Browsed by
Tag: dplyr

Converting Character Values to Numeric in R: A How-To Guide

Converting Character Values to Numeric in R: A How-To Guide

First, let’s create a dataset. and observe the different data formats of each value. I have two sets of yield data: one in character format (yield column) and the other in numeric format (yield1 column). How to convert missing value to 0 when data is numeric? When data is numeric (yield1 column), and if there are missing values, how can we replace it to 0? or you can also use the following code. How to convert missing values to 0…

Read More Read More

How to create separate linear and quadratic regression graphs for each group in the same panel using R?

How to create separate linear and quadratic regression graphs for each group in the same panel using R?

When we draw regression lines for a group, they are usually of the same type, such as simple linear regression. Here is an example using yield data for different nitrogen rates per genotype. Then, the regression graph for each group would be shown below. I think it would be better to show the quadratic regression line for genotype A. In this case, how can we create separate linear and quadratic regression graphs for each group in the same panel? Data…

Read More Read More

Combining Factors from Separate Datasets into a Single Column Using R Studio (feat. dplyr package)

Combining Factors from Separate Datasets into a Single Column Using R Studio (feat. dplyr package)

When data is divided into two separate datasets, it needs to be combined into a single column. Using R, we can simply combine the two datasets. I will create a simple dataset. Now I will combine these two datasets into one. 1) using data.frame() To explain the below code simply, we are using the function data.frame() to combine two datasets. Regarding the repetition of the text “Defoliation,” it indicates repeating it by the number of times corresponding to the values…

Read More Read More