#Rstudio summary install
The syntax is generally packagename::palette and you will usually have to install the package before accessing the palette. The summary() command works for both matrix and data frame.
#Rstudio summary code
You can run this line of code to look at all the color options: info_paletteer(color_pkgs = NULL) The summary command is, therefore, more useful as we can see minimum, maximum, mean, etc values. Before adding color to your table, you will need to complete a few additional steps.įirst, install a few new packages and choose a color palette from the many available: install.packages("paletteer") Mean body mass of penguins on different islandsįinally, you can both group and color your columns to help the viewer differentiate between the species. To learn more about these and other customizations, see the kableExtra vignette. Kable_material_dark(html_font = "Cambria") You can also adjust the font size: kable(x = penguin_sum, Kable_classic(full_width = FALSE, html_font = "Cambria", font_size=16) Additional options with kableExtra include changing the font: kable(x = penguin_sum, To change the width of the table, add full_width = FALSE within your kable_styling() (or similar) argument. Some other options to consider as alternatives to kable_styling() are: kable_classic(), kable_paper(), kable_classic_2(), kable_minimal(), kable_material() and kable_material_dark(). Add the function kable_styling() to get the basic kableExtra format: kable(x = penguin_sum,Ĭaption = "Mean body mass of penguins on different islands over time") %>% Start with very similar code to what you used with the basic kable table. Mean body mass of penguins on different islands over timeįor additional customization options, use the package kableExtra. To make a possibly more appealing table with the same data, use kable(): kable(x = penguin_sum,Ĭol.names = c("Island", "Year", "Mean Body Mass (g)"),Ĭaption = "Mean body mass of penguins on different islands over time")
You can print the dataset within R/RStudio: penguin_sum # A tibble: 9 × 3
#Rstudio summary how to
This syntax uses the following basic syntax: summary (data) The following examples show how to use this function in practice.
Summarize(mean_body_mass_g = mean(body_mass_g, na.rm = TRUE)) %>% The summary () function in R can be used to quickly summarize the values in a vector, data frame, regression model, or ANOVA model in R. The below code calculates summary statistics, saved in a new dataset called penguin_sum. Look at the below examples which show the various types of. The syntax of the sum () function is sum (x,na.rmFALSE/TRUE) Vector is the easiest method to store multiple elements in R. In this tutorial, we will try to find the sum of the elements of the vector. (For more information on calculating summary statistics, see the Data Wrangling) section.) Let’s learn how to find the sum of the values with the help of the sum () in R. Using the palmerpenguins data, calculate the mean value of penguin body mass (g) across islands over time. Summary tables can be useful for displaying data, and the kable() function in the R package knitr allows you to present tables with helpful formatting.įirst, install and load the package. The Summarizing data page shows how to compute summaries of your data.
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