1
00:00:00,210 --> 00:00:06,359
Hey welcome to this new section! And yeah, as usual
here in the first lecture I'll just give

2
00:00:06,359 --> 00:00:11,610
you a demonstration of the program that
you'll be building, and so you'll have

3
00:00:11,610 --> 00:00:17,369
this program on your hands by the end of
this section. And yeah, during my work as

4
00:00:17,369 --> 00:00:22,109
a freelancer I've seen an increase in
demand for getting data from the

5
00:00:22,109 --> 00:00:27,869
internet from various clients and these
data can concern for different purposes.

6
00:00:27,869 --> 00:00:34,610
For instance you may need
property data from a real estate website

7
00:00:34,610 --> 00:00:39,960
such as this one here or you may need
businesses, so a list of businesses

8
00:00:39,960 --> 00:00:45,300
and you may want to look for that on
yellow pages or even information from

9
00:00:45,300 --> 00:00:52,079
Wikipedia. The problem is these websites
that I don't give you like a CSV with

10
00:00:52,079 --> 00:00:56,370
data that you're looking for.
They don't do that and what you want to

11
00:00:56,370 --> 00:01:02,820
do in that case is you want to scrap data
from these websites, and yeah you may

12
00:01:02,820 --> 00:01:09,090
need data for different purposes and we
can do that, we can do web scrapping, so

13
00:01:09,090 --> 00:01:13,170
the process is called web scrapping.
We can do that with Python, so Python is

14
00:01:13,170 --> 00:01:18,450
perfect for that and basically what you
do is you get these data and you store

15
00:01:18,450 --> 00:01:23,970
them in a table such as a Pandas data
frame here and you can also export that

16
00:01:23,970 --> 00:01:29,909
easily in a output. And yeah, in this section
what you're going to do is you're going

17
00:01:29,909 --> 00:01:35,700
to do web scrubbing on this real estate
website and so with Python you're

18
00:01:35,700 --> 00:01:40,740
going to perform a search query on a
certain location so Python will search

19
00:01:40,740 --> 00:01:45,810
for data and then we can get those data,
and ii will store them in this table, and

20
00:01:45,810 --> 00:01:55,170
then lastly it will save them in an
output CSV file, so everything is

21
00:01:55,170 --> 00:01:59,070
automatic. And you may want to get
different attributes from the website so

22
00:01:59,070 --> 00:02:07,229
in our case we got this set of
attributes and you can get those data in

23
00:02:07,229 --> 00:02:12,090
a single run of the program.
Of course first of all you need to build

24
00:02:12,090 --> 00:02:14,080
that program and that's
what we're going to do

25
00:02:14,080 --> 00:02:19,540
in the next lectures so this is very
useful and in addition to learning web

26
00:02:19,540 --> 00:02:24,820
scrapping this will also boost your
Python skills in general, and yeah

27
00:02:24,820 --> 00:02:28,000
let's kick this off and I'll talk to
you in the next lecture.