Showing posts with label Pandas. Show all posts
Showing posts with label Pandas. Show all posts
The Complete Pandas Bootcamp 2025: Data Science with Python
Tuesday, April 29, 2025
Now with ChatGPT for Pandas, Online Exercises, Seaborn, Machine Learning. Fully Updated (Pandas 3.x) as of Sep 2025
Preview this Course
Description
**Latest course update and full review in September 2024. Now with ChatGPT for Pandas and more than 20 Udemy Online Coding Exercises - NEW Feature**
Welcome to the web´s most comprehensive Pandas Bootcamp. This is the only Pandas course you´ll ever need:
most comprehensive course with 36+ hours of video content
new AI features like Pandas Coding and Advanced Data Analysis with ChatGPT
150+ Coding Exercises (Online and Offline Exercises)
Practical Case Studies for Data Scientists and Finance Professionals
Fully updated to Pandas 2.2 and already anticipating Pandas 3.x
This course has one goal: Bringing your data handling skills to the next level to build your career in Data Science, Machine Learning, Finance & co. It has five parts:
Pandas Basics - from Zero to Hero (Part 1).
The complete data workflow A-Z with Pandas: Importing, Cleaning, Merging, Aggregating, and Preparing Data for Machine Learning. (Part 2)
Two Comprehensive Project Challenges that are frequently used in Data Science job recruiting/assessment centers: Test your skills! (Part 3).
Application 1: Pandas for Finance, Investing and other Time Series Data (Part 4)
Application 2: Machine Learning with Pandas and scikit-learn (Part 5)
Why should you learn Pandas?
The world is getting more and more data-driven. Data Scientists are gaining ground with $100k+ salaries. It´s time to switch from soapbox cars (spreadsheet software like Excel) to High Tuned Racing Cars (Pandas)!
Python is a great platform/environment for Data Science with powerful Tools for Science, Statistics, Finance, and Machine Learning. The Pandas Library is the Heart of Python Data Science. Pandas enables you to import, clean, join/merge/concatenate, manipulate, and deeply understand your Data and finally prepare/process Data for further Statistical Analysis, Machine Learning, or Data Presentation. In reality, all of these tasks require a high proficiency in Pandas! Data Scientists typically spend up to 85% of their time manipulating Data in Pandas.
Can you start right now?
A frequently asked question of Python Beginners is: "Do I need to become an expert in Python coding before I can start working with Pandas?"
The clear answer is: "No! Do you need to become a Microsoft Software Developer before you can start with Excel? Probably not!"
You require some Python Basics like data types, simple operations/operators, lists and numpy arrays. In the Appendix of this course, you can find a Python crash course. This Python Introduction is tailor-made and sufficient for Data Science purposes!
In addition, this course covers fundamental statistical concepts (coding with scipy).
In Summary, if you primarily want to use Python for Data Science or as a replacement for Excel, this course is a perfect match!
Why should you take this Course?
It is the most relevant and comprehensive course on Pandas.
It is the most up-to-date course and the first that covers Pandas Version 2.x. The Pandas Library has experienced massive improvements in the last couple of months. Working with and relying on outdated code can be painful.
Pandas isn´t an isolated tool. It is used together with other Libraries: Matplotlib and Seaborn for Data Visualization | Numpy, Scipy and Scikit-Learn for Machine Learning, scientific, and statistical computing. This course covers all these Libraries.
ChatGPT for Pandas Coding and advanced Data Analytics included!
In real-world projects, coding and the business side of things are equally important. This is probably the only Pandas course that teaches both: in-depth Pandas Coding and Big-Picture Thinking.
It serves as a Pandas Encyclopedia covering all relevant methods, attributes, and workflows for real-world projects. If you have problems with any method or workflow, you will most likely get help and find a solution in this course.
It shows and explains the full real-world Data Workflow A-Z: Starting with importing messy data, cleaning data, merging and concatenating data, grouping and aggregating data, Explanatory Data Analysis through to preparing and processing data for Statistics, Machine Learning, Finance, and Data Presentation.
It explains Pandas Coding on real Data and real-world Problems. No toy data! This is the best way to learn and understand Pandas.
It gives you plenty of opportunities to practice and code on your own. Learning by doing. In the exercises, you can select the level of difficulty with optional hints and guidance/instruction.
Pandas is a very powerful tool. But it also has pitfalls that can lead to unintended and undiscovered errors in your data. This course also focuses on commonly made mistakes and errors and teaches you, what you should not do.
Guaranteed Satisfaction: Otherwise, get your money back with a 30-Days-Money-Back-Guarantee.
I am looking forward to seeing you in the course!
Who this course is for:
- Everyone who want to step into Data Science. Pandas is Key to everything.
- Data Scientists who want to improve their Data Handling/Manipulation skills.
- Everyone who want to switch Data Projects from Excel to more powerful tools (e.g. in Research/Science)
- Investment/Finance Professionals who reached the limits of Excel.
Python Numpy Data Analysis for Data Scientist | AI | ML | DL
Wednesday, January 15, 2025
Unlock the Power of Data Analysis with Python Pandas for Data Science, AI, Machine Learning, and Deep Learning
Preview this Course
Description
Introduction to Python Numpy Data Analysis for Data Scientist | AI | ML | DL
Would want to become a Data Scientist? This course will make your foundation for Data Science, Machine, Learning etc. As this course contains thousands of students enrolled with positive feedback!
The Python Numpy Data Analysis for Data Scientist course is designed to equip learners with the necessary skills for data analysis in the fields of artificial intelligence, machine learning, and deep learning.
This course covers an array of topics such as creating/accessing arrays, indexing, and slicing array dimensions, and ndarray object. Learners will also be taught data types, conversion, and array attributes.
The course further delves into broadcasting, array manipulation, joining, splitting, and transposing operations.
Learners will gain insight into Numpy binary operators, bitwise operations, left and right shifts, string functions, mathematical functions, and trigonometric functions.
Additionally, the course covers arithmetic operations, statistical functions, and counting functions. Sorting, view, copy, and the differences among all copy methods are also covered.
By the end of the course, learners will be proficient in using Python Numpy for data analysis, making them ready to take on the challenges of the data science industry.
What you can do with Pandas Python
Data analysis: Pandas is often used in data analysis to perform tasks such as data cleaning, manipulation, and exploration.
Data visualization: Pandas can be used with visualization libraries such as Matplotlib and Seaborn to create visualizations from data.
Machine learning: Pandas is often used in machine learning workflows to preprocess data before training models.
Financial analysis: Pandas is used in finance to analyze and manipulate financial data.
Social media analysis: Pandas can be used to analyze and manipulate social media data.
Scientific computing: Pandas is used in scientific computing to manipulate and analyze large amounts of data.
Business intelligence: Pandas can be used in business intelligence to analyze and manipulate data for decision-making.
Web scraping: Pandas can be used in web scraping to extract data from web pages and analyze it.
Instructors Experiences and Education:
Faisal Zamir is an experienced programmer and an expert in the field of computer science. He holds a Master's degree in Computer Science and has over 7 years of experience working in schools, colleges, and university. Faisal is a highly skilled instructor who is passionate about teaching and mentoring students in the field of computer science.
As a programmer, Faisal has worked on various projects and has experience in multiple programming languages, including PHP, Java, and Python. He has also worked on projects involving web development, software engineering, and database management. This broad range of experience has allowed Faisal to develop a deep understanding of the fundamentals of programming and the ability to teach complex concepts in an easy-to-understand manner.
As an instructor, Faisal has a proven track record of success. He has taught students of all levels, from beginners to advanced, and has a passion for helping students achieve their goals. Faisal has a unique teaching style that combines theory with practical examples, which allows students to apply what they have learned in real-world scenarios.
Overall, Faisal Zamir is a skilled programmer and a talented instructor who is dedicated to helping students achieve their goals in the field of computer science. With his extensive experience and proven track record of success, students can trust that they are learning from an expert in the field.
What you will learn in this course Python Numpy Data Analysis for Data Scientist
These are the outlines, you can read that will be covered in the course:
Outlines:
Introduction to Numpy - Numpy Environment Setup
Creating / Accessing Arrays - Indexing & Slicing, Array Dimensions (1, 2, 3, ..N), ndarray Object, Data Types, Data Type Conversion
Array Attributes - Array ndarray Object Attributes, Array Creation in Different Ways, Array from Existing Data, Array from Range Function
Broadcasting - Array Iteration, Update Array Values, Broadcasting Iteration
Array Manipulation Operations - Array Joining Operations, Array Transpose Operations, Array Splitting Operations, More Array Operations
Numpy Binary Operators – Binary Operations - bitwise_and, bitwise_or, numpy.invert(), left_shift, right_shift
String Functions - Mathematical Functions, Trigonometric Functions
Arithmetic Operations - Add, Subtract, Multiply, Divide, floor_divide, Power, Mod, Remainder, Reciprocal, Negative, Absolute, Statistical Functions, Counting Functions
Sorting - sort(), argsort(), lexsort(), searchsorted(), partition(), argpartition()
View - Copy
This shows the confidence of the course provider in the quality of their content, and it gives you the opportunity to try out the course risk-free.
So if you're looking to improve your skills in Python data analysis for data science, AI, ML, or DL, this course is definitely worth considering.
Thank you
Faisal Zamir
Who this course is for:
- Data Scientists who need to analyze large data sets and want to use Python's powerful tools for this purpose.
- AI and Machine Learning engineers who want to work with numerical data using Python and Numpy.
- Deep Learning enthusiasts who want to understand the fundamentals of Numpy arrays and use it to manipulate and process image and audio data.
- Researchers who want to use Python and Numpy for scientific computing and numerical analysis.
- Programmers who want to learn a powerful and widely-used library for numerical computing with Python.
- Students who are interested in pursuing a career in Data Science or related fields and want to learn the basics of Numpy for data analysis.
Complete Data Analysis with Pandas : Hands-on Pandas Python
Wednesday, January 11, 2023
Complete Data Analysis with Pandas : Hands-on Pandas Python - Learn in demand skill Pandas, Sci-kit Learn, Numpy For Data Science & Machine Learning : Seaborn | MatplotLib | Python
JOIN OTHER 40,000 SUCCESSFUL STUDENTS WHO HAVE ALREADY ENROLLED & MASTERED PYTHON & PANDAS SKILLS (DATA ANALYSIS LIBRARY) WITH ONE OF MY BEST SELLING, TOP RATED COURSE.
Hi, I am Ankit, one of the Best Selling author on Udemy, taught various courses on Data Science, Python, Pandas, PySpark, Model Deployment.
By the end of this course, you will able to apply all majority of Data analysis function on various different datasets with built in function available in pandas. Analysis techniques like exploratory data analysis, data transformation, data wrangling, time series data analysis, analysis through visualization and many more. Carry on reading to know more about course.
The era of Microsoft Excel is going to be over, so would you like to learn the next generation one of the most powerful data processing tool and in demand skill required for data analyst, data scientist and data engineer. Then this course is for you, welcome to the course on data analysis with python’s most powerful data processing library Pandas.
What you’ll learn
- 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
- Master pandas with quizzes.
- Data Visualization Matplotlib and Seaborn Library
- Importing data from various different kinds of sources
- Complete Machine Learning work flow implementation with Scikit-learn
Pandas & NumPy Python Programming Language Libraries A-Z™
Wednesday, November 2, 2022
Pandas & NumPy Python Programming Language Libraries A-Z™- NumPy & Python Pandas for Python Data Analysis, Data Science, Machine Learning, Deep Learning using Python from scratch
- New
- Created by Oak Academy, Ali̇ CAVDAR
Welcome to the " Pandas & NumPy Python Programming Language Libraries A-Z™ " Course
NumPy & Python Pandas for Python Data Analysis, Data Science, Machine Learning, Deep Learning using Python from scratch
What you'll learn
- Pandas is an open source Python package that is most widely used for data science/data analysis and machine learning tasks.
- Pandas is mainly used for data analysis and associated manipulation of tabular data in DataFrames.
- Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
- Pandas Pyhon aims to be the fundamental high-level building block for doing practical, real world data analysis in Python
- Numpy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices.
- NumPy aims to provide an array object that is up to 50x faster than traditional Python lists.
- NumPy brings the computational power of languages like C and Fortran to Python.
- Installing Anaconda Distribution for Windows
- Installing Anaconda Distribution for MacOs
- Installing Anaconda Distribution for Linux
- Introduction to NumPy Library
- The Power of NumPy
- Creating NumPy Array with The Array() Function
- Creating NumPy Array with Zeros() Function
- Creating NumPy Array with Ones() Function
- Creating NumPy Array with Full() Function
- Creating NumPy Array with Arange() Function
- Creating NumPy Array with Eye() Function
- Creating NumPy Array with Linspace() Function
- Creating NumPy Array with Random() Function
- Properties of NumPy Array
- Reshaping a NumPy Array: Reshape() Function
- Identifying the Largest Element of a Numpy Array: Max(), Argmax() Functions
- Detecting Least Element of Numpy Array: Min(), Argmin() Functions
- Concatenating Numpy Arrays: Concatenate() Function
- Splitting One-Dimensional Numpy Arrays: The Split() Function
- Splitting Two-Dimensional Numpy Arrays: Split(), Vsplit, Hsplit() Function
- Sorting Numpy Arrays: Sort() Function
- Indexing Numpy Arrays
- Slicing One-Dimensional Numpy Arrays
- Slicing Two-Dimensional Numpy Arrays
- Assigning Value to One-Dimensional Arrays
- Assigning Value to Two-Dimensional Array
- Fancy Indexing of One-Dimensional Arrrays
- Fancy Indexing of Two-Dimensional Arrrays
- Combining Fancy Index with Normal Indexing
- Combining Fancy Index with Normal Slicing
- Fancy Indexing of One-Dimensional Arrrays
- Fancy Indexing of Two-Dimensional Arrrays
- Combining Fancy Index with Normal Indexing
- Combining Fancy Index with Normal Slicing
- Introduction to Pandas Library
- Creating a Pandas Series with a List
- Creating a Pandas Series with a Dictionary
- Creating Pandas Series with NumPy Array
- Object Types in Series
- Examining the Primary Features of the Pandas Series
- Most Applied Methods on Pandas Series
- Indexing and Slicing Pandas Series
- Creating Pandas DataFrame with List
- Creating Pandas DataFrame with NumPy Array
- Creating Pandas DataFrame with Dictionary
- Examining the Properties of Pandas DataFrames
- Element Selection Operations in Pandas DataFrames
- Top Level Element Selection in Pandas DataFrames: Structure of loc and iloc
- Element Selection with Conditional Operations in Pandas Data Frames
- Adding Columns to Pandas Data Frames
- Removing Rows and Columns from Pandas Data frames
- Null Values in Pandas Dataframes
- Dropping Null Values: Dropna() Function
- Filling Null Values: Fillna() Function
- Setting Index in Pandas DataFrames
- Multi-Index and Index Hierarchy in Pandas DataFrames
- Element Selection in Multi-Indexed DataFrames
- Selecting Elements Using the xs() Function in Multi-Indexed DataFrames
- Concatenating Pandas Dataframes: Concat Function
- Merge Pandas Dataframes: Merge() Function
- Joining Pandas Dataframes: Join() Function
- Loading a Dataset from the Seaborn Library
- Aggregation Functions in Pandas DataFrames
- Coordinated Use of Grouping and Aggregation Functions in Pandas Dataframes
- Advanced Aggregation Functions: Aggregate() Function
- Advanced Aggregation Functions: Filter() Function
- Advanced Aggregation Functions: Transform() Function
- Advanced Aggregation Functions: Apply() Function
- Pivot Tables in Pandas Library
- Data Entry with Csv and Txt Files
- Data Entry with Excel Files
- Outputting as an CSV Extension
- Outputting as an Excel File
- Basic Knowledge of Python Programming Language
- Basic Knowledge of Numpy Library
- Basic Knowledge of Mathematics
- Watch the course videos completely and in order.
- Internet Connection
- Any device where you can watch the lesson, such as a mobile phone, computer or tablet.
- Determination and patience for learning Pandas Python Programming Language Library.
The Ultimate Pandas Bootcamp: Advanced Python Data Analysis
Wednesday, August 3, 2022
Free Coupon Discount - The Ultimate Pandas Bootcamp: Advanced Python Data Analysis, Master the powerful pandas library to analyze, manipulate and visualize data. More than 10 datasets & bonuses included! | Created by Andy Bek
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Preview this Udemy Course GET COUPON CODE
Description
Welcome to the best resource online for learning and mastering data analysis with pandas and python.
Over 31 hours, 10+ datasets, and 50+ skill challenges, you will gain hands-on mastery of, not only pandas 1.0.x, but also tens of computer science, statistics, and programming concepts.
We will break down, understand, and practice hundreds of methods, attributes, and techniques in pandas and python that will fundamentally change the way you work with data.
In The Ultimate Pandas Bootcamp (2020) you won’t be working with outdated versions of pandas, writing repetitive commands on the same boring dataset. Instead, you’ll learn pandorable and pythonic solutions to interesting, real-world data problems, while working with many diverse datasets that range from wine servings, video game sales, and SAT scores to stock prices, college salaries and more!
Data analysis is an applied science, which is why in each section, you’ll stop and practice what you learn in dedicated skill challenges, followed by detailed solutions where we often consider and compare alternative solutions.
Data analysis is one of the most in-demand skill across all industries and an increasing number of roles. And python is increasingly the language of choice.
Pandas is the wonderful open-source library that is the embodiment of those trends: based on the python programming language, pandas is the de facto data analysis library in the python data science community.
––––– Structure & Curriculum –––––
Over more than 31 hours, we'll cover everything that pandas has to offer, from manipulating series and dataframes, to merging datasets, handling time series, aggregations, filtering, sorting and much more!
The first four sections of the bootcamp constitute the core curriculum. You'll get acquainted with series and dataframes and develop an in-depth understanding of pandas data structures.
· Series at a Glance
· Series Methods and Handling
· Introducing DataFrames
· DataFrames More In Depth
In the next eight sections, you will dive into more advanced topics and take your pandas skills to another level, learning how to work with multiple datasets, manipulate time series, visualize data, write custom functions to transform data and much more.
· Working With Multiple DataFrames
· Going MultiDimensional
· GroupBy And Aggregates
· Reshaping With Pivots
· Working With Dates And Time
· Regular Expressions And Text Manipulation
· Visualizing Data
· Data Formats And I/O
Pandas and python go hand-in-hand which is why this bootcamp also includes a full-length introduction to the python programming language, to get you up and running writing pythonic code in no time.
This is the ultimate course on one of the most-valuable skills today. I hope you commit to mastering data analysis with pandas.
See you inside!
Who this course is for:
Anyone looking to deeply understand and master pandas
Anyone interested in mastering data analysis with python
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Data Analysis with Python: NumPy & Pandas Masterclass
Saturday, July 30, 2022
Data Analysis with Python: NumPy & Pandas Masterclass - Learn NumPy & Pandas for data science, data analysis & business intelligence, with practical, hands-on Python projects!
- New
What you'll learn
- Master the essentials of NumPy and Pandas, two of Python's most powerful data analysis packages
- Learn how to explore, transform, aggregate and join NumPy arrays and Pandas DataFrames
- Analyze and manipulate dates and times for time intelligence and time-series analysis
- Visualize raw data using plot methods and common chart options like line charts, bar charts, scatter plots and histograms
- Import and export flat files, Excel workbooks and SQL database tables using Pandas
- Build powerful, practical skills for modern analytics and business intelligence
Requirements
- We'll use Anaconda & Jupyter Notebooks (a free, user-friendly coding environment)
- Familiarity with base Python is strongly recommended, but not a strict prerequisite
Description
This is a hands-on, project-based course designed to help you master two of the most popular Python packages for data analysis: NumPy and Pandas.
We'll start with a NumPy primer to introduce arrays and array properties, practice common operations like indexing, slicing, filtering and sorting, and explore important concepts like vectorization and broadcasting.
From there we'll dive into Pandas, and focus on the essential tools and methods to explore, analyze, aggregate and transform series and dataframes. You'll practice plotting dataframes with charts and graphs, manipulating time-series data, importing and exporting various file types, and combining dataframes using common join methods.
Throughout the course you'll play the role of Data Analyst for Maven Mega Mart, a large, multinational corporation that operates a chain of retail and grocery stores. Using the Python skills you learn throughout the course, you'll work with members of the Maven Mega Mart team to analyze products, pricing, transactions, and more.
COURSE OUTLINE:
Intro to NumPy & Pandas
Introduce NumPy and Pandas, two critical Python libraries that help structure data in arrays & DataFrames and contain built-in functions for data analysis
Pandas Series
Introduce Pandas Series, the Python equivalent of a column of data, and cover their basic properties, creation, manipulation, and useful functions for analysis
Intro to DataFrames
Work with Pandas DataFrames, the Python equivalent of an Excel or SQL table, and use them to store, manipulate, and analyze data efficiently
Manipulating DataFrames
Aggregate & reshape data in DataFrames by grouping columns, performing aggregation calculations, and pivoting & unpivoting data
Basic Data Visualization
Learn the basics of data visualization in Pandas, and use the plot method to create & customize line charts, bar charts, scatterplots, and histograms
MID-COURSE PROJECT
Put your skills to the test with a brand new dataset, and use your Python skills to analyze and evaluate a new retailer as a potential acquisition target for Maven MegaMart
Analyzing Dates & Times
Learn how to work with the datetime data type in Pandas to extract date components, group by dates, and perform time intelligence calculations like moving averages
Importing & Exporting Data
Read in data from flat files and apply processing steps during import, create DataFrames by querying SQL tables, and write data back out to its source
Joining DataFrames
Combine multiple DataFrames by joining data from related fields to add new columns, and appending data with the same fields to add new rows
FINAL COURSE PROJECT
Put the finishing touches on your project by joining a new table, performing time series analysis, optimizing your workflow, and writing out your results
Join today and get immediate, lifetime access to the following:
13+ hours of high-quality video
Python & Pandas PDF ebook (350+ pages)
Downloadable project files & solutions
Expert support and Q&A forum
30-day Udemy satisfaction guarantee
If you're a data scientist, BI analyst or data engineer looking to add Pandas to your Python skill set, this course is for you.
Happy learning!
-Chris Bruehl (Python Expert & Lead Python Instructor, Maven Analytics)
Who this course is for:
- Analysts or BI professionals looking to learn data analysis with NumPy and Pandas
- Aspiring data scientists who want to build or strengthen their Python skills
- Anyone interested in learning one of the most popular open source programming languages in the world
- Students looking to learn powerful, practical skills with unique, hands-on projects and course demos
Pandas and Scikit-learn For Data Analysis & Machine Learning
Thursday, March 3, 2022
Free Coupon Discount - Pandas and Scikit-learn For Data Analysis & Machine Learning, Learn in demand skill Pandas, Sci-kit Learn, Numpy For Data Science & Machine Learning : Seaborn | MatplotLib | Python
Created by Ankit Mistry Data Science & Machine Learning Academy
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Preview this Udemy Course GET COUPON CODE
Description
JOIN OTHER 30,000 SUCCESSFUL STUDENTS WHO HAVE ALREADY ENROLLED & MASTERED PYTHON & PANDAS SKILLS (DATA ANALYSIS LIBRARY) WITH ONE OF MY BEST SELLING, TOP RATED COURSE.
Student Testimonial :
Great going, ankit is good at explanation of data processing stuff. i bought many of his course related to python and machine learning. - Jay
Every concept is clearly explained and the tutor of this course replies to every question asked in Q&A section. - Mukka Akshay
It was very good session. The instructor has enough knowledge and able to make me understand clearly. Thank you Ankit! - Bibek Baniya
This is an amazing course if you want to understand the extent of the power of Pandas. - Venkat Raj
It's one of the best course !!! Most of the topics has been covered and explained up to the expectation - Ankur SIngh
it is a good match with what i was looking for, the instructor is quite knowledgeable. - Shivi Dhir
This class is not too fast or too slow, the way he teaches is perfect. - Frankie Y
It is excellent - Rakhshee Misbah
good experience - Weiting
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Update : New section on Data visualization library Matplotlib and Seaborn added.
Update : New section on Numpy Library get added.
-----------------------------------------------------------------------------------------------------------
If you want to master most in-demand data analysis library pandas, carry on reading.
Hi, I am Ankit, one of the Best Selling author on Udemy, taught various courses on Data Science, Python, Pandas, PySpark, Model Deployment.
By the end of this course, you will able to apply all majority of Data analysis function on various different datasets with built in function available in pandas. Analysis techniques like exploratory data analysis, data transformation, data wrangling, time series data analysis, analysis through visualization and many more. Carry on reading to know more about course.
The era of Microsoft Excel is going to be over, so would you like to learn the next generation one of the most powerful data processing tool and in demand skill required for data analyst, data scientist and data engineer.
Then this course is for you, welcome to the course on data analysis with python's most powerful data processing library Pandas.
Why this course?
Data scientist is one of the hottest skill of 21st century and many organisation are switching their project from Excel to Pandas the advanced Data analysis tool .
This course is basically design 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.
What is this course?
This course covers
Basics of Pandas library
Python crash course for any of you want refresh basic concept of python
Python anaconda and Pandas installation
Detail understanding about two important data structure available in a Pandas library
Series data type
Data frame data type
How you can group the data for better analysis
How to use Pandas for text processing
How to visualize the data with Pandas inbuilt visualization tool
Multilevel index in Pandas.
Time series analysis
Numerical Python : NumPy Library
Matplotlib and Seaborn for Data visualization
Machine Learning Theoretical background
Complete end to end Machine Learning Model implementation with Scikit-learn API
(from Importing Data to Splitting data, Fitting data and Evaluating Data) & How to Improve Machine Learning Model
Importing Data from various different kind of file
You will get following after enrolling in this course.
150+ HD quality video lecture
16+ hours of content
Discussion forum to resolve your query.
quizzes to to test your understanding
This course is still in a draft mode. I am still adding more and more content, quiz, projects related to data processing with different functionalities of Pandas. So stay tuned and enroll now.
Regards
Ankit Mistry
100% Off Udemy Coupon . Free Udemy Courses . Online Classes
The Complete Pandas Bootcamp 2022: Data Science with Python
Friday, January 14, 2022
Free Coupon Discount - The Complete Pandas Bootcamp 2022: Data Science with Python, Pandas fully explained | NEW Version 1.0 | 150+ Exercises | Must-have skills for Machine Learning & Finance | +Seaborn | Created by Alexander Hagmann
Preview this Udemy Course - GET COUPON CODE
Description
+++++ UPDATE: Pandas Version 1.0 is finally here! This is the first course that covers Pandas 1.0. It gives optimal guidance on how to transition from versions 0.X to 1.0! +++++
Welcome to the web´s most comprehensive Pandas Bootcamp with 30+ hours of structured video content and 150+ exercises!
This course has one goal: Bringing your Data Handling skills to the next level to build your career in Data Science, Machine Learning, Finance & co. This course is structured in four parts, beginning from Zero with all the Pandas Basics (PART 1). PART 2 is the heart of this course and shows the complete data workflow: Importing, Cleaning, Merging, Aggregating, Grouping and Preparing Data for Statistics & Machine Learning. Finally, you can test your new skills in a Comprehensive Project Challenge that is frequently used in Data Science job applications / assessment centres (PART 3). In the last part of this course (PART 4), you will learn how to import, handle and work with (financial) Time Series Data.
Why to take a course on Pandas?
The world is getting more and more Data-Driven. New professions like Data Scientist are gaining ground with $100k+ salaries. It´s time to switch from Soap Box Cars (Spreadsheet Software like Excel) to High Tuned Racing Cars (Pandas)!
Python is a great platform/environment for Data Science with powerful Tools for Science, Statistics and Machine Learning. And the Pandas Library is the Heart of Python Data Science. Pandas enables you to import, clean, join/merge/concatenate, manipulate and deeply understand your Data and finally prepare/process Data for further Statistical Analysis, Machine Learning or Data Presentation. In reality, all of these tasks require high proficiency in Pandas! Data Scientist typically spend up to 85% of their time with manipulating Data in Pandas.
A frequently asked question of Python Beginners is: "Do I need to become a Python Coding Expert before I can start working with Pandas?"
The clear answer is: "No! Do you need to become a Microsoft Software Developer before you can use Excel? Probably not!"
You require some Python Basics like Data Types, simple Operations/Operators, Lists and Numpy Arrays. In the Appendix of this course, you can find 4 hours of Python Basics. This Python Intro is tailor-made and more than sufficient for Data Science purposes!
As a Summary, if you primarily want to use Python for Data Science or as a replacement for Excel, then this course is a perfect match!
Why to take this Course?
- It is the most relevant and comprehensive course on Pandas.
- It is the most up-to-date course and the first that covers Pandas Version 1.0. Pandas Library has experienced massive improvements in the last couple of months. From my own experience, working with and relying on outdated code can be painful.
- It can serve as a Pandas Encyclopedia covering all relevant Methods, Attributes and workflows for real life projects. If you have problems with any Method or workflow, you will most likely get help and find a solution in this course.
-It shows and explains the full real life Data Workflow A-Z, starting from importing messy Data, cleaning Data, merging and concatenating Data, grouping and aggregating Data, explanatory Data Analysis through to preparing and processing Data for Statistics, Machine Learning and Data Presentation.
-It explains Pandas Coding on real Data and real life Problems. No Toy Data! This is the best way to learn and understand Pandas.
-It gives you plenty of opportunities to practise and code on your own. Learning by doing. In the exercises, you can select your individual level of difficulty with optional hints and guidance / instruction.
-Pandas is a very powerful tool. But it also has Pitfalls that can lead to unintended and undiscovered errors in your Data. This course also focuses on commonly made mistakes and errors and teaches you, what you should not do.
- Guaranteed Satisfaction: Otherwise, get your money back with 30-Days-Money-Back-Guarantee.
I am looking forward to seeing you in the course!
Who this course is for:
Everyone who want to step into Data Science. Pandas is Key to everything.
Data Scientists who want to improve their Data Handling/Manipulation skills.
Everyone who want to switch Data Projects from Excel to more powerful tools (e.g. in Research/Science)
Investment/Finance Professionals who reached the limits of Excel.
100% Off Udemy Coupon . Free Udemy Courses . Online Classes
Pandas library for data science (All in One)
Saturday, June 12, 2021
Pandas library for data science (All in One) - learn pandas and it's functions by working on a dataset and by making your own dataframe
- New
- Created by Shambhavi Gupta
- English [Auto]
What you'll learn
- Learn methods and attributes across numerous pandas functions
- Perform the functions of data operations in Python's popular "pandas" library including filling null values, performing statistical functions and much more!
- Defining your own datasets using pandas and numpy library
- Learn functions important for data manipulation
- Learn and master the most important Pandas functions
- Bring your Data Handling & Data Analysis skills to an outstanding level.
- Update your resume with one of the in demand skill : Data analysis Pandas
- Detect and intelligently fill missing values.
Description
Data scientists spend only 20 percent of their time on building machine learning algorithms and 80 percent of their time finding, cleaning, and reorganizing huge amounts of data. That mostly happen because many use graphical tools such as Excel to process their data. However, if you use a programming language such as Python you can drastically reduce the time it takes for processing your data and make them ready for use in your project. This course will show how Python can be used to manage, clean, and organize huge amounts of data.
By the end of this course, you will be able to apply all majority of Data analysis function on various different datasets with built in function available in pandas
Why this course?
Data scientist is one of the hottest skill of 21st century and many organization are switching their project from Excel to Pandas the advanced Data analysis tool .
This course is basically design 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.
What is this course?
This course covers
Basics of Pandas library
Functions of pandas library
making your own data frame using Numpy and pandas
applying data manipulation functions
finding the null values
filling null values using various functions
applying statistical functions
Who this course is for:
python developers curious about data science
everyone who wants to improve their Python programming skills
everyone who wants to improve their data science skills
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Complete Data Analysis with Pandas : Hands-on Pandas Python
Monday, May 3, 2021
Complete Data Analysis with Pandas : Hands-on Pandas Python - Learn in demand skill Pandas, Sci-kit Learn, Numpy For Data Science & Machine Learning : Seaborn | MatplotLib | Python
- Created by Ankit Mistry, Data Science & Machine Learning Academy
- English [Auto]
What you'll learn
- 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
- Master pandas with quizzes.
- Data Visualization Matplotlib and Seaborn Library
- Importing data from various different kinds of sources
- Complete Machine Learning work flow implementation with Scikit-learn
Description
JOIN OTHER 40,000 SUCCESSFUL STUDENTS WHO HAVE ALREADY ENROLLED & MASTERED PYTHON & PANDAS SKILLS (DATA ANALYSIS LIBRARY) WITH ONE OF MY BEST SELLING, TOP RATED COURSE.
Student Testimonial :
Great going, ankit is good at explanation of data processing stuff. i bought many of his course related to python and machine learning. - Jay
Every concept is clearly explained and the tutor of this course replies to every question asked in Q&A section. - Mukka Akshay
It was very good session. The instructor has enough knowledge and able to make me understand clearly. Thank you Ankit! - Bibek Baniya
This is an amazing course if you want to understand the extent of the power of Pandas. - Venkat Raj
It's one of the best course !!! Most of the topics has been covered and explained up to the expectation - Ankur SIngh
it is a good match with what i was looking for, the instructor is quite knowledgeable. - Shivi Dhir
This class is not too fast or too slow, the way he teaches is perfect. - Frankie Y
It is excellent - Rakhshee Misbah
good experience - Weiting
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Update : New section on Data visualization library Matplotlib and Seaborn added.
Update : New section on Numpy Library get added.
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If you want to master most in-demand data analysis library pandas, carry on reading.
Hi, I am Ankit, one of the Best Selling author on Udemy, taught various courses on Data Science, Python, Pandas, PySpark, Model Deployment.
By the end of this course, you will able to apply all majority of Data analysis function on various different datasets with built in function available in pandas. Analysis techniques like exploratory data analysis, data transformation, data wrangling, time series data analysis, analysis through visualization and many more. Carry on reading to know more about course.
The era of Microsoft Excel is going to be over, so would you like to learn the next generation one of the most powerful data processing tool and in demand skill required for data analyst, data scientist and data engineer.
Then this course is for you, welcome to the course on data analysis with python's most powerful data processing library Pandas.
Why this course?
Data scientist is one of the hottest skill of 21st century and many organisation are switching their project from Excel to Pandas the advanced Data analysis tool .
This course is basically design 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.
What is this course?
This course covers
Basics of Pandas library
Python crash course for any of you want refresh basic concept of python
Python anaconda and Pandas installation
Detail understanding about two important data structure available in a Pandas library
Series data type
Data frame data type
How you can group the data for better analysis
How to use Pandas for text processing
How to visualize the data with Pandas inbuilt visualization tool
Multilevel index in Pandas.
Time series analysis
Numerical Python : NumPy Library
Matplotlib and Seaborn for Data visualization
Machine Learning Theoretical background
Complete end to end Machine Learning Model implementation with Scikit-learn API
(from Importing Data to Splitting data, Fitting data and Evaluating Data) & How to Improve Machine Learning Model
Importing Data from various different kind of file
You will get following after enrolling in this course.
150+ HD quality video lecture
16+ hours of content
Discussion forum to resolve your query.
quizzes to to test your understanding
This course is still in a draft mode. I am still adding more and more content, quiz, projects related to data processing with different functionalities of Pandas. So stay tuned and enroll now.
Regards
Ankit Mistry
Who this course is for:
Beginner Python developer who is curious about Data Science, Not for experienced Data Scientist
Anyone who want to make career in Data Science, Data analytics
Anyone wants to learn data analysis with python language
Excel user who wants to enhance data analysis skills.
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