Hello and welcome to the second patented Odille Undetailed Frames.
Let us begin.
First, we have to import the library reads.
Great.
Then create the data frame.
No dignity, delphinium the F.
So this is the same day timeframe that we had created in previous ordeal.
These are the column names W, X, Y, Z, and these are the indexes, A, B, C, D, E, no.
Verville, understand conditional selection in data frames.
No, down here.
Conditional election.
Babe, the name of the doorframe, the F specified can be John be F is greater than zero.
So this is our output.
This output is in the form of booleans.
These are the boolean values, true and false.
When a value in data frame is greater than zero, then it is true.
Otherwise, it is false.
You can see here minus two falls, four plus two point seven two four zero point six for you.
We can store this result in a variable.
Also, let us do it.
Copy this.
Create a variable.
B, execute.
Now, take variable be.
He had also be how same result Willian values.
No tape did offer him b f specify this variable.
Now we have different output.
Let us understand this, Verdie, billion values are true.
Only those values are shown.
Otherwise, there are Adnen values.
You can see for true values.
Photo values for falls, then value.
So this is how we can select the values from our data frame on the basis of a condition instead of that
variable b we can specify can be shared directly.
Delete this variable be specified the condition.
This one data frame, the F is greater than zero.
Execute.
Same result.
No, no, down here.
We have specified this condition for interrogate our frame.
We can specify this condition for a specific column.
Also.
Let us see how the name of the data from the F select the column W.
Greater than zero.
Execute.
So these are the billion values for Colomb W..
Drew Drew falls through to.
Now store this result in a variable.
Take this video while.
Same result.
No bussing, this can be shown in detail from the F.
No, no, down here.
Third row is missing, and this is because condition is false.
For the third, Drew, you can see.
Falls.
So here we have selected this data frame on the basis of a column that is conditions in a single column.
Instead of that variable, we can post in condition basically copy this condition.
Data from the EFF.
Then the condition execute.
Same result.
So this is how we can apply conditional selection in a data frame.
Let us understand how to apply multiple can be at a time.
Multiple conditions.
Take the day delphinium, D.F..
No, Louisville specified the multiple conditions together, laid out for him D.
F.
He said we will specify multiple conditions.
This is for first condition.
And this is for second condition.
First, we will select Golomb W is greater than zero.
This one baby F column name and this column W is greater than zero.
And along this condition we how to add one more condition.
So specify and operator values in column VI is greater than one.
This column A.
B.
F.
Column VI.
Greater than one.
Let us understand these two conditions again.
First, we are selecting this data frame on the basis of this column.
Column W.
Here we are going to select only those values which are greater than zero.
And after that, we are selecting data from the F on the basis of this column VI.
Here we will select only those values in column VI, which are greater than one.
And between these two conditions we are using and operator.
So here we are selecting only those values which satisfies these two conditions.
I will not done here.
And operator
execute.
So this is the result.
Only a single row satisfies these two conditions.
This one rule.
Let us understand.
Our operator copy this line.
Based.
Maintain or operate the.
And this is the symbol for auto operator by.
Let us understand these two conditions.
First, we are selecting only those values from column W, which are a greater than zero.
And after that, we are selecting only those value from column VI, which had a greater than one and
in-between V health specified.
Operator.
This one.
So here we will get only those values which satisfies at least one can be can no execute.
So this is the output.
Only one drawer is missing.
So this fold roll satisfies at least one of these two condition.
So this is how we can do multiple conditioning, the digital frames.
Let us understand.
Index in detail.
Take the data out from the EV.
Great.
Now tape the F dot.
Reset index.
Execute.
Here you can see one index is added.
This one, this column.
So using this method, we can they say the index.
And to permanently save this, you have to make this parameter in place as glue.
As of now, I'm not going to do that.
Now create a list.
New index.
R g.
B.
All.
Vij.
Take the least.
Great.
No, add this list as a column in this data frame from the F.
To do that, they D.F. name off the column glove's.
Then the name of the least new index executed.
No, Jake Beatty, Delphinium, D.F..
Great column is added, name of the column is Gullahs.
And these are the values, no, they say the values of this new column as index to do that type name
of the data frame dot method, set index and in parentheses, name of the column.
Gullahs.
Take the cube.
So here we have successfully edited this column as index.
To permanently store this make parameter in place is equal to true.
So this is all about the state index method.
And they it index method.
Let us revise what we have learned in this tutorial.
Flushed.
Well understood.
Conditional selection in the adult frames.
After that, we all understood how to select the values from a data frame on the basis of multiple conditions.
And to do that, we use these two operators and or.
And at the end, we help understood index.
These two methods that he said index method and state index method.
So this second by 10 did all deal on data frames.
And here I will see you in the next one.
Then happy learning.