Hi.
In this video we will talk about how to load the data into our pandas data
frame. What are the options and about our dataset?
Our dataset for this module is stored in a CSV file. Uh,
it is called Cybersecurity attacks csv,
and this is the main data set,
which contains a few statistics about various cyber attacks, their categories,
sub-categories, protocol in a specific time period.
The second file, this is this one, D C P four C S V,
uh, which contains information about ports and services running on these ports.
In one of the exercises, it'll be used to join with the main dataset.
We have already used few times the pandas method to load C Ss V into
pandas. It is the method, the read, c s v wait past the file name,
which would like to open.
It is very flexible and has a lot of parameters,
but the most used parameters are the heater parameter,
which allows to set by you explicitly.
If you data content heaters step as a separator,
and in case your file is too big,
you can process the C s V chunk by chunk using chunk parameter visual return
to you and iterator object.
The c s V file is most common and reliable,
but often you may want to load the data from different sources like a database
market files. H D F F.
The C S V file is the most common and reliable,
but often you may want to load the data from different sources like a database,
market files, uh, feather format, uh, SS three bucket, or from Hadoop.
And, uh, Panda supports many of these.
In our next video, we will explore a few methods for the initial data audit.