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To display X-axis labels with dash in base R plot, we can use axis function and define the labels manually. For this purpose, we can first create the plot without X-axis labels by using the argument xaxt="n" and then use the axis function.Check out the below example to understand how it can be done.ExampleIn order to display X-axis labels with dash in base R plot, use the following code −plot(5, 5)OutputIf you execute all the above given codes as a single program, it generates the following output −In order to display X-axis labels with dash in base R plot, add ... Read More
To find the groupwise cumulative mean, we can use cummean function of dplyr package.For example, if we have a data frame called df that contains a categorical column say Group and a numerical column say Response then the groupwise cumulative mean can be found by using the command given below −df%>%group_by(Group)%>%mutate(CM=cummean(Response))Example 1Following snippet creates a sample data frame −Group
To combine data frames stored in a list in R, we can use full_join function of dplyr package inside Reduce function.For Example, if we have a list called LIST that contains some data frames then we can combine those data frames by using the below command −Reduce(full_join,LIST)Check out the Example given below to understand the Output of this command.ExampleFollowing snippet creates a sample data frame −df1
To create barplot for some top values in an R data frame, we can subset the required top values inside the barplot function.For example, if we have a data frame called df that contains a categorical column say C and a numerical column for frequency defined as F then the barplot for top five values can be created by using the below mentioned command −barplot(df$F[1:5],names.arg=df$C[1:5])ExampleFollowing snippet creates a sample data frame −Category
To find the column name that has the least value for each row in an R data frame, we can use colnames function along with apply function.For Example, if we have a data frame called df then we can find column name that has the least value for each row by using the command mentioned below −df$Least_Column
To set the coefficient of one variable to 1 for logistic regression model, we can use offset function.For example, if we have a data frame called df that contains a binary column say y and three independent variables say x1, x2, and x3 and we want to create a logistic regression model with x1 coefficient equal to 1 then we can use the below given command −glm(y~x2+x3,offset=x1,data=df,family=binomial)Example 1Following snippet creates a sample data frame −y1
To display Y-axis labels with more decimal places, we would need to round the values of the vector or column for which we want to create the plot to the appropriate number of decimal places.After that axis function will be used for creating the graph. Before doing all this, the graph of original values should be created without axes.Check out the below example to understand how it works.ExampleFollowing snippet creates a sample data frame −x
To create pie chart using plotly, we first need to find the count data based on categories and then use the plot_ly function by mentioning chart type as "pie".To find the count data, we can use count function from dplyr package after that plot_ly function will be applied.Check out the below example to understand how it can be done.ExampleFollowing snippet creates the mtcars data −data(mtcars) head(mtcars, 20)OutputThe following mtcars data is created − mpg cyl disp hp drat wt qsec vs am gear carb Mazda RX4 ... Read More
To find the groupwise large and small values in an R data frame, we can use mutate function of dplyr package, the grouping can be easily done with the help of group_by function.For Example, if we have a data frame called df that contains grouping column say Grp and a numerical column Num then we can find the groupwise large and small values by using the below command −df%%group_by(Gp)%%mutate(Val=ifelse(Val==max(Val),"large","small"))Example 1Following snippet creates a sample data frame −Group
To merge rows having same values in an R data frame, we can use the aggregate function.For example, if we have a data frame called df that contains two categorical columns say C1 and C2 and one numerical column Num then we can merge the rows of df by summing the values in Num for the combination of values in C1 and C2 by using the below given command −aggregate(Num~.,df,FUN=sum)Example 1Following snippet creates a sample data frame −grp1