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Articles by Nizamuddin Siddiqui
Page 90 of 196
How to add a column in an R data frame with consecutive numbers?
Addition of a column with consecutive might have different objectives such as getting the sequence of numbers, representing serial numbers, representing ids, identification of each row, or a variable. We can use the sequence starting from any number up to the number of rows if we know the number of rows for this purpose.Example1Consider the below data frame:> x1 x2 df1 df1Output x1 x2 1 6.137898 5.203712 2 5.283467 5.057344 3 5.873749 4.907388 4 7.628762 5.012650 5 4.134700 4.988379 6 5.340686 4.684900 7 5.126999 4.821752 8 3.722762 4.974044 9 4.097969 ...
Read MoreWhy scale_fill_manual does not fill the bar with colors created by using ggplot2 in R?
We can manually fill the color of bars in a bar plot which is created by using ggplot2 but for this we would be needing color aesthetics already used for the bars. That means we need to use filling of bars inside aes of ggplot2 and then the colors can be mentioned inside the scale_fill_manual function.ExampleConsider the below data frame:> x count df dfOutputx count 1 A 321 2 B 324 3 C 320 4 D 328Loading ggplot2 package and creating bar plot:Example> library(ggplot2) > ggplot(df, aes(x, count))+geom_bar(stat="identity")Output:Creating the bar plot by using scale_fill_manual:Example> ggplot(df, aes(x, count))+geom_bar(stat="identity")+scale_fill_manual(values=c("blue", "green", "grey", "yellow"))OutputThis ...
Read MoreHow to create a covariance matrix in R?
To create a covariance matrix, we first need to find the correlation matrix and a vector of standard deviations is also required. The correlation matrix can be found by using cor function with matrix object. For example, if we have matrix M then the correlation matrix can be found as cor(M). Now we can use this matrix to find the covariance matrix but we should make sure that we have the vector of standard deviations.Example1> M1 M1Output [, 1] [, 2] [, 3] ...
Read MoreHow to find the residual of a glm model in R?
In a linear model, a residual is the difference between the observed value and the fitted value and it is not different for a general linear model. The difference between linear model and the general linear model is that we use a probability distribution to create a general linear model. If we want to find the residual for a general linear model then resid function can be used just like it is used with the linear model.Example1Consider the below data frame:> x1 y1 df1 df1Output x1 y1 1 4 2 2 3 3 3 5 3 4 4 2 5 ...
Read MoreHow to create a bar chart using plotly in R?
Plotly in R is a package specifically designed to create highly-interactive and publication-quality charts. The chart can be created by using plot_ly function of the package and there are three main arguments of plot_ly defined as x, y, and type, where x refers to the X-axis, y refers to the Y-axis and type refers to the chart type but the axes values are stored in a data frame or itself a shared.ExampleLoading plotly package:> library(plotly)Consider the below data frame:> x count df dfOutputx count 1 A 321 2 B 324 3 C 320 4 D 328Creating the bar plot for ...
Read MoreHow to display the curve on the histogram using ggplot2 in R?
Mostly, we use histogram to understand the distribution of a variable but if we have an overlay line on the histogram that will make the chart smoother, thus understanding the variation will become easy. To display the curve on the histogram using ggplot2, we can make use of geom_density function in which the counts will be multiplied with the binwidth of the histogram so that the density line will be appropriately created.ExampleConsider the below data frame:> x df head(df, 20)Output x 1 4 2 5 3 6 4 4 5 9 6 ...
Read MoreHow to create a vector of lists in R?
If we have many lists but we want to use the values in the lists as a vector then we first need to combine those lists and create a vector. This can be done by using unlist function along with the combine function c to create the vector. For example, if we have two lists defined as List1 and List2 and we want to create a vector V using these lists then it can be created as:V x1 x1Output$a [1] -0.6972237 -1.5013768 -0.2451809 -0.2365569 -1.6304919 -1.1704378 [7] 1.1617054 -0.2349498 -1.2582229 0.4112065 $b [1] 2 0 2 6 0 0 ...
Read MoreHow to replace a sub-string with the reverse of that sub-string in R?
The chartr function in base R helps us to replace old strings with new strings and hence it can be also used to replace a subs-string with the reverse of that substring. For example, if we have a vector say x that contains tutorialpsoint and we want to convert it to tutorialspoint then it can be done as chartr("tutorialpsoint ", " tutorialspoint ", x).Example1> x1 x1Output[1] "IDNIA"Example> chartr("DN", "ND", x1)Output[1] "INDIA" Example2> x2 x2Output[1] "IDNIA" "IDNIA" "IDNIA" "IDNONESIA" "IDNIA" "IDNONESIA" [7] "IDNONESIA" "IDNIA" "IDNONESIA" "IDNIA" "IDNIA" "IDNONESIA" [13] "IDNONESIA" "IDNONESIA" "IDNIA" "IDNONESIA" "IDNIA" "IDNIA" [19] "IDNONESIA" "IDNONESIA" "IDNIA" "IDNONESIA" "IDNIA" ...
Read MoreHow to find the mean of row values in an R data frame using dplyr?
The mean of row values can be found by using rowwise function of dplyr package along with the mutate function to add the new column of means in the data frame. The rowwise function actually helps R to read the values in the data frame rowwise and then we can use mean function to find the means as shown in the below examples.Example1Consider the below data frame:> x1 x2 df1 df1Output x1 x2 1 0 8 2 2 3 3 2 5 4 0 5 5 3 2 6 0 10 7 3 5 8 1 7 9 0 4 ...
Read MoreHow to perform chi square test for goodness of fit in R?
The chi square test for goodness of fit is a nonparametric test to test whether the observed values that falls into two or more categories follows a particular distribution of not. We can say that it compares the observed proportions with the expected chances. In R, we can perform this test by using chisq.test function. Check out the below examples to understand how it is done.Example1> x1 x1Output[1] 9 4 1 9 6 6 1 6 0 0 5 8 8 3 7 8 0 3 3 9 6 0 3 8 2 0 8 5 9 1 3 4 ...
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