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R Programming Articles
Page 65 of 174
How to extract the names of list elements in R?
The names of list elements can be extracted by using the names function. For example, if we have a list defined as List that contains three elements with names element1, element2, and element3 then then these names can be extracted from the List by using the below command:names(List)Example1> List1 List1Output$x1 [1] -0.04518909 -0.22779868 0.24339595 -0.86189295 -0.73387277 -0.75313131 [7] 0.39694608 2.30565359 0.55670193 0.21973762 0.62968128 -0.90936921 [13] 1.33946741 -0.16315751 0.31357793 0.40365980 -0.23639612 -2.48749453 [19] 0.52152768 -1.57059863 0.51728464 0.98177111 0.65475629 0.23715538 [25] -0.71796609 -0.42731839 0.32335282 -0.90013122 -0.84549927 -0.88358214 [31] -0.32066379 -0.98945433 0.42469849 -1.63095343 0.32584448 0.10947333 [37] 0.23486625 0.28166351 1.18432843 0.94828212 0.09452671 0.56618262 [43] ...
Read MoreWhat is the difference between na.omit and complete.cases in R?
The na.omit function removes all the missing values in a data frame and complete.cases also does the same thing if applied to the whole data frame. The main difference between the two is that complete.cases can be applied to some columns or rows. Check out the below example to understand the difference.ExampleConsider the below data frame:> set.seed(2584) > x y df dfOutput x y 1 NA 25 2 5 5 3 8 NA 4 6 5 5 4 NA 6 4 5 7 6 NA 8 4 NA 9 4 5 10 8 5 11 8 5 12 ...
Read MoreHow to create heatmap in base R?
A heatmap is a diagrammatic representation of data where the values are represented with colours. Mostly, it is used to display data that has slight variation and applied on matrix data. We can draw it for a full matrix, an upper triangular matrix as well as a lower triangular matrix. This can be done with the help of image function.Example1> M MOutput [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 7 5 4 4 3 6 5 8 3 5 [2,] 8 7 3 5 7 4 5 2 6 6 [3,] 3 2 4 2 5 12 7 3 10 2 [4,] 5 3 6 9 5 9 2 4 5 8 [5,] 3 8 5 5 4 4 4 1 2 5 [6,] 2 3 2 4 7 8 5 8 4 4 [7,] 5 6 4 4 7 3 4 8 8 2 [8,] 4 5 2 10 5 3 5 4 6 7 [9,] 8 6 4 1 4 11 6 4 6 6 [10,] 9 5 5 4 6 2 7 3 6 5Example> image(M)Output:Example2> M1 M1Output [,1] [,2] [,3] [,4] [,5] [,6] [1,] 24.75339 25.40680 23.76650 26.47724 24.54639 25.79895 [2,] 24.08571 25.17951 25.03599 25.63532 23.45812 25.39614 [3,] 24.53005 25.77095 26.21571 24.44029 24.69933 25.62839 [4,] 22.91202 25.49497 24.86587 25.25701 23.16166 24.34106 [5,] 25.37322 24.15308 25.58580 23.52173 25.25538 25.10577 [6,] 24.39613 26.06243 26.56054 25.19265 26.54187 24.35313Example> image(M1)Output:
Read MoreHow to create a bar plot with ggplot2 using stat_summary in R?
There are multiple ways to create a bar plot in R and one such way is using stat_summary of ggplot2 package. In this function, we need to supply a function for the y-axis and to create the bars we must use geom="bar". The main thing is to decide which function should be used for y-axis values.ExampleConsider the below data frame:> x y df dfOutput x y 1 Female 3 2 Male 3 3 Female 7 4 Male 3 5 Female 8 6 Female 5 7 Male 11 8 Male 6 9 Male 5 10 ...
Read MoreHow to remove rows in an R data frame using row names?
There are a lot of ways to subset an R data frame and sometimes we need to do it by removing rows. In general, the rows are removed by using the row index number but we can do the same by using row names as well. This can be done by storing the row names that should be removed in a vector and then removing through subsetting with single square brackets as shown in the below examples.ExampleConsider the below data frame:> x y row.names(df) dfOutput x y A ...
Read MoreHow to create a function in R with two inputs?
To create a function with two inputs, we just need to provide two different arguments inside function. For example, if we want to create a function to find the square of a+b then we can use x and y inside function. Check out the below examples to understand how we can do it.Example1> F F(x=1, y=1) > F(x=2, y=3) > F(x=c(1, 2), y=c(2, 3))Output[1] 4 [1] 25 [1] 9 25Example> F(x=rpois(50, 2), y=rpois(50, 7))Output[1] 36 169 121 36 49 100 144 169 144 81 100 256 121 121 36 64 49 225 121 [20] 16 64 100 36 64 ...
Read MoreHow to extract columns of a data frame with their names after converting it to a time series object in R?
To access columns of data frame in R, we just need to use $ sign but if the data frame is converted to a time series object then all the columns will behave as a time series, hence, we cannot simply use $ sign. For this purpose, we would need to use single square brackets and pass the appropriate column inside it. Look at the below examples to understand how it works.Example 1Consider the below data frame:> set.seed(147) > x1 x2 x3 df1 df1Outputx1 x2 x3 1 5 11 4 2 5 5 3 3 4 6 2 4 10 ...
Read MoreHow to split a data frame in R with conditional row values?
The splitting of data frame is mainly done to compare different parts of that data frame but this splitting is based on some condition and this condition can be row values as well. For example, if we have a data frame df where a column represents categorical data then the splitting based on the categories can be done by using subset function as shown in the below examples.Example1Consider the below data frame:> Country Ratings df1 df1Output Country Ratings 1 India 1 2 China 2 3 Russia 5 4 Sudan 3 5 India 5 6 China 5 ...
Read MoreHow to create an only interaction regression model in R?
Mostly, we start with creating models by including single independent variables effect on the dependent variable and then move on to interaction. But if we are sure that there exists some interaction among variables and we are looking for the interaction effect then only interaction regression model can be created. This can be done by using colon sign between variables to signify the interaction as shown in the below examples.Example1Consider the below data frame:> x1 x2 x3 y df1 df1Outputx1 x2 x3 y 1 1 3 10 8 2 0 3 9 11 3 1 1 6 5 4 1 ...
Read MoreHow to find the absolute distance between columns of an R data frame?
The absolute distance can be found by calculating the difference between column values. And if we want the distance to be absolute then we would be need to use abs function. For example, suppose we have a data frame df that contain columns x and y then the absolute distance can be found by using df$Absolute_Distance set.seed(274) > x1 y1 df1 df1Output x1 y1 1 6 11 2 1 4 3 4 2 4 7 12 5 4 5 6 6 10 7 6 14 8 6 8 9 2 11 10 3 8 11 3 8 12 2 6 ...
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