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In R programming, mostly the columns with string values can be either represented by character data type or factor data type. For example, if we have a column Group with four unique values as A, B, C, and D then it can be of character or factor with four levels. If we want to take the subset of these columns then subset function can be used. Check out the example below.Consider the below data frame −Exampleset.seed(888) Grp
The categorical variables can be easily visualized with the help of mosaic plot. In a mosaic plot, we can have one or more categorical variables and the plot is created based on the frequency of each category in the variables. To create a mosaic plot in base R, we can use mosaicplot function. The categories that have higher frequencies are displayed by a bigger size box and the categories that have less frequency are displayed by smaller size box.Consider the below data frame −Examplex1
In data analysis, we often face inappropriate data and hence the data analysis becomes difficult. An example of inappropriate data is reading missing values with a different value by naming them as Missing or Not Available. It can be done by using below syntax −Syntaxlevels(“data_frame_name”$”Column_name”)[levels(“data_frame_name”$”Column_name”=="Missing"]
We can plot numerical values in R with many scales and that includes log scale as well. Also, it is possible to plot the values with log scales on both the axes. In base R, the best way to do this is defining the axes values with decimal representation as shown in the below examples with well-defined log.Consider the below vector −Exampleset.seed(555) x
Suppose we have a data frame df1 that contains 5 columns and another data frame df2 that contains only column but the data type of the columns in both the data frames is same. Now we might want to add the column of the second data frame starting at the end of the rows of the first data frame by creating the same number of columns as in first data frame. This might be required by researchers to understand the impact of an external variable on the result of the analysis and it can be done with the help of ... Read More
Finding the position of one of more values that are common in two vectors can be easily done with the help of match function. The match function will match the values in first and second vector then return the index or position of these common values in second vector.Exampleset.seed(145) x1
To create the simple logistic model, we need to use glm function with family = binomial because the dependent variable in simple logistic model or binomial logistic model has two categories, if there are more than two categories then the model is called as multinomial logistic model. If we want to extract the odds ratio of slope and intercept from the simple logistic model then exp function needs to be used with model object as shown in the below examples.Exampleset.seed(999) x1
Mostly, we get data that contain column names in lowercase or just first letter is in upper case. If we want to convert those column names to all capital letter words or uppercase then toupper function can be used to the names of the columns. This can be done by using the below syntax −Syntaxnames(“data_frame_name”)
To find the rank of a vector of elements we can use rank function directly but this will result in ranks from smallest to largest. For example, if we have a vector x that contains values 1, 2, 3 in this sequence then the rank function will return 1 2 3. But if we want to get ranks from largest to smallest then it would be 3 2 1 and it can be done in R as rank(-x).Examplex1
We can use str_detect function to check whether a single string or a vector of strings is in lowercase or uppercase. Along with str_detect function, we need to use either upper or lower to check whether the string is in lowercase or uppercase and the output will be returned in TRUE or FALSE form, if the string will be in lowercase and we pass lower with str_detect function then the output will be TRUE and vice-versa.Examplex1