Python Data Analysis and Visualization | Codefinity
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# Python Data Analysis and Visualization

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Track curriculum encompasses a collection of pivotal courses that provide foundational knowledge and skills essential for a successful journey in the field of data science. These courses encompass the comprehensive study of key concepts, tools, and methodologies integral to the realm of data analysis and modeling. Show more
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What you will learn
• Gain a solid foundation in NumPy Basics, starting with array creation and advancing to master indexing and slicing for data manipulation.
• Understand commonly used NumPy functions to perform complex numerical computations with ease.
• Explore mathematical operations within NumPy, equipping you with the skills to apply statistical operations and basic linear algebra.
• Acquire expertise in handling missing values, reshaping arrays, and broadcasting operations fundamental for machine learning and scientific computing.
• 168 chapters
• 19 hours
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Learning track content
Module 1 / Ultimate NumPy
First of all, we will discuss the applications of NumPy and why it is popular. Afterwards you will learn various possible options to create different arrays in NumPy.
It's now time to learn how to use index notation to retrieve specific elements or subsets of data from arrays. You will also learn how to use indices to retrieve data based on certain conditions and handle missing values.
There are quite few of common operations on arrays which you may want to perform. Luckily, NumPy has built-in functions and methods for this purpose which you will learn here.
It's time to discover how to efficiently use mathematical operations on NumPy arrays and apply them in some real-world problems.
Module 2 / Pandas First Steps
In this section, we'll explore the fundamentals of Series and DataFrame structures. You'll also learn about the distinctions between these two types of structures.
Data can be sourced in various formats, such as CSV, JSON, SQL, HTML, and more. With Pandas, you're not limited to a single format — you can work with data across a multitude of file types. In this chapter, we'll specifically focus on the CSV and TXT formats.
Here, you'll learn how to process raw data by removing extraneous information and managing null values in a dataset.
Module 3 / Advanced Techniques in pandas
This section will teach you how to output specific columns by their titles or indices. Also, you will get acquainted with the ways you can select rows by indices.
Here, you will learn how to extract data that has specific conditions. Also, you will learn how to combine them and even create your own.
In this section, you will expand your knowledge on setting different data conditions. You will learn to check if your data is in a defined list of values or between two values. You will also learn how to find the largest and smallest values.
This section is one of the most fascinating of the course. Here, you will learn how to group data in different ways. It will help you work as a data analyst to find out information on specific data groups.
This section is one of the most significant for a data analyst because if the data contains missing data values in the incorrect format, it will be impossible to work with. Thus, you will learn how to deal with such inappropriate values here.
Module 4 / Mathematics for Data Analysis and Modeling
Let's start with some basic definitions and concepts we'll use later. Consider the idea of a function, a numerical sequence, and its sum, and also understand what a coordinate system's basis is.
The simplest and most commonly used type of relationship is the linear relationship. Linear algebra is a branch of higher mathematics entirely devoted to linear functions and linear spaces. Let's look at some of the most important topics in linear algebra: vectors, matrices, solving linear equations, and solving the spectral problem for matrices.
Mathematical analysis is a discipline that allows you to analyze functions according to various criteria. Consider how to check numerical sequences for convergence, find the maximum/minimum values of functions, solve nonlinear equations, and use integrals to solve applied problems.
Module 5 / Probability Theory Basics
We will start our way of learning probability theory by considering some basic definitions and rules: what is a stochastic experiment and random event, what is independence and incompatibility of events in the context of probability theory, what is the probability and how can we calculate probabilities of different elementary events.
In real-life tasks, we often have to deal with complex relationships and, as a result, calculate probabilities of several events or events that depend on each other. Let's consider how we can do this using probability theory.
To solve many real problems in probability theory, special models have been created that describe a particular situation. Let's consider some of the most used models that can be used to describe some discrete results of stochastic experiments.
What if the result of a stochastic experiment cannot be described by a discrete value? For this, models that work with continuous values are used. Consider the most popular of these models.
Often we are faced with the task of checking the dependence of the results of different stochastic experiments on each other. Moreover, it is necessary not only to assess the presence of dependencies but also to somehow quantify the degree of dependencies. To solve these problems, we can use covariance and correlation.
Module 6 / Ultimate Visualization with Python
First, we will discuss plotting applications, Matplotlib library, and its advantages. Afterwards you will create your first simple plot using Matplotlib.
Now you are ready to create various commonly used in practice plots. Without further ado, let's dive in right now!
Plotting and visualization is not only about creating a plot or several plots, it is also about making them clear, understandable and pleasant to look at. Time to learn plots customization in maplotlib, let's do it!
Statistics is essential in working with data, hence why it is extremely important to know how to create various statistical plots. Now it's time for us to explore the most common ones.
Seaborn is another powerful plotting library in Python built on top of matplotlib. Now that you are familiar with matplotlib, it's time to dive into visualization with seaborn.
Requirements
1. A computer with a browser - all browsers are supported.
3. Everything else needed to start learning and practicing is already included in this course.
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Ruslan Kravchuk
The main thing is to learn and not give up
The material is good, there is a lot to learn, all in order to become better and the main thing is to learn what you want....
Matteo Comune
Thanks to them I'm learning a lot…
Thanks to them I'm learning a lot faster because they help you to understand everything from scratch. It's the best website that helps people with no background in IT...
great course for beginners
great course for beginners, they test your knowledge in every lesson...
Elpunzon
I am enjoying my Codefinity experience…
I am enjoying my Codefinity experience learning Python. The self-paced way of learning is great because I can fit it into my schedule...
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Is nice to learn from codefinity
Is nice to learn from codefinity. Its easy and have good examples on what I learned here...
jacob Templet
Easy to follow along with and provides...
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Elan
Codefinity is a comprehensive learning…
Codefinity is a comprehensive learning tool to help you develop your skills as a software engineer or data scientist. The exercises are fun and a good way to sharpen your skills...
Thibault
First time learning how to code
First time learning how to code and successfully doing so with codefinity - thank you...
Well designed for total beginners
Well designed for total beginners, incremental progress and makes me feel confident....
_Gracy
it's simply perfectly well explained
it's simply perfectly well explained! so far I have not experienced any difficulty because everything is so well managed...
Ruslan Kravchuk
The main thing is to learn and not give up
The material is good, there is a lot to learn, all in order to become better and the main thing is to learn what you want....
Matteo Comune
Thanks to them I'm learning a lot…
Thanks to them I'm learning a lot faster because they help you to understand everything from scratch. It's the best website that helps people with no background in IT...
great course for beginners
great course for beginners, they test your knowledge in every lesson...
Elpunzon
I am enjoying my Codefinity experience…
I am enjoying my Codefinity experience learning Python. The self-paced way of learning is great because I can fit it into my schedule...
Alexandru Alexandru
Is nice to learn from codefinity
Is nice to learn from codefinity. Its easy and have good examples on what I learned here...
jacob Templet
Easy to follow along with and provides...
Easy to follow along with and provides challenge in my every day life. The challenge keeps me wanting to learn day after day...
Elan
Codefinity is a comprehensive learning…
Codefinity is a comprehensive learning tool to help you develop your skills as a software engineer or data scientist. The exercises are fun and a good way to sharpen your skills...
Thibault
First time learning how to code
First time learning how to code and successfully doing so with codefinity - thank you...
Well designed for total beginners
Well designed for total beginners, incremental progress and makes me feel confident....
_Gracy
it's simply perfectly well explained
it's simply perfectly well explained! so far I have not experienced any difficulty because everything is so well managed...
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What you'll get with our subscription:
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• Personalized study tracks
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