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Articles by Nizamuddin Siddiqui
Page 89 of 196
How to subset nth row from an R data frame?
We can find subsets using many ways in R and the easiest way is to use single-square brackets. If we want to subset a row or a number of consecutive or non-consecutive rows then it can be directly done with the data frame name and the single-square brackets. For example, if we have a data frame called df and we want to subset 1st row of df then we can use df[1, ] and that’s it.ExampleConsider the below data frame:> set.seed(214) > x y z a b c q w df1 df1Outputx y z a b c q w 1 ...
Read MoreHow to convert a named vector to a list in R?
A named vector cannot be directly converted to a list because we would need to un-name the vector names and convert those names to names of the list elements. This can be done by using lapply function function. For example, suppose we have a named vector x then it can be converted to a list by using the command x x1 names(x1) x1OutputA B C D E F G H I J K L M N O P Q R S T U V W X Y Z 1 2 3 4 5 6 7 8 9 10 11 12 ...
Read MoreWhat is the difference between $ and @ in R?
If we have a data frame defined as df that contains column x, y, and z then extraction of these columns from df can be done by using df$x, df$y, and df$z. On the other hand, if we have an S4 object defined as Data_S4 that contains column x, y, and z then the extraction of these columns can be done by using Data_S4@x, Data_S4@y, and Data_S4@z.Example of a data frame:Example> x1 x2 df dfOutput x1 x2 1 4 2 2 7 0 3 10 2 4 3 1 5 7 1 6 2 2 7 3 4 8 4 ...
Read MoreHow to create a heatmap for lower triangular matrix in R?
A heatmap is a diagrammatic representation of data where the values are represented with colours. Mostly, it is used to display data that has slight variation. We can draw it for a full matrix, an upper triangular matrix as well as a lower triangular matrix. This can be done with the help of image function.Example1> M1 M1Output [, 1] [, 2] [, 3] [, 4] [, 5] [, 6] [1, ] 6 9 4 7 5 4 [2, ] 6 6 4 3 7 5 [3, ] 2 6 ...
Read MoreHow to extract the names of list elements in R?
The names of list elements can be extracted by using the names function. For example, if we have a list defined as List that contains three elements with names element1, element2, and element3 then then these names can be extracted from the List by using the below command:names(List)Example1> List1 List1Output$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 check if values in a column of an R data frame are increasingly ordered or not?
The values are increasingly ordered if the first value is less than the second, the second is less than the third, the third is less than the fourth, the fourth is less than the fifth, and so on. In base R, we have a function called is.unsorted that can help us to determine whether the values in a column of an R data frame are increasingly ordered or not. Check out the below examples to understand how it works.Example1> set.seed(3257) > x df1 df1Output x 1 9 2 8 3 8 4 7 5 10 6 2 7 7 ...
Read MoreHow to replace numbers with ordinal strings for a survey in an R vector?
The easiest way to replace numbers with ordinal strings is using ifelse function. The ifelse function in R works as ifelse(test_expression, x, y). Here, test_expression must be a logical vector or an object that can be coerced to logical). The return value is a vector with the same length as test_expression.Example1> x1 x1Output[1] 1 1 1 0 1 0 0 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 1 0 0 0 0 1 1 1 0 1 1 0 1 [38] 0 1 1 0 0 1 0 1 1 ...
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