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To create a line chart using ggplot2 that touches the edge we can follow the below steps −First of all, creating data frame.Then loading ggplot2 package and creating the line chart in default manner.After that creating the line chart with coord_cartesian function.Create the data frameLet's create a data frame as shown below −x
To create groupwise correlation matrix for an R data frame, we can follow the below steps −First of all, create a data frame.Then, find the correlation matrix by splitting the data frame based on categorical column.Create the data frameLet's create a data frame as shown below −v1
Converting a variable into zero mean and unit variance means that we want to standardize the variable and it can be done with the help of scale function we can follow the below steps −First of all, creating data frame.Then using scale function to convert the variable into zero mean and unit variance.Create the data frameLet's create a data frame as shown below −x
To subset an R data frame with condition based on only one value from categorical column, we can follow the below steps −First of all, create a data frame.Then, subset the data frame with condition using filter function of dplyr package.Create the data frameLet's create a data frame as shown below −Class
To display categorical column name in facet grid, we can use the following steps −First of all, creating data frame.Loading ggplot2 package and creating a chart with facetsCreating the chart with facets and labeller function to display categorical column nameCreate the data frameLet's create a data frame as shown below −x
To create the bar chart with ggplot2 using color brewer in R, we can follow the below steps −First of all, create a data frame.Then, create the chart with default colors.After that, use scale_colour_brewer function to create the bar chart.Create the data frameLet's create a data frame as shown below −Group
If na.rm is set to TRUE using dplyr package then the output for statistical operations returns NaN. To avoid this, we need to exclude na.rm. Follow below steps to understand the difference between the tw −First of all, create a data frame.Summarise the data frame with na.rm set to TRUE if NA exists in the data frame.Summarise the data frame without setting na.rm to TRUE.Create the data frameLet's create a data frame as shown below −Group&li;-rep(c("First", "Second", "Third"), times=c(3, 10, 7)) Response&li;-rep(c(NA, 3, 4, 5, 7, 8), times=c(3, 2, 5, 2, 4, 4)) df&li;-data.frame(Group, Response) dfOn executing, the above script ... Read More
To display NA frequency for a ggplot2 graph using color brewer in R, we can follow the below steps −First of all, create a data frame.Then, create the chart with default colors.After that, use scale_colour_brewer function to create the bar chart and set the color of NA values bar with na.value.Create the data frameLet's create a data frame as shown below −Group
To display NA group values in scatterplot created with ggplot2 using color brewer in R, we can follow the below steps −First of all, create a data frame.Then, create the scatterplot with default colors.After that, use scale_color_brewer function to create the scatterplot with color of points (including NA) based on color palette given in scale_color_brewer.Create the data frameLet's create a data frame as shown below −x
To convert ggplot2 graph into a plotly graph in R, we can follow the below steps −First of all, create a data frame.Then, create a ggplot2 graph and save it in an object.After that, load plotly package and create the ggplot2 graph using ggplotly function.Create the data frameLet's create a data frame as shown below −x