WEBVTT

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Hello, everyone, and welcome to this tutorial here in this tutorial, we will understand the frames.

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Let us begin.

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Our data frame is a two dimensional Radosta Judd that these data is aligned in a tabular fashion in

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drawers and columns depend as data frame consists of three principal components, data, rows and columns

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to understand data frames.

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First, we have to import, but it needs.

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Important MP as MP, then import Ben Dodds as PD after that import.

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One more liability from num dort random

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import brand and.

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Then import and PDR, random dot seed one zero one.

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Great.

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You will ensure that we will house same output.

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Now define a data frame the F to define data frame.

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We have to use a method BD dot data frame.

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And these are the arguments that we can enter here.

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Data.

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Index columns.

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Data type.

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And copy specified data.

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First data is equal to land.

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And for you.

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Comma food.

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Didn't specify the index.

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A, b.

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C, b, e.

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After that specified the columns.

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W x.

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Vij.

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Z execute.

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No, Jake, this did help him the F.

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Great.

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So this is our data frame.

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So these are the column names W, X, Y, Z.

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And these are the names.

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A, B, C, D, E.

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And this is the data, as we have discussed earlier.

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This data in a table, lot of farm rows and columns.

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Each of these column is a number ECD.

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This is a number ECD column W.

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This is a number.

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Series.

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Again, column X.

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Column Y and column.

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The each of these column is a number C reads.

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And all these numbers series share a common index.

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This one.

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So we can say that data stream is a bunch of bendat TV that share a common index.

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So these are the basics about the data frame.

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And this is how we can create a data stream using this method dot data frame.

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Let us understand indexing and selection.

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Suppose we want to select this column.

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Column W to do that by the name of data frame and then specify the column name.

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So this is a very quiet output column w no, take the tape.

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D.F..

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Column DeBlois.

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Series.

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So this column is a name P.c reads.

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No, Jake, the type of data frame B F.

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They delphinium.

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So they doorframe is a bunch of numpty series with common index from the day doorframes, if we can

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select multiple columns.

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Also, let us see how.

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Take the data from the F.

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He we will select these two columns X and VI.

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To do that type name off the data frame here, we will passing at least Golomb X and column by execute.

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Great.

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So this is our output column X and column by no Kopit is.

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Take the tape.

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They Dufrene when there is more than one Numpty series, then it is a data frame.

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So this is all about the indexing and selection in data frames.

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Let us understand how to add a new column.

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First, take the data from the EFF so we can add a column.

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To add a column, type B F specified the name of new, column new, we will add this column with arithmetic.

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Operation B, F, column W, Blur's B F.

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Column X.

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Execute.

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Now, Jake, D-Day Delphinium, B.F..

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Great.

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So this column is added successfully here.

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And this is the addition of these two columns, column W and column X.

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So this is how we can add a new column in data frame.

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Let us understand how to remove the columns and drawers in data frames.

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Removing columns and roads.

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To remove a column, we use drop method type D.F. dot drop.

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Here we have to specify labels and axes.

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Specify labels first.

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Labels is equal to new.

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This is the name of a column that we are going to remove.

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Then specify axes.

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Axes is equal to one axis, is equal to one for the columns and axis is equal to zero for the rules.

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No execute.

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Great.

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So the column new is removed here.

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Now take the detailed from the F.

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In regional data frame, this column is not removed to remove this column permanently be how to add

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one more parameter IBF dot drop.

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Specify labels new, then specify axes vun to delete this column permanently, be able to specify in

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place is equal to true.

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In place is equal to true.

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No execute.

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Dig the data frame.

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Great.

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So this column is removed successfully to remove a column V, how to deliberately specify in place is

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equal to true.

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So this is how we can remove a column from a data frame.

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Let us understand how to remove a rule a b f dot draw.

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Specify a name of the rule.

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B.

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And after that we have to specify the index.

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Access is equal to zero.

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Execute.

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You can see here Ruby is deleted.

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No, no, down here.

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By default, access is equal to zero.

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So we don't have to specify this.

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It will take automatically.

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So this is all about deleting rows and columns in a data frame.

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Let us understand how to select the rules in a data stream.

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Selecting deludes.

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For Dick debate to frame the F.

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Great.

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Now, suppose we want to select this through this one.

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See, to do that type data frame the F Dot LLC.

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And specify the name of Duru executed.

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So this is the road that we have selected rules.

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Now take the data type.

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COPD.

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Based.

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Seaweed's, so data frame is also a number ECD.

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So this is Helvey again, select deals in a data frame.

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Let us understand how to select the subset of rules and columns.

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Selecting this subset of rules and columns.

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Dig, dig, dig it out from the F.

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Great.

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No, suppose they want to select this value zero point seven fold to do that type data frame.

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B f.

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Got a Locy here.

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We have to specify Drew and column.

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So this value has rule.

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See, and column X specify a row first, then the column execute.

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So this is a very wide output.

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We can select a subset.

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Also, let us see how.

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We will select these four values.

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Minus zero point nine three zero point nine for you.

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Two point six zero and zero point six eight.

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By the F dot Alosi.

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First, we have to specify do lose.

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So these four values has rules B and E specify as a list the.

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Then V, how to specify column names.

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VI and the VI commands the executed.

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So this is a very quiet output.

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First, we have to specify the rules and then we have to specify the columns.

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When we have to select multiple rows and multiple columns, then we have to specify rules as a list.

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And columns also as a list.

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So in this little deal, we have learned a lot of things.

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Literary vides.

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First, the Hill understood how to create a data frame to create a data stream.

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We use this method data frame.

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After that, we felt understood indexing and selection in a data frame, a single column in a data frame

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is another piece.

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Deeds and data frame is a bunch of numbers, c.D, with a common index.

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After that, we helped understood how to add a new column in a data frame.

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So this way we can add a new column in a data frame.

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Then we all understood how to remove columns and rules for the columns to be able to specify.

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Access is equal to one and for Duros we have to specify access is equal to zero.

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And to say this change button one and only be able to specify in place is equal to true.

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After that, we have understood how to select the rules like these to select the rules.

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We have to use this method.

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Dot Alosi.

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And at the end, we understood how to select a subset of rules and columns.

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So this first by 10, did all deal on data frames.

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I will see you in the next one.

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buildOn, happy learning.