Requirements
·
No programming experience
Description
Nearly
every scientist working in Python draws on the power of NumPy.
NumPy brings the
computational power of languages like C and Fortran to Python, a language much
easier to learn and use. With this power comes simplicity: a solution in NumPy
is often clear and elegant.
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.
Pandas is an open-source
library that is made mainly for working with relational or labeled data both
easily and intuitively. It provides various data structures and operations for
manipulating numerical data and time series. This library is built on top of
the NumPy library. Pandas is fast and it has high performance &
productivity for users.
Why
learn pandas?
If
you've spent time in a spreadsheet software like Microsoft Excel, Apple
Numbers, or Google Sheets and are eager to take your data analysis skills to
the next level, this course is for you!
Data
Analysis with Pandas and Python introduces you to the
popular Pandas library built on top of the Python programming
language.
Pandas is a powerhouse tool
that allows you to do anything and everything with colossal data sets --
analyzing, organizing, sorting, filtering, pivoting, aggregating, munging,
cleaning, calculating, and more!
I
call it "Excel on steroids"!
Over
the course of more than 19 hours, I'll take you step-by-step through Pandas,
from installation to visualization! We'll cover hundreds of different methods,
attributes, features, and functionalities packed away inside this awesome
library. We'll dive into tons of different datasets, short and long, broken and
pristine, to demonstrate the incredible versatility and efficiency of this
package.
Data
Analysis with Pandas and
Python is bundled with dozens of datasets for you to use. Dive right
in and follow along with my lessons to see how easy it is to get started with
pandas!
Whether
you're a new data analyst or have spent years (*cough* too long *cough*) in
Excel, Data Analysis with pandas and Python offers you an
incredible introduction to one of the most powerful data toolkits available
today!
Matplotlib is easy to use and an
amazing visualizing library in Python. It is built on NumPy arrays and designed
to work with the broader SciPy stack and consists of several plots like line,
bar, scatter, histogram, etc.
Matplotlib
Anatomy
As
the name implies, in this section you will learn how Matplotlib works and how a
variety of charts are generated.
It
gives you a solid understanding and a lot of aha-moments when it comes to
creating and / or customizing charts that you haven't dealt with before.
Create
2D Charts
In
this section, you will generate plethora of charts using Matplotlib OOP, and
Pandas and mix them together to achieve the maximum efficiency and granular
control over graphs.
Axes
Statistical Charts
Here
we will learn how to make statistical charts such as Auto Correlation,
Boxplots, Violinplots and KDE plots with Matplotlib OOP and Pandas.
Seaborn
Seaborn,
a high-level interface to Matplotlib helps make statistical plots with ease and
charm. It is a must-know library for data exploration and super easy to learn.
And in this section, we will create Regression plots, Count plots, Barplots,
Factorplots, Jointplots, Boxplots, Violin plots and more.
Who this course is for:
·
Students interested towards data science
career path
·
Students interested towards data analyst
career path
·
This course is for you if you want to
learn NumPy, Pandas, and Matplotlib for the first time or get a deeper
knowledge of NumPy and Pandas to increase your productivity with deep and Machine
learning.
·
This course is for you if you are coming
from other programming languages and want to learn Python NumPy and Pandas fast
and know it really well.
·
This course is for you if you are tired
of NumPy, Pandas, and Matplotlib courses that are too brief, too simple, or too
complicated.
·
This course is for you if you want to
build real-world applications using NumPy or Panda and visualize them with
Matplotlib.
·
This course is for you if you want to
master the in-and-out of NumPy, Pandas, and data visualization.
·
Existing Software Programmers who want
to shift to Data Science career
·
This course is for you if plan to pass
an interview soon.
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