Data Preprocessing with NumPy
This course will guide you through one of Python’s most notable packages – NumPy. We’ll explain why it’s so popular and discuss the numerous applications of its crown jewel – the ndarray class.
with Viktor MehandzhiyskiStart Course
This course is designed to show you how to work with one of Python’s fundamental packages – NumPy. You will learn what a “package” is and see how to install, upgrade and import it. By the time you finish the course, you’ll be comfortable with NumPy’ ndarray class, how to slice and reduce the dimensions of its instances, as well as how to quickly refer to the documentation. Furthermore, you’ll be ready to take advantage of NumPy’s various built-in functions and methods, which we’ll use to generate random and non-random data, import and export data to and from Python, find statistical values for a dataset, and clean and preprocess ndarrays.
Skills you will gain
What You'll Learn
Do you already know how to use Python? Improve your skills by adding another tool to your arsenal – one of the most notable packages, NumPy!
- Introduction to NumPy Free6 Lesson 19 Min
- Why do we use NumPy? Free3 Lesson 20 Min
- NumPy Fundamentals6 Lesson 29 Min
- Working with Arrays4 Lesson 27 Min
- Generating Data with NumPy7 Lesson 32 Min
- Importing and Saving Data with NumPy6 Lesson 39 Min
- Statistics with NumPy8 Lesson 42 Min
- Data Manipulation with NumPy13 Lesson 95 MinChecking for Missing Values in Ndarrays Substituting Missing Values in Ndarrays Reshaping Ndarrays Removing Values from Ndarrays Sorting Ndarrays Argument Sort in NumPy Argument Where in NumPy Shuffling Ndarrays Casting Ndarrays Striping Values from Ndarrays Stacking Ndarrays Concatenating Ndarrays Finding Unique Vaules in Ndarrays
- A Loan Data Practical Example with NumPy15 Lesson 88 MinSetting Up: Introduction to the Practical Example Setting Up: Importing the Data Set Setting Up: Checking for Incomplete Data Setting Up: Splitting the Dataset Setting Up: Creating Checkpoints Manipulating Text Data: Issue Date Manipulating Text Data: Loan Status and Term Manipulating Text Data: Grade and Sub Grade Manipulating Text Data: Verification Status & URL Manipulating Text Data: State Address Manipulating Text Data: Converting Strings and Creating a Checkpoint Manipulating Numeric Data: Substitute Filler Values Manipulating Numeric Data: Currency Change – The Exchange Rate Manipulating Numeric Data: Currency Change - From USD to EUR Completing the Dataset:
“A large portion of a data analyst’s work is dedicated to preprocessing datasets. Unquestionably, this involves tons of mathematical and statistical techniques that NumPy is renowned for. NumPy can be described as a computationally stable state-of-the-art Python instrument that provides flexibility and can take your analysis to the next level.”
Content Creator at 365 Data Science
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Data Preprocessing with NumPy
with Viktor Mehandzhiyski