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Category: R programming

How to Convert Time to Numeric for Line Graphs in R?

How to Convert Time to Numeric for Line Graphs in R?

Here is one dataset. With this data, I’ll create a line graph to show the change in day length over time. First, let’s transpose the columns to rows using pivot_longer(). I’ll sort the data by Day and Month, but since the month column is in text format, sorting it from January to December directly isn’t feasible. Therefore, I’ll add a number corresponding to each month for sorting purposes. Now, I can sort by ‘month1’ and ‘Day’ from January 1 to…

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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…

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How to add separate text to panels divided by facet_wrap() in R?

How to add separate text to panels divided by facet_wrap() in R?

□ Graph Partitioning Using facet_wrap() in R Studio□ How to customize the title format in facet_wrap()? In my previous posts, I introduced how to divide panels in one figure using facet_wrap(). Today, I’ll introduce how to add separate text to panels. First, let’s make sure we have the required packages installed. I’ll create a dataset as shown below: Next, I’ll reshape the dataset into columns to facilitate data analysis. And then, I’ll summarize this data using descriptive statistics. Finally, I’ll…

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In R, Drawing Lines with Different X-axis Starting Positions

In R, Drawing Lines with Different X-axis Starting Positions

In R, I want to draw a line in a graph, and first, I’ll create the data. Next, I’ll create a bar graph. In this graph, I want to draw a horizontal line. The code to draw lines is introduced in the post below. □ Drawing Lines in ggplot() I added a horizontal line to represent the mean yield of all cultivars. Next, I would like to draw a horizontal line starting from Cultivar B. How can this be achieved?…

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Matching Datasets in R: An Approach Comparable to Excel’s VLOOKUP Function

Matching Datasets in R: An Approach Comparable to Excel’s VLOOKUP Function

I have two datasets. Now, I want to combine these two datasets, but the row numbers differ between the two datasets. In dataB, the 3rd replicate for Tr1 and the 2nd replicate for Tr3 were deleted due to environmental errors. In this case, simply combining the two datasets is not feasible. One solution is to merge them row-wise using the rbind() function. This way, the two datasets will be combined by row. However, my goal is to combine the two…

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How to run R codes in Google Colab?

How to run R codes in Google Colab?

Google Colab is essentially a Jupyter notebook environment, which means that typically only Python code works. However, it is also possible to use R code in Google Colab. If you’re unfamiliar with Google Colab, please read the post below to grasp its general concept. □ How to use Google Colab for Python (power tool to analyze data)? When opening a new Google Colab window, navigate to Runtime in the menu, choose Change runtime type, and a new window will appear,…

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How to convert an uploaded data to code in R?

How to convert an uploaded data to code in R?

Let’s upload one dataset to R. Now, I want to save this data as code so that I can store it in my web note. This is because it would be difficult to find the original dataset after a long time. Therefore, I want to save it as text code in a list on my web note. 1) using dput() First, we can use dput() function. 2) using datapasta() Second, we can use datapasta() function 3) using constructive() This is…

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Customizing R Graphs: Splitting Text into Two Rows

Customizing R Graphs: Splitting Text into Two Rows

I have a dataset as below. Now, I want to create a bar graph about this data. First, let’s summarize the data. Then, let’s create a bar graph. Now, to save space, I’d like to split the x-axis text into two rows using the following code. When you run the same code to create a bar graph, the resulting graph is shown below. Code summary https://github.com/agronomy4future/r_code/blob/main/Customizing_R_Graphs_Splitting_Text_into_Two_Rows.ipynb © 2022 – 2023 https://agronomy4future.com

A Practical Approach to Linear Mixed-Effects Modeling in R

A Practical Approach to Linear Mixed-Effects Modeling in R

A Linear Mixed-Effects Model (LMM) is a statistical model that combines both fixed effects and random effects to analyze data with repeated measurements or hierarchical structure. Let’s break down the key components and concepts of a Linear Mixed-Effects Model: 1) Fixed Effects: 2) Random Effects: 3) Linear Mixed-Effects Model Equation: The general equation of a Linear Mixed-Effects Model can be written as: Y= Xβ + Zb + ε 4) Estimation: In summary, Linear Mixed-Effects Models are a powerful statistical tool…

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Step-by-Step Guide to Calculating and Adding Variable Means in R

Step-by-Step Guide to Calculating and Adding Variable Means in R

Here is one dataset. I want to add the mean of each treatment to a new column, and I am using the following code. However, the code is quite lengthy. Let’s simplify it using tapply() How about there are more variables? Now, I want to add the mean of the combination of treatment and environment. I want to calculate the mean of combination between A and North Full: https://github.com/agronomy4future/r_code/blob/main/Step_by_Step_Guide_to_Calculating_and_Adding_Variable_Means_in_R.ipynb We aim to develop open-source code for agronomy ([email protected]) © 2022…

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Enhancing Visualizations: Manipulating Color and Shape in R with Two Variables

Enhancing Visualizations: Manipulating Color and Shape in R with Two Variables

I have one dataset as below. Now, I’ll create a regression graph between grain number (GN) and average grain weight (AGW). I distinguished genotypes with different colors, and now I want to differentiate resistance (yes and no) using distinct shapes. Therefore, I’ll be changing the shape representation from genotype to resistance. However, the color is not currently applied to the legend. I aim to apply the provided color to the legend, and additionally, assign colors to represent different levels of…

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Exploring Best Linear Unbiased Estimators (BLUE) through Practical Examples in R

Exploring Best Linear Unbiased Estimators (BLUE) through Practical Examples in R

□ The Best Linear Unbiased Estimator (BLUE): Step-by-Step Guide using R (with AllInOne Package) In my previous post, I explained how to use R to perform the Best Linear Unbiased Estimator (BLUE). Now, this is a practical exercise focusing on BLUE in R. Here is one dataset. I have data on grain number (GN) and average grain weight (AGW) in winter wheat for about five genotypes and one transgenic line. The study examines the response to disease resistance (yes or…

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Performing Regression Analysis in R with Variables in the Same Column

Performing Regression Analysis in R with Variables in the Same Column

When analyzing regression, we typically assume that two continuous variables are situated in separate columns, allowing us to easily designate them as x and y. However, in many cases, data is organized vertically, and variables of interest are found within the same column. This vertical structuring is, in fact, the fundamental data arrangement when conducting data analysis. Now, let’s delve further into the discussion by examining the dataset. Let’s proceed by uploading the dataset.” This data pertains to iron content…

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Equivalent Functions: IF function in Excel vs. ifelse() in R

Equivalent Functions: IF function in Excel vs. ifelse() in R

When working with Excel, I believe you use the IF function from time to time, especially when categorizing values. The IF function is particularly useful for this purpose. Here is one example. I want to categorize organic matter (%) by unit 1.0. This process involves converting numeric variables to categorical variables. To achieve this, I have used the IF function as shown above. Then, you can categorize organic matter in the F column as shown above. Now, my next question…

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Efficient Multivariate Summary in R: A Guide to Analyzing Multiple Independent Variables

Efficient Multivariate Summary in R: A Guide to Analyzing Multiple Independent Variables

In my previous post, I introduced how to summarize data, such as mean, standard deviation, and standard error. However, at that moment, I demonstrated how to summarize only one variable. □ Streamlined Data Summary in R STUDIO: Enhancing Bar Graphs with Error Bars Now, let’s discuss this further with a dataset. I would like to summarize the Yield data, including the mean, standard deviation, and standard error. I’ll use ddply() Now, I also want to summarize variables GN and AGW….

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Converting Rows to Columns in R: A Guide to Transposing Data (feat. pivot_wider and pivot_longer)

Converting Rows to Columns in R: A Guide to Transposing Data (feat. pivot_wider and pivot_longer)

When data is arranged, it can be structured either vertically (row-based) or horizontally (column-based). The choice depends on your preference for organizing data. However, when running statistics, data should be arranged row-based, as variables need to be in the same column. On the other hand, when calculating per variable, it is much easier to organize data column-based, allowing for simpler calculations. Regardless of the approach, well-organized data is essential, and the ability to restructure data is a valuable skill. Today,…

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A Guide to Normalizing Data for Different Treatments in R

A Guide to Normalizing Data for Different Treatments in R

I have data, as shown below, regarding iron contents in soil and the plant uptake of iron at different growth stages in winter wheat. I want to analyze the relationship between the iron content in the soil and the plant uptake of iron at different growth stages in winter wheat. We can simply draw a regression graph. However, before doing that, we need to reshape the data. I’ll transpose the data from rows to columns based on the variables in…

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How to delete and change specific texts within a column in R?

How to delete and change specific texts within a column in R?

When we want to change texts within a columns, you can have several methods which I already introduced before. □ How to Rename Variables within Columns in R? However, changing all texts and specific texts would be different. Let’s upload a data. Now, we can change the variables name as following code: How about changing the text in the ID column? I want to remove ‘Delta_’ and keep only the numbers. Will you change the text one by one as…

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How to Upload and Combine Multiple Files In R?

How to Upload and Combine Multiple Files In R?

In a folder, I have 5 different .csv files. I want to upload these files to R and combine all of them because the data format (number of columns and structure) is the same. While you can certainly upload them one by one, imagine a scenario where you have 100 datasets. Will you upload all 100 of them individually? No! That would be a waste of time. In such cases, you can use a simple code to upload multiple files…

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Calculating Predicted Values for Each Group in Basic Modeling

Calculating Predicted Values for Each Group in Basic Modeling

□ The Best Linear Unbiased Estimator (BLUE): Step-by-Step Guide using R (with AllInOne Package) In my previous post, I explained how to estimate dependent values from fitting models. Now I’ll explain how to add this predicted value to the original data using R. First, let’s upload data to R. Now, I’ll predict yield using the model. I believe that ‘row’ represents a random factor for each treatment, so I’d like to adjust the residuals using BLUP (Best Linear Unbiased Predictor),…

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How to calculate responsiveness in response to control using R?

How to calculate responsiveness in response to control using R?

In my previous post, I explained how to quantify phenotypic plasticity and introduced the concept of ‘responsiveness.’ □ Quantifying Phenotypic Plasticity of Crops I introduced a formula to calculate responsiveness as (Treatment – Control) / Control. Genotype Control Treatment Responsiveness A 100 90 -10.0% B 120 70 -41.7% C 115 90 -21.7% D 95 85 -10.5% E 110 105 -4.5% However, when analyzing data, the format may not always be the same as above. Mostly, treatments (independent variable) are arranged in…

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How to customize the title format in facet_wrap()?

How to customize the title format in facet_wrap()?

□ Graph Partitioning Using facet_wrap() in R Studio By following my previous post, you can understand how to obtain the figure below. If you copy and paste the code above into your R console, you can obtain the same figure as shown above. Now, I’d like to change the title format by removing the title border. Next, I’d like to draw a line in the title. Please refer to the code below. full code: https://github.com/agronomy4future/r_code/blob/main/How_to_customize_the_title_format_in_facet_wrap().ipynb © 2022 – 2023 https://agronomy4future.com

Variable-Dependent Manipulation of Point and Line Sizes in R

Variable-Dependent Manipulation of Point and Line Sizes in R

I will randomly create a piece of data and then proceed to plot a line graph with points for this data. I have differentiated point colors and shapes based on the variable “Genotype”. In the above code, the value geom_point(size=5) sets the point size to 5 for both GenotypeA and GenotypeB. However, I would like to increase the point size specifically for GenotypeA. I will change the code from geom_point(size=5) to geom_point(aes(size=Genotype)). This means that I will adjust the point…

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Converting an Excel File to an R file: Optimizing File Size

Converting an Excel File to an R file: Optimizing File Size

Today, I will introduce a method for converting an Excel file into an R file. I have placed an Excel file in a folder named ‘DataBase’ on the desktop. This file contains wheat grain size data, with 96,320 rows and a size of approximately 15MB. When an Excel file is large, you may experience performance issues, such as Excel slowing down during data operations, especially if your computer has limited memory. It would be more convenient to convert this Excel…

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Drawing Lines in ggplot()

Drawing Lines in ggplot()

When using ggplot() to create multiple graphs, there are times when you might want to add separate lines to the graphs. Today, I’ll be posting about how to draw additional lines on graphs. Let’s start by generating a simple piece of data. Next, I will proceed to draw a regression graph for this data. 1) Drawing a 1:1 ratio line. To examine the slope of the regression line, I would like to draw a 1:1 ratio line. geom_abline (slope=1, linetype…

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