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Here.

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Before moving to the plot alibi and cufflinks we first need to set a plot away in cufflinks.

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They what we are going to do in this video.

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So we will begin with importing them.

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Be as and B and import upon does as BD.

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We go to Denver.

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Also Ed met blowed lip space in line there.

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There you go with Dedmon.

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Now we will first import the plot all right that is import bloat and light as being to pretend.

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Did you go with that one.

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After that you need to import cufflinks as S.F. David Goldman.

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Now you need to do two things here.

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First you need to set up the connection to all flight because bloated by cufflinks are something that

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works online.

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In that case you need some I.D. and stuff like that one.

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So we make this old stuff all flight.

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So for that we require three commands here.

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First one is import load elevate or flight.

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As Bill shifted them now right the same tax bill.

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That is this plot of land library.

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Note in it underscore the notebook underscored more.

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This is something that make the libraries connected in offline mode and make this one true.

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After that make cufflinks or flight that is just simply this library S.F. dot go underscore or fly.

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If you do not write this index you need simpler alibi and companies log Logan idea and password.

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So to prevent death things just tried this long difficult despondency.

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So this is what all you need to do to set up global grain companies in your projects.

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You can also just make this one.

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Now we are done with this so I am moving all these in just this life.

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So this one here this one here.

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This one here and these two indifferently because someday we will get some added while doing these in

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the same line.

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So there we go with that but now we will define some datasets that we are going to need.

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Here first is just generally a random data offering BD or data frame.

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I believe you are no expert in this thing.

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So here we would generate a random data frame and we do random no grand don't use it and N for native

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values and hundred rows and five columns you can take any and then we have columns.

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These will be something like a b c d and e labial.

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If you print that one you will find this bunch of options.

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Sorry you did your defense.

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After that we will define it under the definition that is a data frame that containing also these algebraic

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kinds of values so that we can plot some different types of plots there.

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So data from here we will define a simple dictionary first X and the values for x are like a.

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Then we have B then we have C then we have d and we have e then we go after that we have white and white

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will contain all the numeric values 1 2 2 4 and 5.

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Then we have said that will also continue to values for distribution type of plots and the Eagles and

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random values them should pretend.

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And now we have f this one x y z columns and 5 those first one these values that has connected values

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and then we have numeric values.