Hey, welcome to this new section, and in
this section, you'll learn how to use
pandas, which is a very important Python
library, and you really don't want to
miss that. So what is pandas? Well,
pandas is a library providing data
structures and data analysis tools
within Python. Or if the word tools
confuses you, then you can say pandas is
a library providing data structures and
data analysis code. So basically, pandas
allows you to load data from different
sources into Python, and then use Python
code to analyze those data and produce
results, which can be in the form of
tables, text, and also visualization
with the help of visualization
libraries, such as bokeh. bokeh,
which is covered later in the course. So
for now, we'll focus on data without
visualizing them, and pandas is great
for that. So practically, how do we use
pandas? Well, you learn how to open text
files using Python built in file
handling methods earlier in the course.
Now, what we open from text files was
just plain text. But what if you want to
load text files with data constructed
off rows and columns. So things get a
bit complicated. But here is where
pandas comes into play. So you can
probably do that using build-in Python
methods that we have learned in the
course. But to be more efficient and to
be much more efficient, you need to
have a high level library such as
pandas, which is able to recognize such
data structures automatically. So I use
Pandas for loading data from data mining
activities, such as web scraping. So
you scrap data from a website with
Python, and then store those data in
pandas dataframes. So you use pandas to
provide data structures for you in
Python. I use Pandas for loading data
from Excel files, and also use pandas
for analyzing those data instead of
using Excel. Excel can be good for
analyzing a small table of data that
fits in your screen, in your computer
screen. But for data larger than
that, so you really want to use code.
So you write Python code once and then
you reuse it with other data as well, and
you don't want to do selections,
and dragging, and many other cumbersome
operations that you normally do in
a graphical base program, such as Excel.
So code is the way to go if you want to
be efficient with data. and Python is great
for that with pandas. So you really want
to get a good hang of pandas, and you
will learn that in this section, and
also practice it with real world
applications that we will be building as
you progress through the course. Let's
go ahead and dive into some code for now
in the next lectures. See you.