Top Social media companies in Mumbai 2019

Like is now this is where we left off last time I just was given a brief overview of our projects and how we're going to proceed Social media companies in Mumbai through tunnels be not so brief so do apologize for being longer than I wanted. But now we're going to start by exploring our actual data sets and take a look at how the day is going to be represented.

And talking about how we'll manipulate it and what pieces we want once we're comfortable with how that dates represented digital marketing company we can then move on to actually imposing formatting and manipulating the retrieve data to grab only the pieces that we actually ones.

OK, so we're going to start by showing you where I got all of this data from and then I'll direct you to the resources folder at the actual CSP files are stored. So I was just going to open up a new window of chrome here. OK. And we're going to go to investing dot com. All right so now we're investing dot com. You can see we can enter any stock that we want in the search bar. And I'm going to start.

Let's just ignore that. I'm going to start just by work with gold first because that's going to be the stock that we'll work with, to begin with. So if I just type in gold a bunch of options comes up I'm Social media companies in Mumbai going to use gold futures. Although to be honest doesn't matter too much which one we use. So each of those stocks is going to be different by the way from the other stocks.

I just happen to use gold futures because it seemed to make sense to me. So as you can see there's a bit of information about it as current prices constantly fluctuating gives up by how much what percent and so on and so forth. It gives a graph that basically maps all of the days of fluctuations over a day a week a month three months a year five years and so on and so forth. But we're not going to cover any of that.

We're actually just going to get the CSP files via this historical data tab. So we click on this and it gives us all of the information here so that gives us the current date of that particular reading. It gives us the price that the end of that day gives us the opening price with the high and low prices Social media companies in Mumbai where the amount of volume exchange although sometimes you'll see just this dash here some reason not all of the volume data is uploaded and then it gives you the rough change over the course of the day.

So depending on which day you were actually retrieving the data of these figures might be different. Like I said I'm going to provide those files. I personally use when I built this project for you guys in the Resources folder that we both have the same or we all have the same data sets. OK. Otherwise, if you do want to download the most recent stuff you can just go up here.

Click on this calendar icon OK and then just enter your start date and your end date. You could go back as many years as you want as long as there is actually data collected for those years. I just started off I think the training data sets are going to be about a month back. OK, so from September to October the or date that's the testing day sets the training data sets for a year from this date here. So they're actually to go back months then and one month back.

Okay. So this is just to get you familiar with which data sets we're going to be using that once you have those that particular data in Social media companies in Mumbai mind you could just download the data download as CSP sheet and then just import into a project. So I'll show you where to find those resources and your actual resources folders we can even come out of this if we want and you can open up a new instance or find out.

I'm in my resources folder now OK so this will probably still be filled with a bunch more stuff than just these four items. But what you're going to want to look for is this directory called stock files. These are just the CSP files for a few of our stocks OK. Once we open this up you'll see that there are eight files in total source for each or rather two for each of the four stocks we got the natural gas station gold data oil data. And so the days of for the last month that's again going to be used for testing.

And the last year that's going to be used for training and applies to all of these. Okay. So we can actually take all four of these if we once thought because we're going to be working with just the goal to start off with less actually just retrieve the gold data. Okay. And we are going to either import this into a folder or we can simply drag and drop it right into our project here.

Okay. Now, rather than gigantic dropping it in I'm going to actually just get rid of that. I'm just going to copy and paste over that I have it in both locations. Okay. So come on C we'll copy these two OK we're going to go Social media companies in Mumbai into the project directory and paste will specify the copy rather than just moving those files. Again I want them in both locations.

So this is how this whole page is going to be reading our CSG files or rather all going to represent them. This is just the last months of the last year we'll have a lot more data points as you can see. But the edges will all be the same. So we have the current date or the date of that particular reading the again the end price the opening price of the stock price the high and low prices the amount of volume exchanged in this case Kay is in thousands of stocks.

Okay. And then the change percentage which is just going to be the difference between the start and end values so if we have a positive value that means the price went up. And if we have a negative value the price went down. Now it's also important to note how many data points that are in this set as this will again differ depending on which stock we're going to be looking at.

So, for example, I think the oil and natural gas stocks have a lot more data points that are all gold and silver days for some reason. So as you can see we're only interested in about data points or so. And from this, we're going to ignore our date column. We're going to ignore our high and low column and we're only really going to be looking at the end price.

The opening price the amount of volume and actually we can ignore change percentage as well because we'll be calculating our own social media companies in Mumbai change percentage. Like I said this is just going to be our actual testing data as just a month's worth whereas training is going to be all year right. One thing to note is how things are going to be formatted in this data set.

So as you can see the volumes will have this K afterward. We're going to want to get rid of that because we want to convert these numbers to floats. Similarly, all of the prices are Khama have this column here which basically dictates that they're in the thousands. What we're going to want to get rid of that comment as well because we can actually convert this as it stands to a float.

We have to convert it to a string get rid of that comma and then we can convert it to a float. OK. So by the end, we'll have basically a bunch of floats arrays float Hooray for the end price float Rafe's to the opening prices float for the volumes and then we'll create a closer race for the price differences. Right now I arbitrarily picked these four stocks. Gold and Silver interested me and then I thought oil and gas might be kind of interesting to work with.

So I just pick those four random but you can pick any stock at all that you're interested in. I just I will advise you that the accuracy will probably differ between all of those different stocks it really depends on what you're going to be working with and when you're going to be working with it.

But with that being said we know holidays are going to be represented. Let's move on to the next section where we'll take a look at how to actually import this CSP data into our project store inside of a variable and then we can work on actually manipulating that data and storing what we want namely the price open and volume columns into their own respective floats arrays.