Data Manipulation in Python: Master Python, Numpy & Pandas

Learn Python, NumPy & Pandas for Data Science: Master essential data manipulation for data science in python

4.37 (1622 reviews)
Udemy
platform
English
language
Data Science
category
instructor
Data Manipulation in Python: Master Python, Numpy & Pandas
117,160
students
4 hours
content
Apr 2022
last update
$49.99
regular price

What you will learn

Learn to use Pandas for Data Analysis

Learn to work with numerical data in Python

Learn statistics and math with Python

Learn how to code in Jupyter Notebook

Learn how to install packages in Python

Description

When it comes to being attractive, data scientists are already there. In a highly competitive job market, it is tough to keep them after they have been hired. People with a unique mix of scientific training, computer expertise, and analytical abilities are hard to find.

Like the Wall Street "quants" of the 1980s and 1990s, modern-day data scientists are expected to have a similar skill set. People with a background in physics and mathematics flocked to investment banks and hedge funds in those days because they could come up with novel algorithms and data methods.


That being said, data science is becoming one of the most well-suited occupations for success in the twenty-first century. It is computerized, programming-driven, and analytical in nature. Consequently, it comes as no surprise that the need for data scientists has been increasing in the employment market over the last several years.

The supply, on the other hand, has been quite restricted. It is challenging to get the knowledge and abilities required to be recruited as a data scientist.

Lots of resources for learning Python are available online. Because of this, students frequently get overwhelmed by Python's high learning curve.


It's a whole new ball game in here! Step-by-step instruction is the hallmark of this course. Throughout each subsequent lesson, we continue to build on what we've previously learned. Our goal is to equip you with all the tools and skills you need to master Python, Numpy & Pandas.

You'll walk away from each video with a fresh idea that you can put to use right away!

All skill levels are welcome in this course, and even if you have no prior programming or statistical experience, you will be able to succeed!

Content

Python Quick Refresher

Introduction to Python
Setting up Python
What is Jupyter?
Anaconda Installation: Windows, Mac & Ubuntu
How to implement Python in Jupyter?
Managing Directories in Jupyter Notebook
Input/Output
Working with different datatypes
Variables
Arithmetic Operators
Comparison Operators
Logical Operators
Conditional statements
Loops
Sequences: Lists
Sequences: Dictionaries
Sequences: Tuples
Functions: Built-in Functions
Functions: User-defined Functions

Essential python libraries for data science

Installing Libraries
Importing Libraries
Pandas Library for Data Science
NumPy Library for Data Science
Pandas vs NumPy
Matplotlib Library for Data Science
Seaborn Library for Data Science

Fundamental NumPy Properties

Introduction to NumPy arrays
Creating NumPy arrays
Indexing NumPy arrays
Array shape
Iterating Over NumPy Arrays

Mathematics for Data Science

Basic NumPy arrays: zeros()
Basic NumPy arrays: ones()
Basic NumPy arrays: full()
Adding a scalar
Subtracting a scalar
Multiplying by a scalar
Dividing by a scalar
Raise to a power
Transpose
Element wise addition
Element wise subtraction
Element wise multiplication
Element wise division
Matrix multiplication
Statistics

Python Pandas DataFrames & Series

What is a Python Pandas DataFrame?
What is a Python Pandas Series?
DataFrame vs Series
Creating a DataFrame using lists
Creating a DataFrame using a dictionary
Loading CSV data into python
Changing the Index Column
Inplace
Examining the DataFrame: Head & Tail
Statistical summary of the DataFrame
Slicing rows using bracket operators
Indexing columns using bracket operators
Boolean list
Filtering Rows
Filtering rows using & and | operators
Filtering data using loc()
Adding and deleting rows and columns
Sorting Values
Exporting and saving pandas DataFrames
Concatenating DataFrames
groupby()

Reviews

Mohd
November 9, 2022
The Course is Extremely helpful to get started with the basics of numpy, pandas, seaborn, matplotlib. Though if you are looking for deep knowledge about these libraries then it's not the course for you The course have sufficiently enough content to get started with these libraries for beginners . With short and precise videos, it helped a lot to get my basics clear in many aspects
Bati
October 14, 2022
It would be great to add forecasting methods to the time series, how to treat multiple dataset with common variables etc
Edwin
October 4, 2022
This course is excellent for people just starting out in data analysis and programming, I would definitely recommend it.
Mukul
October 3, 2022
It's an incredible course, it gives you the basic and necessary knowledge to start in data science domain. Good for beginners and instructor is also great and knowledgeable.
Luis
September 27, 2022
Thank you very much Meta Brains, it is an incredible course, it gives you the basic and necessary knowledge to start learning data science, all the chapters are very well explained. The methods, tips and Python functions used are very useful. I would like you to make a continuation to continue learning how to use Pandas and Numpy.
Alexander
August 29, 2022
The course is ok, but not good, i would give 3-3.5 stars but the pronounciation of array, regex and other makes me so mad that i cannot give more than 2 Stars
Mengxin
August 23, 2022
A quick, compact but informative course to have you quickly learn about the basics on these popular Python libraries.
Ni
August 16, 2022
This course is insightful and enjoyable. But my questions in the Q&A box are not answered. Fortunately, I already found the answer to one of my questions. Thank you so much! I learn a lot from this course
Joshua
August 3, 2022
Course covers a variety of different libraries and functions, and provides sample datasets - which is useful. However, each function is rushed and not explained well and the lectures seldom use the sample data sets, relying on simple lists input by the user. Each function is explained in isolation, and rarely are the functions combined to really show the benefits of using them. The course provides very little in the way of quizzes or labs to test knowledge. The course would benefit greatly by providing a handful of projects or activities along the way where users need to combine all topics to write a useful script.
Mohammad
July 5, 2022
This is a very clear and well managed training for beginners and I really love it please keep it up and provide some trainings about monitoring and evaluation. Best of luck for your nice team.
Daniel
June 29, 2022
It is like the perfect introductory python course: clear, concise and precise, definitely would recommend it to everybody.
Cedric
June 26, 2022
Sometimes its not quit clear where the data was form especially in the last chapter, but overall a good introduction.
Kevin
June 16, 2022
The course is extraordinary, with many very useful tips. The methodology of short but precise and to the point classes is great. Highly recommended!
Bernardo
May 18, 2022
Not only too basic; the examples are too simple; there is nothing challenging about the quiz proposed.
Yianna
May 18, 2022
Content seems quite surface level and doesn't go very in depth. Good as an introduction to these Python libraries.

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4324528
udemy ID
9/28/2021
course created date
11/27/2021
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