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In base R, we can use legend function to add a legend to the plot. For example, if we want to create a histogram with legend on top-right position then we can use legend("topright",legend="Normal Distribution") and if we want to change the font size then we need to as cex argument as shown below:legend("topright",legend="Normal Distribution",cex=2)Examplelegend("topleft",legend="Histogram of",cex=1.5)Output
To replace missing values with median, we can use the same trick that is used to replace missing values with mean. For example, if we have a data frame df that contain columns x and y where both of the columns contains some missing values then the missing values can be replaced with median as df$x[is.na(df$x)]
To create a scatterplot for factor levels, we can use facet_grid function of ggplot2 package. For example, suppose we have a factor column in a data frame df defined as F and numerical columns defined as x and y then the scatterplot for the factor levels can be created as −ggplot(df,aes(x,y))+geom_point()+facet_grid(~Factor)Examplelibrary(ggplot2) ggplot(df,aes(x,y))+geom_point()+facet_grid(~Factor)Output
One of the most important aspects of a boxplot is Y-axis labels because these labels help us to understand the limit of the variable. Since R generate these labels automatically in a good way, we stick with that but we can change that using coord_cartesian function with ylim as shown in the below example.Exampleggplot(df,aes(x,y))+geom_boxplot()+coord_cartesian(ylim=c(290,400))Output
To create a random sample in R, we can use sample function but if the weight of the values is provided then we need to assign the probability of the values based on the weights. For example, if we have a data frame df that contains a column X with some values and another column Weight with the corresponding weights then a random sample of size 10 can be generated as follows −df[sample(seq_len(nrow(df)), 10, prob=df$Weight_x), ]Exampledf[sample(seq_len(nrow(df)), 5, prob=df$weight_x), ] Output x weight_x 11 5.257177 10 19 5.401021 9 13 5.334041 10 10 4.416107 6 5 6.593158 2Exampledf[sample(seq_len(nrow(df)), 3, prob=df$weight_x), ... Read More
The replicates of a data frame in R can be created with the help of sapply function, to set the number of times we want to repeat the data frame we can use rep.int,times argument. For example, if we have a data frame df and we want to create 5 replicates of df and add them in the original then sapply(df,rep.int,times=5) can be used.Examplesapply(df,rep.int,times=5)Output x1 x2 x3 x4 [1,] 20.84538 9.486324 2.961236 967.9296 [2,] 23.29721 5.344792 3.044849 960.2204 [3,] 20.55978 6.064207 3.005293 1086.9639 [4,] 20.66044 8.436004 2.892010 1029.8222 [5,] 19.81347 9.277129 2.980567 1018.0453 [6,] 20.84538 9.486324 2.961236 967.9296 [7,] 23.29721 5.344792 3.044849 960.2204 [8,] 20.55978 6.064207 3.005293 1086.9639 [9,] 20.66044 8.436004 2.892010 1029.8222 [10,] 19.81347 9.277129 2.980567 1018.0453 [11,] 20.84538 9.486324 2.961236 967.9296 [12,] 23.29721 5.344792 3.044849 960.2204 [13,] 20.55978 6.064207 3.005293 1086.9639 [14,] 20.66044 8.436004 2.892010 1029.8222 [15,] 19.81347 9.277129 2.980567 1018.0453 [16,] 20.84538 9.486324 2.961236 967.9296 [17,] 23.29721 5.344792 3.044849 960.2204 [18,] 20.55978 6.064207 3.005293 1086.9639 [19,] 20.66044 8.436004 2.892010 1029.8222 [20,] 19.81347 9.277129 2.980567 1018.0453 [21,] 20.84538 9.486324 2.961236 967.9296 [22,] 23.29721 5.344792 3.044849 960.2204 [23,] 20.55978 6.064207 3.005293 1086.9639 [24,] 20.66044 8.436004 2.892010 1029.8222 [25,] 19.81347 9.277129 2.980567 1018.0453
The bar plot is created with geom_bar function but there always exist some space between the bars and the X-axis labels. If we want to reduce that space or completely remove it we need to use scale_y_continuous function by defining expand argument for former and scale_y_continuous(expand=c(0,0)) for latter.Exampleggplot(df,aes(x,y))+geom_bar(stat="identity")+scale_y_continuous(expand=c(0,0))Output
The group−wise linear regression means creating regression model for group levels. For example, if we have a dependent variable y and the independent variable x also a grouping variable G that divides the combination of x and y into multiple groups then we can create a linear regression model for each of the group. In R, we can convert data frame to data.table object, this will help us to create the regression models easily.Exampledf2[,as.list(coef(lm(Salary~Ratings))),by=Class]OutputClass (Intercept) Ratings 1: I 31894.13 194.9152 2: III 35270.10 663.4089 3: II 40405.42 -1087.9103
A program to reverse digits of a number will interchange the position of the digits and reverse there order.Let’s suppose be a number abcde the reverse will be edcba.Let’s take an example to understand the problem, Inputn = 786521Output125687To reverse digits of the number, we will take each digit of the number from MSB(unit digit) and add it to reverse number variable, after this divide the original number by 10 and the reverse_number is multiplied by 10. This will be done until the number becomes 0.This repetitive process can be accomplished by two methods, iteration, and recursion, we will create ... Read More
To set flex items to be of equal width column, use the flex-fill class. The class displays the items as equal width. In the below example screenshot, you can see that we have four flex items with equal width columns −The flex-fill class is used for every flex items and in this way, we can set equal width. Below, we have two flex items − Example 1 Example 2 Example Bootstrap Example With flex-fill Example 1 Example 2 Example 3 Example 4 Without .flex-fill: Example 1 Example 2 Example 3 Example 4