Halaal, before going ahead in this session, let's have a quick recap of what we have done in all our
previous session in this project.
So from collecting this that huge and bulky data we have just heard in this baby logic over here once
for doing all these things we have analyzed, what exactly is a rush in each and every week after we
have analyzed what exactly is a rush in each and every hour after that, we have also analyzed what
exactly are those in each and every hour, in each and every month.
And this is exactly that subplot of six months once after doing all these things.
Let's go ahead with our very first public statement in which I have to perform an analysis of which
one has maximum.
Right.
So very close.
Let's have a preview of what data frame, how exactly my data looks like.
So this is exactly my data set on which we have to do certain kinds of analysis.
So you will see it here.
I have a column names on which month I have maximum write.
It means I have to group my data on the basis of this month, but that is you have to import some basic
models, some models of your plotty module.
So the very first I'm just going to say import plot, need dot graph, underscore all B.G. as as goal.
After importing this, I'm going to say from this block ne from this model I have to import something
which is offline and from this I have to import something else which is exactly my download path tab
download.
Let me guess, we have to import over in it as well, which is in it underscored notebook on a scoreboard.
After doing all these things we have to import my plot as well after it.
I have been caught my eye plot as well.
So these are all those modules that will definitely help us to create some beautiful additions in your
Tchoupitoulas notebook.
This plot is especially for your eye python notebook.
So once you're doing all these things, let me put one another thing, which is exactly it.
I have to say I have to import something which is exactly Shahd underscore is to do dot plot Lee and
I'm going to create its areas as like SIPRI just executed all this stuff to execute it.
Now, what we have to you have to grouplove data on the basis of this one.
So what I am going to do, I'm just going to say DL Gloopy and here I have to group on the basis of
month.
Once I have this group data on this.
I have to add to this hour, once I have all the stuff on this, I'm just going to say just count number
of hours with respect to each and every month.
So here you have to mention your month, not Menon's here.
I'm going to say it is exactly my man.
Once after doing all these things, you have to just execute it and it will return with this beautiful
statistics.
Let's say I have to store it somewhere else, or you can directly use this statistics in your visitations.
The four days.
I'm just going to say in this go, I have a function which is exactly my bar.
And if in this I'm going to pass shiftless tab, you will get all the custom parameters in this bar
plot off your plotnick.
So here in this bar, what I'm going to do, the very first parameter is exactly my act.
So on this X, I just need this data.
So I'm just going to copy this and I'm just going to paste over here that set and on this y axis, I
basically need my values.
So on X axis, I just need index.
So on this I'm going to say dot index and y axis, I need values.
So I have Ingeus based here.
Let's say I have to assign some level as well.
So for this I have a barometer which is exactly name.
And in this name, let's say my label is, let's say a priority.
Whatever label you want to assign, it's all up to you once you have all this stuff.
So it will exactly return me object.
I'm going to store it in next iteration and just execute it.
Now what you have to do, you have to simply showcase this crazy one.
So I'm going to say I have to showcase it using my applause.
So I have to just pass over here, just execute it and it will exactly that.
And it is beautiful is statistics.
So from this statement that you have, which month has maximum right now, you will come up with controls
and this nine month, which is.
Actually, my September it means September has the highest, it means September has the maximum rights.
So let's move ahead to our next statement in which I have to perform analysis of the journey of each
day.
So let's see what I'm going to do for this.
Here I have a column which is exactly my day column.
So I have to consider this column for this analysis, for this what I'm going to do.
I'm just going to say I just need a histogram of that.
So dot histogram and give of the Aleksi.
I just want my own window side on which I have to display this visit for this.
I'm going to say BLT dot figures.
I have to assign my own windowsill to fix it goes to, let's say, common six, whatever size you want.
It's all up to let's say I have something which is my beans.
What exactly is my inside here?
I'm going to say I just need my beans has thirty then I have some custom parameter, just press tab
and just try to play with all these custom parameters all at once.
You will do all this stuff.
Let's say I have to assign some X levels and Y level as well.
So here I'm going to say my X level is nothing more like the date of the date of the month.
Once you will do all the stuff, you have to assign some your Y label.
So I'm going to say BLT dot y label y label and here you have to assign a valuable X available is nothing
my total journey or total chutneys.
Once you had this Y label, you have to assign some title to your histogram.
So for this I'm going to say BLT the title.
Let's say my title is nothing but let's say Journeys by month, the whatever title name you want to
assign, it's all up to you.
Once you will do all these stuffs, you have to just execute the set.
It will take some couple of seconds.
And this is exactly what we said.
Let's say it is still doesn't look that much user-friendly over here, so you can play with some parameters
over here.
Let's say I have to set my parameter over here.
Here I'm going to say this is nothing but my outweight is equal to let's say it.
So this is exactly zero point eight just executed again and now it will be done some kind of beautiful
with additions over here.
Now you will come across this on this thirty added on this almost in each and every one on this 38 date.
You have definitely HIAS items on this party.
There are a maximum number of rights, ongoing war.
And if you are thinking this conclusion is correct, no, this conclusion, this insight is not correct.
Let me show you a thing.
And if I'm going to call this distribution plot, which is almost similar to this histogram.
So in here, if I'm going to call this off day and if I'm going to execute it now, you'll see over
here it will exactly return me this type of histogram over here in case of whenever I'm going to use
my seabourne distribution plot.
So it's so whether this result is wrong or right, I don't know what you can do in such case.
So here you have something parameter which is exactly which exactly what can be a range of beans.
So let's say I'm going to say my range of beans is nothing.
But from zero point five to thirty point five because I have set my beans is thirty.
So zero point five is your minimum blindsight and totipotent five is your maximum beans.
And if again you are going to execute this now, you will somewhere get your histogram like this distribution.
So if you are going to confuse, you can definitely come up with insight from this distribution it seems
to have.
Yeah, it's still on this third date is still there are maximum.
Right.
But in the before going through the in the before pizzle, there is a huge variance between each and
every day.
That's what I'm going to say.
You can definitely go ahead with this and you can cross-check your analysis.
So that's all about decision.
Hope you love this session very much.
Thank you.
Have a nice day.
Keep learning.
Keep growing.
Keep.