely used library for data manipulation and analysis in Python. You'll start with an introduction to the Pandas Series data structure, followed by an exploration of DataFrames, two-dimensional labeled data structures. The course covers various DataFrame methods and operations, such as data cleaning, merging, and reshaping, which are essential for working with data in a DataFrame. Additionally, you'll learn about selecting and indexing operations to access, manipulate, and analyze data. Lastly, you'll gain an understanding of Pandas aggregation operations to summarize and group data in a DataFrame. By the end of this course, you'll have the necessary skills to use Python Pandas to solve real-world problems related to data manipulation and analysis.

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Course Outline

Introduction to Pandas and DataFrames
Working with the Pandas Series Data Structure
Understanding the usage of DataFrames
Various DataFrame Methods and Operations
Selecting and Indexing Operations
Pandas Aggregation Operations

Our course instructor

Mr. Bharani Akella

Data Scientist

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2.9M+ Learners
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82 Courses
Bharani has been working in the field of data science for the last 2 years. He has expertise in languages such as Python, R and Java. He also has expertise in the field of deep learning and has worked with deep learning frameworks such as Keras and TensorFlow. He has been in the technical content side from last 2 years and has taught numerous classes with respect to data science.

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Python Pandas

With this course, you get

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Free lifetime access

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Completion Certificate

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1.5 Hours

of self-paced video lectures

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Frequently Asked Questions

What are Python pandas used for?

Pandas library is mainly used for data analysis and data manipulation

Is Python Panda Free?

Yes, Pandas library is free to learn.

Are Python pandas better than Excel?

Yes, it is being proved that pandas are faster than Excel. Moreover, Python is free to use, which costs nothing. 

What is the best way to learn Pandas?

The best way to learn Pandas is to learn the basics of it and have hands-on in Pandas.

Are Python Pandas hard to learn?

No, Python Pandas is not hard to learn. It is considered to be moderate and one can get familiar with this library pretty well with practice.

How long does it take to learn Pandas in Python?

Assuming you already know python, it might take two to three weeks, depending on the time spent on learning.

Will I get a certificate after completing this Python Pandas free course?

Yes, you will get a certificate of completion for Python Pandas after completing all the modules and cracking the assessment. The assessment tests your knowledge of the subject and badges your skills.

How much does this Python Pandas course cost?

It is an entirely free course from Great Learning Academy. anyone interested in learning the basics of Python Pandas can get started with this course.

Is there any limit on how many times I can take this free course?

Once you enroll in the Python Pandas course, you have lifetime access to it. So, you can log in anytime and learn it for free online.

Can I sign up for multiple courses from Great Learning Academy at the same time?

Yes, you can enroll in as many courses as you want from Great Learning Academy. There is no limit to the number of courses you can enroll in at once, but since the courses offered by Great Learning Academy are free, we suggest you learn one by one to get the best out of the subject.

Why choose Great Learning Academy for this free Python Pandas course?

Great Learning Academy provides this Python Pandas course for free online. The course is self-paced and helps you understand various topics that fall under the subject with solved problems and demonstrated examples. The course is carefully designed, keeping in mind to cater to both beginners and professionals, and is delivered by subject experts. Great Learning is a global ed-tech platform dedicated to developing competent professionals. Great Learning Academy is an initiative by Great Learning that offers in-demand free online courses to help people advance in their jobs. More than 5 million learners from 140 countries have benefited from Great Learning Academy's free online courses with certificates. It is a one-stop place for all of a learner's goals.

What are the steps to enroll in this Python Pandas course?

Enrolling in any of the Great Learning Academy’s courses is just one step process. Sign-up for the course, you are interested in learning through your E-mail ID and start learning them for free online.

Will I have lifetime access to this free Python Pandas course?

Yes, once you enroll in the course, you will have lifetime access, where you can log in and learn whenever you want to. 

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Python Pandas

Python is a high-level, general-purpose programming language that is widely used for a variety of tasks such as web development, machine learning, data analysis, and more. One of the most popular libraries for data analysis in Python is Pandas.

Pandas is a library that provides data structures for effectively handling and manipulating data in Python. It is built on top of NumPy, another popular library for numerical computing in Python. Pandas provide two primary data structures: Series and DataFrame.

A Series is a one-dimensional labeled array that can hold any data type, including integers, floats, strings, and more. It is similar to a column in a spreadsheet or a SQL table. A DataFrame, on the other hand, is a two-dimensional labeled data structure that can hold multiple Series. It is similar to a spreadsheet or a SQL table.

Pandas is an essential tool for data analysis in Python, and it provides a variety of methods and operations that make it easy to manipulate and analyze data. Some of the essential topics that you'll learn about in a Python Pandas course include:

Data Cleaning: Cleaning and pre-processing data is often the first step in any data analysis project. Pandas provides various methods for cleaning and transforming data, such as dropping missing values, replacing values, and more.

Data Manipulation: Pandas provides many methods for manipulating and transforming data, such as merging, grouping, and pivoting data. These methods make it easy to transform data into the format you need for analysis.

Data Visualization: Pandas integrates with other popular data visualization libraries in Python, such as Matplotlib and Seaborn, to create high-quality visualizations of your data. You'll learn how to create different types of charts and graphs, including line charts, bar charts, and scatterplots.

Time Series Analysis: Pandas provides functionality for working with time-series data, such as resampling and shifting data, and calculating rolling statistics. Time series analysis is essential in fields such as finance, economics, and climate science.

Data Aggregation: Pandas provides various methods for aggregating and summarizing data, such as calculating mean, median, and standard deviation, and more. These methods make it easy to summarize and analyze large datasets.

In summary, Python is a versatile programming language that is widely used for data analysis, and Pandas is a powerful library for manipulating and analyzing data in Python. A Python Pandas course will equip you with the essential skills to work with data in Python effectively. You'll learn how to clean and transform data, create visualizations, perform time series analysis, and more. With the knowledge gained in a Python Pandas course, you'll be able to solve real-world problems related to data analysis and make informed decisions based on your analysis.

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