Server Side Programming Articles - Page 1283 of 2650

To add an extra point to scatterplot using ggplot2, we can still use geom_point function. We just need to use aes function for quoting with new values for the variables, also we can change the color of this point using colour argument. The display of an extra point will help us to distinguish between a threshold/new value and remaining values.Consider the below data frame −Example Live Demox

To extract words from a string vector, we can use word function of stringr package. For example, if we have a vector called x that contains 100 words then first 20 words can be extracted by using the command word(x,start=1,end=20,sep=fixed(" ")). If we want to start at any other word then starting value will be changed accordingly.Example Live Demox

To find the rate of return for a vector values, we can use the formula for rate of return. For example, if we have a vector called x then the rate of return can be calculated by using the syntax diff(x)/x[-length(x)]. The output will be in decimal form and if we want to convert it to percentage then the output needs to be multiplied with 100, we can also input the same within the formula as (diff(x)/x[-length(x)])*100.Example Live Demox1

Sometimes values in a string vector has an extra space at the end, this might happen while typing the values or due to some other manual errors. To remove spaces at the end in string vectors, we can use gsub function. For example, if we have a vector called x that contains string values with spaces at the end then the removal of values can be done by using the command gsub(" $","",x,perl=T)Example Live Demox1

The integer64 vector contains vector values that represents signed integers with values that range from negative 9,223,372,036,854,775,808 to positive 9,223,372,036,854,775,807. To create an integer64 vector, we can use as.integer64 function of bit64 package. The difference between integer64 vector and others is that a large number of values can be stored in the vector.Examplelibrary(bit64) x1

The pnorm function is used to find the probability for a normally distributed random variable. Probabilities such as less than mean, greater than mean, or probability between left- and right-hand side of the mean. If we want to use pnorm function on data frame columns then apply function can help us.Consider the below data frame −Example Live Demox1

To manually define the breaks for a histogram using ggplot2, we can use breaks argument in the geom_histogram function. While creating the number of breaks we must be careful about the starting point and the difference between values for breaks. This will define the number of bars for histogram so it should be taken seriously and should be according to the distribution of the data.Consider the below data frame −Example Live Demox

To fill NA values with next and previous values, we can use na.locf function of zoo package with fromLast = TRUE. This is the situation of a column as shown below −x 0 NA NA 1 1 NA 0 1The output after filling NA values with next and previous values will be −x 0 0 0 1 1 1 0 1Consider the below data frame −Example Live Demox1

The hiding of NA values does not mean removal of NA values. If we have some NA values in an R matrix then we can hide them using blanks with double quotes. For example, suppose we have a matrix called M that contains some NA values then M can be printed by hiding NA value using print.table(M,na.print="")Example Live DemoM1

To fix the lower value for X-axis in base R, we can use xlim argument in plot function. Mostly, we set the lower value to zero but it is not necessary it can be something else, either less than zero or greater than zero as well. If only lower value needs to be fixed then upper value will be set by using the max function as shown in the below example.Examplex