Pandas is a software library
returned for the biting programming language
for data manipulation and analysis In
particular it offers data structures and
operations for manipulating numerical tables and
time series Find us back It
is the most important Do it
at the disposal of data scientists
and analysts working and bison today
understanding this we have come in
for this life in pond are
sectorial Now before we go ahead
with session I like to inform
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in the description below What is
recall Well recollect actually Rick authority
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terminology we call as categorical variables
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what is the minimum cell What
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bigger values are smaller very extreme
values we call extreme values Right
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don't find fight What they're anything
good is better than less than
zero point for this is that
Doesn't you know But if I
only I mean this is the
card should not come You got
You are Yes Only B f
came way Cosby If only have
be Yes This is also not
opened This is also not grander
than you know Party fight But
you don't know See masterful This
is my data frame Correct What
is the condition I want a
play I want to see all
the records All the records which
has scored greater them score one
greater than you know part If
I tell me why Among the
already card which school Which three
cars have rather than 0.5 be
Be Yes Correct See False Be
false You Drew No I'm telling
score one I'm putting a condition
on one column score one not
the entire roof Okay we look
at the condition of charity and
no the condition is like this
rate Hey in this data frame
where the school is better than
so if there are only this
butler thing what will happen I
did it through our falls I
am passing that true or false
is to my data frame so
that only truth will be displayed
The index off those things were
a little come So if you
want more than one column I
can use the same concept And
if I want to put them
more than one condition they can
use and person under really pipe
is for But so what did
you know It will get me
both Score one is rather than
fire And also stores score to
his rather than zero If it's
just say score two is also
greater than find five No Tell
me what will happen No we're
looking at this data This record
should not come Correct We could
not come No Okay look Look
at this data frame The data
frame has This is indexed correct
BC like this BC had not
good Lexus him I want to
rename that to a proper country
name So I create I can
reset the Knicks If every said
the index what will happen next
will be you know 123 And
have you also noticed UNIX become
a column now it needed next
Waas I only remember her own
name No Index became a column
Okay I am creating a new
index now These are my 10
countries I'm creating a simple ish
No no What is this Newness
will help This is a simple
list isn't it They want to
give this Mr Toe my data
frame and asked you to use
as a knicks Okay so but
does it Allah We have a
country's feel Does it have a
country's feel No So what should
I do know for say should
I could create a new countries
feel I'm adding this index to
it But does it help countries
already No So what should I
do know Tell me from the
based on Fort of Oratory alone
How to add a new column
How do I didn't you call
him We added this column six
nightly A score six Now How
did we had Same like this
Only know we have added Then
we were not getting no this
time The remedy Earlier we have
added a column score Six Adding
a new column How did we
created a new column Could it
be treating you column list That
means I'm not supposed to give
a list Then we figure here
score six off some values here
How many Three comma for comma
seven Come on six Come before
Come on in Come on Time
to become a 27 Come out
of how many values are there
10 should be a given Right
Can Should we give in to
it Omega Run 23456789 10 11
But really cannot give Fallujah Siri's
I can give a city street
They cannot give it just lister
to it So how do you
cannot know this entail Is India
cities now Really that can I
had no you understood No Because
theater frame always works with in
excess and column That means you
could get a lot of work
on regularly Lexus They next off
list is not efficient but it
where did has given and no
have added sake That's the problem
Great Isn't in Not a number
No For their only main Here
remember here But I given no
10 very more One thing now
still it is the same No
not Detrick In with the other
the other framed and have a
little That's not the case because
the index off this particular thing
is different from index off This
is not able to match I
told you in the elite sportsmen
and sports to that right ot
on for some sports we got
there and then value way because
when you are adding something when
you're adding something it will it
will only go away What is
the city's What is this Index
off this one You don't want
to be like this Is it
any Jiro matching here Know that
Know what really be ableto No
So what should they do Know
you said one is They said
that so that they can pass
it to it that the money
I can give it next to
this funnels and others to the
city's also right How do I
give a city street now Not
in Mexico Toe All right What
is the only thing that I
want me see late B c
b ye Yes G hitch I
earned the jays dot Split Yeah
this is a split This is
Stringer for unknown it off disc
record close And I should close
that bracket here You know what'll
happen No I like it When
you doing mistake also you know
you should know What is that
What is that How it is
happening there Otherwise you're not able
to carry your own This is
what understanding the concept is No
I understood No I didn't dislike
you for a new programmer Wouldn't
what How What I look I'm
trying to add something list I'm
not ever to add Then I
realized I can had only a
Siri's But when Harding cities also
it when you are adding a
new series to an existing data
frame the next I should match
other very little Not Noto How
did those values they The other
is he said the knicks and
then create a new index The
sort of trying to understand No
clear now this writer frame which
has C six records now Okay
I said I'm doing a research
in Lex All their necks has
become you know 1234 My own
to give it named to it
123456789 10 How many How only
nine now So I created a
new index now Okay Now will
it work No Nor that What
does What does happen But he
says that it does new thing
even with the list Also you
can add as long s the
list also listed What is the
index off list You know 1234
only now you can add it
Okay now I have it Now
I want to reset one of
the country as my index sensor
off B Didn't I deserted Yeah
This is the whole value Okay
I understand This is a hold
value No that country became the
index Is it off BCD country
became index Yeah Where you are
happening The district and the different
Yes Again simple This is again
changing not training there Actually it
is creating a new radio frame
So what should I do in
places A call to group then
actually at a formal she So
what are all thing that we
learned below Find us This is
a really similar to what we
have learned with number A Selection
Edition's and then basic operations When
we do a case study the
new I'll combine all the knowledge
that we have gained in the
last six hours Now and then
we'll we'll make use off tech
because this is our learning basics
on you know the last two
hours we'll do a case study
Then we will come in all
this knowledge with actual later Okay
So the other thing that you
would normally do it pandas is
missing value treatment So in this
data how many missing values out
of there There are only thing
where you say you know you
look at this data frame They're
not missing values since you know
that after you know by this
But somebody has really did the
data from a text former for
file You will not know what
are the missing values are there
So simply you can say drop
any because what will happen No
it will drop all the records
that that has you and one
single values there And then Tero
it will rather than tell rope
Okay So if you want to
drop columns which has missing values
don't want to the doctor and
Cairo and what you can do
access is equal dough one Okay
Now because it only this particular
thing had doesn't have anything These
two columns So these two girls
have been dropped again in places
going to true It's not true
that it was in a letter
sent remains as is She wouldn't
let us remain as is I'm
only creating a new data frames
here Okay So dropping me ready
for access is it will do
Gino That means it will drop
all the rose No access is
equal to one minute will drop
the columns usually will you drop
out when you do something you
can feel this is like they
were filtering Alino Okay there's a
thing called threshold That means don't
drop even if one degree for
there's only one single while you
don't drop it minimum should be
to the special value is to
this more than do Then only
your drop But as I can
see Okay then it is dropping
Only which one It is dropping
now Here It didn't drop it
because this record then how do
you know If you look at
this data this record has to
Indians That is a double Only
this is a very cards remain
at this one And this one
You mean the data set Understood
Threshold No you really lot drop
what you'll do You'll fill that
value Correct If you drop your
losing their correct what do you
do You will feel the values
you ask Business Hey this value
is missing What should I do
Know I didn't say okay Sorry
I have given incorrect to you
Just you feel this with I'm
x value So if you want
to fill with some value I
can say filled out and me
Is he called the Jiro Then
what did what he did Wherever
missing values are there it has
operated with gentle this Now you're
getting a new thing altogether You're
crazy You're getting a new data
set No Only Lexus are incremental
Order You see if you look
it again Another frame My dad
of him has not changed clinic
on the air Getting the same
index on this is a new
reader frame Let's a say in
places you could do through Have
you understood this in place Concept
everyone What is in place Whatever
changes that you're doing you're filtering
row filtering whatever you're doing Are
you doing within the data frame
itself Are you're doing it Creating
a new Yeah definitely Okay when
you create a new data from
same index will will will be
carried That's really a question Right
So the other way is you
Normally you don't put the constant
There should be some logic For
example it is missing in the
group Were all 100 Get that
asset Example One person the age
is missing Okay But I have
experience on the other column What
I will do rather than keeping
Jiro are on average age off
all the other people in this
room What I will do it
But what is the already experience
off the since these days having
them is experience What is the
average age of cannons experience with
people in the room Then I
will use that as the that
is much more intelligent to them
randomly for you Putting a constant
aria average off the interrogator said
Correct So he does That's what
I'm doing What I'm doing is
some value is missing for baseball
Some scoring missing for baseball shall
afford zero for everything You know
what I'm doing is what is
the average score off baseball on
putting that value in that That
makes matters that much more intelligent
Way Officer This is called missing
value treatment How do you treat
a missing value that are different
techniques in it is another technique
One other technique is find a
11 to group close to that
particular missing value on foot A
mean army Deanna more off it
on who will take this call
with the help of some business
knowledge How do you know experience
has experienced a rate feel here
I would take in some other
field experiences build really really close
to that heritage This is again
on my knowledge in this case
general knowledge But in business you'll
not be able to do this
You need some don't my knowledge
So this is all part of
for what is already in the
ghetto And I signed Lifecycle Project
where which stated we haven't They're
in preparing organizing the data understanding
the data still way we can
get back into understanding better But
we realize that has a missing
value So there were immediately the
moment you realize missing values What
do you do You believe those
missing value records How do you
teach them Feed the means Fill
them Could it Is it enough
But melody memory is the constraint
here What are fits in their
memory All right that's fairly Does
that does That is beyond your
memories That means your memory left
heading for TV So no doubt
the four db operating system of
the application will take it on
TV How much What's with that
Do you have Don't give me
right and you were working on
A to G We're doing the
medical duplication and calculations you some
from memory require further application So
you not be able to hold
large volumes of data that said
this This problems could be get
a problem Then you get into
a large volumes of data They
told you twitch your model one
to process Where do you want
to distribute that Then what you
do is you will distribute they
the work Then you use platforms
Carl spark spot cast and machine
learning algorithms Because Richard Dawkins are
buried for executing the algorithm in
a this you would you do
it What I'll get that you're
seeing there Not distributed algorithm They're
not designed for distribution So the
father that day is a distributor
I looked at them Ah platform
called spark Where you can use
that is another advantage of lemmings
fighting there You you change instead
of one Does u change some
other package is the last cake
it learned You lose another package
but fundamental concepts remain Sit You're
getting the point So that isn't
because this part's and advance packages
are also using spot lighting Have
them one of the interface But
US forecasts part can be used
with Karl also But fighting we
do have you and fighting on
our as well so far also
has Parker Are we here Clear
till now Well let's get into
small small at duties was other
activities What Actually you do honey
there Does it groups No feel
tired that then that is done
And we did some missing value
treatment I don't understand the data
by using group that says you
know I have a customer data
letter like this Get a frame
like this So this is what
is this this a dictionary Right
Can I cannot Dictionary endured a
tough for him if I cannot
Dexter Interview Different What happens All
my keys becomes my in Texas
Right That's that That's the case
here But do they have here
what has happened here Tell me
this this kids became my column
here Correct this What is this
City's keys becomes You're rowing Lexus
But different is a data frame
Your kids will become Europe columns
It literally remember faster We when
the first example We did converted
a dictionary doing a series Then
all values become We'll use all
their keys become row in Texas
but only help multiple records Then
Oliver kids will become your column
Names makes sense right This is
logically correct rate This is how
it should work Okay No there's
a function called group A bite
So how many customers are there
for you here Same goes Massari
breeding Now you under grew by
the new Arbeit God created for
you So they had to store
that group result in today An
object No on that group What
do you do There's an object
which had only grew by each
customer on that group What you
don't know that Say Allah ways
you do And I have read
the operation of some numerical operations
on it Correct you Can I
display it Because that's didn't grew
Form it Now what do you
do it on this particular thing
I'm trying to for a traitor
displayed It's an object feeds the
group It's it's a delegated An
object with us on this group
What you do Well so some
operation I was intellect starts from
the group and also you feel
you could not get not good
Anything After that You say group
take a small ready comma some
off our average off or whatever
something connect That's exactly what happens
in living as equals Okay so
are you gonna group operation use
You say mean Israel rating multiple
lines off court or they can
do is groupe dot Maybe And
I can see I get Henderson
Okay so then this group like
a new standard deviation liken grow
minimum maximum cone I can describe
this group if I want I
can describe the group There's a
beautiful function card Describe if you
look at this disgrace what it
is doing now So when did
you know anyone Customer you have
on group you have Geno two
is another group Purity is another
group and it is giving me
some important statistics for me What
is that What is the count
How many customers are there in
Jiro This group What is the
meaning of this group What is
the standard deviation of this group
What is the minimum value of
this group What is the 25th
percentile of this group What is
the 50th percentile of this group
7/5 person relatives What is the
maximum this like this Like I
can get all these values This
is very good On which Well
on the way We have only
single value there Right in group
You have data like this on
the help profit Yes kind If
Good question If I didn't name
descript usually does it only on
numeric data types This claim Does
it done human great apes I'll
show you also I'll tell you
that also Yes Give me a
minute Okay On the way we
learned a trance posting So what
will happen if I transpose this
is and get like this What
is the difference between this and
this is only transfers off it
but mean my real ability has
increased You know if you if
you are good good in reading
like this you can use this
transport If you're good in very
reading like this can can remain
as this Saillant Take it easy
a little Okay It is enough
entire transport I can also say
simply He also seems I will
answer this question Yes Give me
a minute Okay Okay If you
want I play filter on it
This is also a simple letter
from kind of a thing I
can only get only for one
part cleric Cardinal I want only
one drink One Butler column Then
I can get only the that
particular column idealist Okay I'll be
clear on grouping now So simple
early no group by dot Whatever
operation that you want to look
so 11 other function that we
learned in this popular thing is
described function for the stray function
only works on Humenik But if
you want to work on even
with the distinct I sure you
know for example actually if you
look at this group this group
has customer name on also profit
links It can be something else
Also correct So a lady one
mentee estimate I have that example
so that we could easily do
claim that Okay I'm creating a
data frame here I have one
more day different I had three
data frames No get a friend
Oneness Some customer data data frame
to has some other customer data
later Frame free Has some other
customer data Okay No let's see
One more escape me No less
and less This data D E
A F year One dark in
four is one functioning in front
It will tell me what is
the data Type off each off
this information and what is their
different Hey you know in this
data frame I have four entries
I mean there are four credit
cards on indexes starting from zero
to 30 And these are my
data columns 44 columns First a
column This has four values This
has four values like this Is
it a nominal object That means
everything is faith There's no no
love gets on What is the
battery profit It's an object object
Object like this It is anything
telling Okay No this a d
f even dark Describe what it
does is describing the entire data
sick But it is taking all
of the sales get Only because
he knows it is that all
objects were not able to describe
them So I'm not describing it
I wondered is craving nunik database
Which one Yes That's Monday as
an object because I'm giving customer
idea given it at this string
Good cause I got it Okay
No that Emmy Yeah There's a
function car include the perimeter card
Include include is equal to follow
No you get all that thanks
It has including the categorical in
Nunik It has both categorical in
nomadic No cost already Also getting
in the categorical Obviously they will
not be mean Median mortar No
top on dull for whatever that
is applicable It will have you
noticed this has brought some other
new things like count unique home
in a unique Are there great
frequency Because if it for the
categorical very well water What All
things you do How many unique
products are there only unique customers
Are there harmony for what is
the frequency After repetition What is
the total count Whatever that is
applicable That value will come here
Like it No This is how
you can do this Okay Only
said he might have three letter
frames one day at a time
like this because you know get
a frame to read a frame
Three I have three letter frames
Three different sources I got a
letter from three different sources Know
what operation that you do A
giant much kind of operations earlier
you know Okay Foster Concatenation Concatenation
What happens Thank God there's nothing
What Yes Side right By defiled
What it does is it will
add hard Gentilly it will have
are generally right Neither completely new
data from God created wherever that
butler thing is it doesn't It
has not done based on Then
we'll see the rate of him
like this It is like this
rate Saudi death It's created on
the different columns Are there any
free Every data frame all combined
together Wherever it is able to
match the specific columns Western columns
it is able to match them
which was not finding that column
for example payback is not really
faster Get a frame It has
filled Mel is there Are you
getting the point So this so
simple concatenation But if you want
concatenation toe happen on columns that
when they think should come next
to next not hard Generally what
you want particularly concoct mission then
you can say access is equal
to one now instead of water
in now instead off bringing them
Robredo It has been column by
column this column by column No
this is a separate record on
this is a Frederick card This
is a critical Normally you don't
know concatenation What do you do
You do it Margene based on
a column name Correct this column
This column Wherever the matches you
try to born get the things
this exactly is the concept car
merging is now are cool at
the tables Okay this is quite
common in quarter to Rita this
quarter three and quarter for data
What should they know You know
if a concurrent what'll happen it
will come where they were hard
Generally correct That means cute They
hear dated ladies on AL value
for Q three and Q for
it will not come under to
come here So I want to
merge them No I don't want
to congratulate them I want toe
Merge them so you can go
okra merging and in their emerging
Also Okay so you do Merging
Best Don Which column Customer 80
So what has happened in the
second record There is no car
over customer ready to but still
it is able to manage and
get it on the whenever it
is not able to get it
If it has placed Indians what
you said in their joint what
would happen Only those customers who
has a matching when we will
be matched You'll understand What is
the letter Um uh Diamond Yeah
Outer Join for that We train
here Mr In a common column
name the value in that column
I'm trying to find their corresponding
this thing His car Maji Okay
Now they said the concept all
joining comes into picture for this
Ho How does joining rocks is
joining You also seem similar to
merge only very very similar to
what is The only difference is
giant Merck uses a common columns
to combine to record but as
join uses a two row indexes
to join the data frames Bassem
column name It will join that
giant Will do Wanna raw index
We remember Rose also can have
names No we can do based
on Rose Also For example if
you look at the data like
this your table one like this
right I zero you and I
to on a table to is
like this Now you want to
join them sir Table Wonder Join
This is a pure outer giant
Correct I don't know Join because
outer joint study in the joint
Right now If you want older
giant you can do the soles
so that you'll get all the
other records which have not so
beautiful It is doing the left
outer Join here left Join here
You know that is matching It
is getting It is a simple
left to join here The sort
of question right This is a
left join you want I join
in sort of table to table
on your place They were to
one year and you'll get the
right over again Very sign off
I like to inform that we
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