Data Manipulation in Python: A Pandas Crash Course

Data Manipulation in Python: A Pandas Crash Course, available at $44.99, has an average rating of 5, with 27 lectures, based on 16 reviews, and has 45 subscribers.

You will learn about Learn how to use Python and Pandas for data analysis and data manipulation. Transform, clean and merge data with Python. Data Visualization with Python Create, save and serialise data frames in and out of multiple formats. Detect and intelligently fill missing values. Merge data sources into a beautiful whole. Seamlessly work with data from different time zones. Learn the common pitfalls and traps that ensnare beginners and how to avoid them. This course is ideal for individuals who are Python students that want to learn how to manipulate data professionally. Aspiring data analysts and scientists looking to upgrade their skillset. People who would prefer to spend more time solving interesting problems than formatting data. Old hands at programming that want to see what new methods and industry-leading tools are at their fingertips in the new decade. It is particularly useful for Python students that want to learn how to manipulate data professionally. Aspiring data analysts and scientists looking to upgrade their skillset. People who would prefer to spend more time solving interesting problems than formatting data. Old hands at programming that want to see what new methods and industry-leading tools are at their fingertips in the new decade.

Enroll now: Data Manipulation in Python: A Pandas Crash Course

Summary

Title: Data Manipulation in Python: A Pandas Crash Course

Price: $44.99

Average Rating: 5

Number of Lectures: 27

Number of Published Lectures: 27

Number of Curriculum Items: 27

Number of Published Curriculum Objects: 27

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Learn how to use Python and Pandas for data analysis and data manipulation. Transform, clean and merge data with Python.
Data Visualization with Python
Create, save and serialise data frames in and out of multiple formats.
Detect and intelligently fill missing values.
Merge data sources into a beautiful whole.
Seamlessly work with data from different time zones.
Learn the common pitfalls and traps that ensnare beginners and how to avoid them.

Who Should Attend

Python students that want to learn how to manipulate data professionally. Aspiring data analysts and scientists looking to upgrade their skillset. People who would prefer to spend more time solving interesting problems than formatting data. Old hands at programming that want to see what new methods and industry-leading tools are at their fingertips in the new decade.

Target Audiences

Python students that want to learn how to manipulate data professionally. Aspiring data analysts and scientists looking to upgrade their skillset. People who would prefer to spend more time solving interesting problems than formatting data. Old hands at programming that want to see what new methods and industry-leading tools are at their fingertips in the new decade.

n the real-world, data is anything but clean, which is why Python libraries like Pandas are so valuable.

If data manipulation is setting your data analysis workflow behind then this course is the key to taking your power back.

Own your data, don’t let your data own you!

When data manipulation and preparation accounts for up to 80% of your work as a data scientist, learning data munging techniques that take raw data to a final product for analysis as efficiently as possible is essential for success.

Data analysis with Python library Pandas makes it easier for you to achieve better results, increase your productivity, spend more time problem-solving and less time data-wrangling, and communicate your insights more effectively.

This course prepares you to do just that!

With Pandas DataFrame, prepare to learn advanced data manipulation, preparation, sorting, blending, and data cleaning approaches to turn chaotic bits of data into a final pre-analysis product. This is exactly why Pandas is the most popular Python library in data science and why data scientists at Google, Facebook, JP Morgan, and nearly every other major company that analyzes data use Pandas.

If you want to learn how to efficiently utilize Pandas to manipulate, transform, pivot, stack, merge and aggregate your data for preparation of visualization, statistical analysis, or machine learning, then this course is for you.

Here’s what you can expect when you enrolled with your instructor, Ph.D. Samuel Hinton:

Learn common and advanced Pandas data manipulation techniques to take raw data to a final product for analysis as efficiently as possible.
Achieve better results by spending more time problem-solving and less time data-wrangling.
Learn how to shape and manipulate data to make statistical analysis and machine learning as simple as possible.
Utilize the latest version of Python and the industry-standard Pandas library.

Performing data analysis with Python’s Pandas library can help you do a lot, but it does have its downsides. And this course helps you beat them head-on:

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Introduction to Data Analysis

Lecture 3: Real Time Business Intelligence Problems

Lecture 4: Introduction to Pandas Library

Lecture 5: Python & Jupyter NoteBook Installation

Chapter 2: Data Manipulation with Pandas

Lecture 1: Importing Libraries in JupyterNote Book

Lecture 2: How to View Dataset

Lecture 3: How to fetch Columns

Lecture 4: How to Perform Descriptive Analysis

Lecture 5: How to Identify Unique Values

Lecture 6: How to Filter the dataset

Lecture 7: How to filter Specific Numbers of Records

Lecture 8: How to Apply Logical Condition

Lecture 9: How to Replace Null Values

Chapter 3: Data Visualization with Pandas

Lecture 1: How to Create Count plot

Lecture 2: How to Create Histogram

Lecture 3: How to Create Bar Plot

Lecture 4: How to create Bar Plot Example

Lecture 5: How to Create Scatter Plot

Lecture 6: How to Create Box Plot

Lecture 7: Pandas Library chearsheet

Lecture 8: What is Data Cleaning

Lecture 9: Data Cleaning with Examples

Chapter 4: EDA with AIPRM Chat GPT Hands on Tasks

Lecture 1: EDA Analysis with Chat GPT

Chapter 5: Final Assignment

Lecture 1: Final Assignment

Chapter 6: Data Analysis with Power Query

Lecture 1: Live Data Analysis with Power Query ( Ms Excel)

Lecture 2: How to Append Multiple Excel Sheets

Instructors

Asim Noaman Lodhi
Certified Google Partner, Digital Marketer, QA Consultant

Rating Distribution

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5 stars: 16 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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