Insightful Analytics
Krunal Lathiya 
The grepl() function (stands for “grep logical”) in R searches for patterns within each element of a character vector. It returns a logical vector of the same length as input, where each value is either TRUE or FALSE. If the pattern matches that specific element, it returns TRUE. Otherwise, it returns FALSE. The above figure … Read more
The zip() function creates a new zip archive file. You must ensure that the zip tool is available in your system to work with zip() functions. For example, Windows and Mac systems have built-in zip tools, but Linux does not have a tool; you need to install it separately. Then, you can use this zip() function … Read more
When working with file systems, checking the directory or file existence is always better before commencing the operations. For a directory To create a directory, if it does not exist, use the dir.exists() function. After checking its existence, if it does not exist, you can use the dir.create() function to create a new directory with a specified … Read more
To create a grouped boxplot in R, we can use the ggplot2 library’s aes() and geom_boxplot() functions. The aes() function maps the continuous and categorical variables to visual properties of a plot. The geom_boxplot() function creates a boxplot. There is a difference between a standard boxplot and a grouped boxplot. A standard boxplot provides a … Read more
For data exploration, quickly inspecting the data, verifying the structure, or debugging large datasets, we need some kind of tool that helps prevent excessive data flooding in the console. That’s where head() and tail() generic functions come into play. head() function The head() function displays the first n parts of the vector, matrix, table, or … Read more
The %in% operator checks if elements of one vector are present in another vector. It returns a logical vector of the same length as the left-side argument. Each element in the output is either TRUE or FALSE, depending on the value matching. If the value matches, it returns TRUE; otherwise, it returns FALSE. If you apply … Read more
The %in% operator checks whether the element is present. And NOT IN (%!in%) operator does the exact opposite. The %!in% is a custom operator that checks if the elements of one vector are not present in another vector. It returns a logical vector of the same length as the left-hand vector, with TRUE for those … Read more
For understanding the central tendency of your input dataset, you need to calculate the basic summaries like mean, median, and mode. It gives you the data distribution, which tells you whether it is symmetrical or skewed. Mean Mean means the arithmetic average of a number in mathematics. An average is the sum of the total … Read more
Calculating Standard Deviation (SD) by group in a Data Frame essentially means finding the SD of a specific numeric column separately for each unique categorical variable (column) or group. It allows us to see how the data variability differs across the groups. Here are three ways to calculate SD by group: Using dplyr Using data.table … Read more
When we say summarise multiple columns, it means aggregate the input data by applying summary functions (sum, mean, max, etc.) to multiple numeric columns simultaneously. The below image describes visually: If grouping is required, you can group by a specific categorical column and get the statistics for each group. The dplyr package provides the summarise() … Read more
