Sakinashaikh: Created page with " {| border =1 |'''Time''' |'''Narration''' |- || 00:01 ||Welcome to this tutorial on '''Pipe Operator'''. |- || 00:06 ||In this tutorial,we will learn about: |- || 00:10..."

2020-05-22T11:06:22Z

Created page with " {| border =1 |'''Time''' |'''Narration''' |- || 00:01 ||Welcome to this tutorial on '''Pipe Operator'''. |- || 00:06 ||In this tutorial,we will learn about: |- || 00:10..."

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{| border =1
|'''Time'''
|'''Narration'''

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|| 00:01
||Welcome to this tutorial on '''Pipe Operator'''.

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|| 00:06
||In this tutorial,we will learn about:

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|| 00:10
||'''summarise''' and '''group_by functions'''

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|| 00:14
||Operations in '''summarise function'''

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|| 00:18
||'''Pipe '''operator

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|| 00:20
||To understand this tutorial, you should know,

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|| 00:25
||Basics of statistics

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|| 00:28
||Basics of '''ggplot2''' and '''dplyr''' packages

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|| 00:34
||'''Data frames'''

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|| 00:36
||If not, please locate the relevant tutorials on '''R''' on this website.

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|| 00:43
||This tutorial is recorded on

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|| 00:45
||'''Ubuntu Linux '''OS version 16.04

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|| 00:51
||'''R''' version 3.4.4

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|| 00:55
||'''RStudio''' version 1.1.463

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|| 01:01
||Install '''R''' version 3.2.0 or higher.

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|| 01:07
||For this tutorial, we will use

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|| 01:10
||A '''data frame moviesData.csv'''

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|| 01:15
||A '''script''' file '''myPipe.R'''.

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|| 01:20
||Please download these files from the '''Code files''' link of this tutorial.

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|| 01:27
||I have downloaded and moved these files to '''pipeOps''' folder.

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|| 01:33
||This folder is located in '''myProject''' folder on my '''Desktop'''.

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|| 01:40
||I have also set '''pipeOps''' folder as my '''Working Directory.'''

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|| 01:46
||Now we learn about '''summarise function'''.

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|| 01:50
||'''summarise function''' reduces a '''data frame '''into a single row.

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|| 01:56
||It gives summaries like mean, median, etc. of the '''variables''' available in the '''data frame'''.

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|| 02:05
||We use '''summarise''' along with '''group_by function'''.

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|| 02:11
||Let us switch to '''RStudio'''.

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|| 02:15
||Open the '''script myPipe.R '''in''' RStudio'''.

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|| 02:21
||'''Run''' this '''script''' by clicking on the '''Source''' button.

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|| 02:26
||'''movies data frame''' opens in the '''Source''' window.

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|| 02:31
||In the '''movies dataframe''', scroll from left to right.

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|| 02:37
||This will enable us to see the remaining '''objects''' of the '''movies data frame'''.

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|| 02:44
||To know the mean of '''imdb_rating''' of all movies, we will use '''summarise function'''.

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|| 02:52
||Click on the '''script myPipe.R'''

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|| 02:57
||In the '''Source''' window, type the following '''command'''.

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|| 03:02
||Inside the '''summarise function''', the first '''argument''' is a '''data frame''' to be '''summarised'''.

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|| 03:09
||Here, it is '''movies'''.

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|| 03:12
||The second '''argument''' is the information we need, that is the mean of '''imdb_rating'''.

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|| 03:21
||Save the '''script''' and '''run''' the current line by pressing '''Ctrl+Enter '''keys simultaneously.

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|| 03:31
||The mean value is shown.

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|| 03:34
||One will argue that I can find the mean by using '''mean function''' along with '''dollar''' operator.

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|| 03:43
||What is the use of installing a whole '''package''' and using a complex '''function'''?

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|| 03:49
||Basically, we do not use '''summarise function''' for computing such things.

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|| 03:56
||This '''function''' is not useful unless we pair it with '''group by function'''.

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|| 04:03
||When we use '''group_by function''', the '''data frame''' gets divided into different groups.

|-
|| 04:12
||Let us switch back to '''RStudio'''.

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|| 04:16
||In the '''Source''' window, click on '''movies data frame. '''

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|| 04:21
||In the '''movies data frame, '''scroll from right to left.

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|| 04:27
||We will group the '''movies data frame''' based on the '''genre'''.

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|| 04:33
||For this, we will use '''group underscore by function'''.

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|| 04:39
||Click on the '''script myPipe.R'''

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|| 04:43
||In the '''Source''' window, type the following '''command'''.

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|| 04:48
||'''Run''' the current line.

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|| 04:51
||A new '''data frame groupMovies '''is stored.

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|| 04:56
||Now, we will use '''summarise function''' on this '''data frame'''.

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|| 05:02
||In the '''Source''' window, type the following '''command'''.

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|| 05:07
||'''Run''' the current line.

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|| 05:10
||I will resize the '''Console''' window

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|| 05:14
||The mean values of all movies in different '''genres''' are displayed.

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|| 05:21
||Notice that, '''Documentary genre''' has the highest mean '''imdb_rating.'''

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|| 05:28
||And '''Comedy genre''' has the lowest mean '''imdb_rating.'''

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|| 05:34
||I will resize the '''Console''' window

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|| 05:38
||In the '''Source''' window, click on '''movies data frame. '''

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|| 05:43
||In the '''movies data frame''', scroll from left to right.

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|| 05:49
||Let us find the mean '''imdb_rating '''distribution for the movies of '''Drama genre'''.

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|| 05:58
||Also, we will group movies of '''Drama genre''' by '''mpaa_rating. '''

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|| 06:05
||For this, we will use '''filter, group_by''', and '''summarise functions''' one by one.

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|| 06:12
||Click on the '''script myPipe.R'''

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|| 06:17
||In the '''Source''' window, type the following '''commands'''.

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|| 06:23
||First, we will extract the movies of '''Drama genre'''.

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|| 06:29
||Then, we group these movies based on '''mpaa_rating'''.

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|| 06:35
||Finally, we apply '''summarise function'''.

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|| 06:39
||This will calculate the mean of the filtered and grouped movies.

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|| 06:46
||'''Run''' the last three lines of code.

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|| 06:50
||I will resize the '''Console''' window

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|| 06:54
||The required mean values are printed on the '''console'''.

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|| 06:59
||I will resize the '''Console''' window again.

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|| 07:03
||In this code, we have to give names to each and every intermediate '''data frame'''.

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|| 07:10
||But there is an alternate method to write these '''statements''' using the '''pipe''' operator.

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|| 07:17
||The '''pipe '''operator is denoted as '''%>%'''.

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|| 07:25
||It prevents us from making unnecessary '''data frames'''.

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|| 07:30
||We can read the '''pipe '''as a series of imperative '''statements'''.

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|| 07:35
||If we have to find the '''cosine''' of '''sine''' of '''pi''', we can write

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|| 07:42
||Let us switch to '''RStudio'''.

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|| 07:45
||We will learn how to do the same analysis by using the '''pipe''' operator.

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|| 07:51
||In the '''Source''' window, type the following '''command'''.

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|| 07:56
||Here three lines of code have been written as a series of '''statements'''.

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|| 08:02
||We can read this code as,

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|| 08:06
||Using the '''movies data frame''', filter the movies of '''Drama genre'''

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|| 08:13
||Next, group the filtered movies by '''mpaa_rating'''

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|| 08:19
||Finally, summarise the mean of '''imdb_rating '''of the grouped data.

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|| 08:26
||This code is easier to read and write than the previous one.

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|| 08:32
||In the case of '''pipe''' operator, we don’t have to repeat the name of the''' data frame.'''

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|| 08:39
||Notice that we have written name of the''' data frame''' only once.

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|| 08:45
||Save the '''script''' and run the current line.

|-
|| 08:50
||I will resize the '''Console''' window.

|-
|| 08:54
||The required mean values are printed on the '''Console'''.

|-
|| 08:59
||I will resize the '''Console''' window again.

|-
|| 09:03
||In the '''Source''' window, click on '''movies data frame. '''

|-
|| 09:08
||In the '''Source''' window, scroll from left to right.

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|| 09:13
||Let us check what is the difference between '''critics_score ''' and '''audience_score''' of all the movies.

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|| 09:22
||We will use a '''box plot''' for our study.

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|| 09:26
||By using the '''pipe''' operator, we can combine the '''functions''' of '''ggplot2''' and '''dplyr packages'''.

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|| 09:34
||Click on the '''script myPipe.R'''

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|| 09:38
||In the '''Source''' window, type the following '''command'''.

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|| 09:43
||Save the '''script''' and run the current line.

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|| 09:49
||The required '''box plot''' appears in the '''Plots''' window.

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|| 09:54
||In the '''Plots''' window, click on the '''Zoom''' button to maximize the plot.

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|| 10:00
||Here you can see that for the genres '''Drama, Horror, '''and '''Mystery & Suspense''' movies, the median is close to zero.

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|| 10:14
||This means that the '''audience '''and '''critics '''opinions are very similar for these '''genres'''.

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|| 10:22
||Whereas for '''Action & adventure''' and '''Comedy '''movies, the median is not close to zero.

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|| 10:30
||This means that the '''audience''' and '''critics''' opinions are different for these '''genres'''.

|-
|| 10:37
||Close this plot.

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|| 10:39
||In the '''Source''' window, click on '''movies data frame. '''

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|| 10:44
||In the '''Source''' window, scroll from right to left.

|-
|| 10:49
||Let us check the number of movies in every category of '''mpaa_rating''' of each '''genre'''.

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|| 10:57
||Click on the '''script myPipe.R'''

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|| 11:01
||In the '''Source''' window, type the following '''command'''.

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|| 11:06
||Notice that we have included both '''genre '''and '''mpaa_rating''' in '''group_by function'''.

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|| 11:15
||So, the analysis will be done on the data divided by these 2 '''variables'''.

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|| 11:22
||Also, we have used '''num = n()'''.

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|| 11:27
||The '''function n''' computes the number of times the event with specific condition has happened.

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|| 11:35
||'''Run''' the current line.

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|| 11:38
||I will resize the '''Console''' window.

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|| 11:42
||From the output, we can see that there are 22 '''Action and Adventure''' movies with '''mpaa_rating '''as '''R'''.

|-
|| 11:53
||Let us summarize what we have learnt.

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|| 11:57
||In this tutorial, we have learnt about:

|-
|| 12:00
||'''summarise''' and '''group_by functions'''

|-
|| 12:04
||Operations in '''summarise function'''

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|| 12:08
||'''Pipe '''operator

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|| 12:10
||We now suggest an assignment.

|-
|| 12:14
||Use the '''built-in data set iris'''.

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|| 12:18
||Using the '''pipe''' operator, group the flowers by their species.

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|| 12:24
||Summarise the grouped data by the mean of '''Sepal.Length '''and '''Sepal.Width'''.

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|| 12:33
||The video at the following link summarises the Spoken Tutorial project.

|-
|| 12:37
||Please download and watch it.

|-
|| 12:41
||We conduct workshops using Spoken Tutorials and give certificates.

|-
|| 12:46
||Please contact us.

|-
|| 12:49
||Please post your timed queries in this forum.

|-
|| 12:54
||Please post your general queries in this forum.

|-
|| 12:59
||The '''FOSSEE '''team coordinates the '''TBC '''project.

|-
|| 13:03
||For more details, please visit these sites.

|-
|| 13:07
||The Spoken Tutorial project is funded by NMEICT, MHRD, Govt. of India

|-
|| 13:13
||The script for this tutorial was contributed by Varshit Dubey (CoE Pune).

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|| 13:20
||This is Sudhakar Kumar from IIT Bombay signing off. Thanks for watching.

|-
|}

R/C2/Pipe-Operator/English-timed - Revision history

Sakinashaikh: Created page with " {| border =1 |'''Time''' |'''Narration''' |- || 00:01 ||Welcome to this tutorial on '''Pipe Operator'''. |- || 00:06 ||In this tutorial,we will learn about: |- || 00:10..."