A frequency table is very often used by statisticians when they are studying categorical data to understand how frequently a variable appears in their data set. If you plan on entering the industry as a data analyst or even if your work remotely involves the use of data to make decisions, then you will be coming across frequency tables all the time. It is therefore essential to have an understanding of how frequency tables work and how you can quickly construct one.
There are several easy ways to create an R frequency table, ranging from using the factor and table functions in Base R to specific packages. Good packages include ggmodels, dplyr, and epiDisplay. In this tutorial, I will be going over some techniques of generating frequency tables using R. It contains information about the mileage, number of forward gears, number of carburetors and cylinders for various cars. You can load the data set into your environment using the data function.
The most common and straight forward method of generating a frequency table in R is through the use of the table function. In this tutorial, I will be categorizing cars in my data set according to their number of cylinders.
I can now use the table function to see how many cars fall in each category of the number of cylinders. This tells me that 11 cars have 4, 7 cars have 6 and 14 cars have 8 cylinders.
Moreover, the table is not stored as a data frame and this makes further analysis and manipulation quite difficult. The number of ways through which you can perform a simple task in R is exhaustive and each method has its own pros and cons.
It gives you a highly featured report of your data that includes frequency, cumulative frequencies and proportions. If, for instance, you wish to know what percentage of cars have 8 cylinders or what fraction of cars have 4 gears, this method allows you to get your answer using the same report. Up till now, we have talked about frequency or the count of appearance of one variable in a data set, but for data analysts, an important task would be to generate a frequency with 2, 3 or even more variables.
Such a table is also called a Cross Table or a Contingency Table. When talking about frequency tables, I find it important to extend the discussion to tables with higher number of variables as well.
If I talk about the data set that I am using in this tutorial, suppose I want to know how many cars use a combination of 4 cylinders and 5 forward gears. One way would be to do this manually using two different frequency tables, but that method is quite inefficient especially if my data set had more variables.
It not only gives me a frequency count but also the proportions and the chi square contribution of each category. This is optional but when specified, it gives me the row percentages and the column percentages for each category. This information is particularly useful when you want to compare one variable with another. Getting the frequency count is among the very first and most basic steps of a data analysis. Although R gives you many different ways to get the frequency of variables in your data set, I normally find it helpful to get acquainted with a number of methods instead of just one or two.
This is because the type of table you need to generate depends largely on what you want to achieve from your data. Syed Abdul Hadi is an aspiring undergrad with a keen interest in data analytics using mathematical models and data processing software. His expertise lies in predictive analysis and interactive visualization techniques.
Reading, travelling and horse back riding are among his downtime activities. Basic Frequency Table in R. EpiDisplay Example — frequency table in R. Relative Frequency Table in R. CrossTables in R — Example.You can report issue about the content on this page here Want to share your content on R-bloggers? For example, you can extract the kernel density estimates from density and scale them to ensure that the resulting density integrates to 1 over its support set.
I recently needed to get a frequency table of a categorical variable in R, and I wanted the output as a data table that I can access and manipulate. This is a fairly simple and common task in statistics and data analysis, so I thought that there must be a function in Base R that can easily generate this. Sadly, I could not find such a function. The cars in this data set have either 3, 4 or 5 forward gears. How many cars are there for each number of forward gears? You can correct this problem with the names function.
I finally have what I want, but that took several functions to accomplish. Is there an easier way? As the class function confirms, this output is indeed a data frame! Filed under: Applied StatisticsCategorical Data AnalysisData AnalysisDescriptive StatisticsR programmingStatisticsTutorials Tagged: categorical variableclasscountdata framefactorfrequency tableinstall.
I'm new with R. I need to generate a simple Frequency Table as in books with cumulative frequency and relative frequency. You're close! There are a few functions that will make this easy for you, namely cumsum and prop. Here's how I'd probably put this together. I make some random data, but the point is the same:.
The base functions tablecumsum and prop. With cbind and naming of the columns to your liking this should be pretty easy for you in the future. The output from the table function is a matrix, so this result is also a matrix. If this were being done on something big it would be more efficient todo this:. If you are looking for something pre-packaged, consider the freq function from the descr package. Learn more. How to generate a frequency table in R with with cumulative frequency and relative frequency Ask Question.
Asked 8 years, 3 months ago. Active 3 years, 7 months ago. Viewed 91k times. Sturges x as. Active Oldest Votes. Sturges x Tabulate and turn into data. Chase Chase It worked nice, it was confusing me that the display of the data is done as a data frame instead of a table.
Formatting as a data. Good luck!
How to Make a Frequency Table in R
Lots of good info here on SO and plenty of people who like answering questions. Sandy Muspratt Sandy Muspratt My suggestion is to check the agricolae package Thomas Orozco Afranio Vieira Afranio Vieira 1. Sign up or log in Sign up using Google.This time, what could more more fascinating an aspect of analysis to focus on than: frequency tables?
OK, most topics might actually be more fascinating. Especially when my definition of frequency tables here will restrict itself to 1-dimensional variations, which in theory a primary school kid could calculate manually, given time. But they are such a common tool, that analysts can use for all sorts of data validation and exploratory data analysis jobs, that finding a nice implementation might prove to be a time-and-sanity saving task over a lifetime of counting how many things are of which type.
I would like to know how many observations e. The dataset I will use in my below example is similar to the above table, only with more records, including some with a blank missing type. A super simple way to count up the number of records by type. It does have a useNA parameter that will show that though if desired. I tested 5 options, although there are, of coursecountless more. In no particular order:.
Several came very close. I would recommend looking at any of the janitor, summarytools and questionr package functions outlined below if you have similar requirements and tastes to me. This is a pretty good start! By default, it shows counts, percents, and percent of non-missing data. It can optionally sort in order of frequency. It the output is tidy, and works with kable just fine.
The only thing missing really is a cumulative percentage option. This one is pretty fully featured. It even optionally generates a visual frequency chart output as you can see above. It shows the frequencies, proportions and cumulative proportions both with and without missing data. It can sort in order of frequency, and has a totals row so you know how many observations you have all in.Calculates absolute and relative frequencies of a vector x.
Continuous numeric variables will be cut using the same logic as used by the function hist. Categorical variables will be aggregated by table. The result will contain single and cumulative frequencies for both, absolute values and percentages. Default taken from the function hist. This is ignored if x is not of numeric type. Ignored if x is not of numeric type. Default is "level"other choices are 'by frequency' "descending" or "ascending" or 'by name of the levels' "name".
How to Calculate a Frequency Table in R
The argument can be abbreviated. This is ignored if x is numeric. Defines whether to include extra NA levels in the table. Defaults to "no" which is the table default too. Use dig. Use the argument right to define if the intervals should be closed on the right and open on the left or vice versa. In print. Freq the dots are not used. If breaks is specified as a single number, the range of the data is divided into breaks pieces of equal length, and then the outer limits are moved away by 0.
If x is a constant vector, equal-length intervals are created that cover the single value. PercTablecuthistcumsumtableprop.
Created by DataCamp. Frequency Table for a Single Variable Calculates absolute and relative frequencies of a vector x.R in Action 2nd ed significantly expands upon this material. This section describes the creation of frequency and contingency tables from categorical variables, along with tests of independence, measures of association, and methods for graphically displaying results.
R provides many methods for creating frequency and contingency tables. Three are described below. In the following examples, assume that A, B, and C represent categorical variables.
You can generate frequency tables using the table function, tables of proportions using the prop. In this case, use the ftable function to print the results more attractively. Table ignores missing values. The xtabs function allows you to create crosstabulations using formula style input. If a variable is included on the left side of the formula, it is assumed to be a vector of frequencies useful if the data have already been tabulated.Creating frequency tables in R using dplyr
It has a wealth of options. There are options to report percentages row, column, cellspecify decimal places, produce Chi-square, Fisher, and McNemar tests of independence, report expected and residual values pearson, standardized, adjusted standardizedinclude missing values as valid, annotate with row and column titles, and format as SAS or SPSS style output!
See help CrossTable for details. For 2-way tables you can use chisq. By default, the p-value is calculated from the asymptotic chi-squared distribution of the test statistic.
Optionally, the p-value can be derived via Monte Carlo simultation. Use the mantelhaen. You can use the loglm function in the MASS package to produce log-linear models.
For example, let's assume we have a 3-way contingency table based on variables A, B, and C. Mutual Independence : A, B, and C are pairwise independent.By Andrie de Vries, Joris Meys. Whenever you have a limited number of different values in R, you can get a quick summary of the data by calculating a frequency table. A frequency table is a table that represents the number of occurrences of every unique value in the variable.
In R, you use the table function for that. You can tabulate, for example, the amount of cars with a manual and an automatic gearbox using the following command:. This outcome tells you that your data contains 13 cars with an automatic gearbox and 19 with a manual gearbox. As with most functions, you can save the output of table in a new object in this case, called amtable. At first sight, the output of table looks like a named vector, but is it? The table function generates an object of the class table.
These objects have the same structure as an array.
Arrays can have an arbitrary number of dimensions and dimension names. Tables can be treated as arrays to select values or dimension names. With over 20 years of experience, he provides consulting and training services in the use of R. How to Calculate a Frequency Table in R.