Programming Articles - Page 902 of 3363

When we create a correlation plot using corrplot the correlation among variables is displayed on the plot, if we want to disable some of those correlations then we first need to set them to NA in the correlation matrix and then use the corrplot function with na.label set to blank as " ".Check out the below given example to understand how it works.ExampleFollowing snippet creates a sample data frame −x

To create bar plot with positive and negative values, we can make use of ggplot function.For example, if we have a data frame called df that contains a categorical column say C and a numerical column Num which has some positive and some negative values then the bar plot for this data can be created by using the below command −ggplot(df,aes(C,Num))+geom_bar(stat="identity")ExampleFollowing snippet creates a sample data frame −Category

To find the degrees of freedom of residual from a regression model, we can use the function df.residual along with the model object.For example, if we have a regression model stored in an object called Model then the degrees of freedom of residual for the same model can be found by using the command mentioned below −df.residual(Model)Example 1Following snippet creates a sample data frame −x1

To find the power of t test, we can use pwr.t.test function of pwr package where we can pass the arguments for type of the test such as one sample or two sample, alternative hypothesis such as one-sided or two-sided, significance level, difference for two samples, and the sample size.Check out the below examples to understand how it works.Example 1To find the power of t test in R, use the code given below −library("pwr") pwr.t.test(n=100, d=1, sig.level=0.05, type="two.sample", alternative="two.sided")If you execute the above given code, it generates the following output for the two-sample t test power calculation −   n = ... Read More

To combine two data frames by filling NA in empty places, we can use rbind_fill function of plyr package.For example, if we have two data frames say DF1 and DF2 that have some common and some uncommon columns then we can combine them by using the below given command −rbind.fill(DF1,DF2)ExampleFollowing snippet creates a sample data frame −df1

To decrease the width of bars for plotly bar chart, we can use layout function and set the autosize argument to FALSE.For example, if we have a data frame called that contains a categorical column C and a numerical column Count then bar chart with decreased width of the bars can be created by using the below command −plot_ly(df,x=x,y=y,type="bar")%>%layout(autosize=F)ExampleFollowing snippet creates a sample data frame −x

To convert a table into matrix in R, we can use apply function with as.matrix.noquote function.For example, if we have a table called TABLE then we can convert it into a matrix by using the command given below −apply(as.matrix.noquote(TABLE),2,as.numeric)Example 1Following snippet creates a dataframe −x1

To create a scatterplot with colors as group, we can define the colors in col argument as characters.For Example, if we have two vectors then we can create scatterplot between x and y with red and blue colors for x and y value by using the below mentioned command −plot(x,y,col=as.character(cut(x,2,labels=c("red","blue"))))ExampleFollowing snippet creates a sample data frame −x

To create a rolling mean column by displaying means to corresponding values in R data frame, we can use ave function with rep function.For Example, if we have a data frame called df that contains a numerical column say X then we can create a rolling mean column for every 5 values by using the below mentioned command −df$Rolling_M_5

To combine two columns in R data frame with comma separation, we can use paste function with sep argument.For Example, if we have two columns say X and Y in a data frame called df then we can combine the values of these two columns in a new column with comma separation by using the below mentioned command −df$Combined