How to import Kaggle datasets directly into Google Colab?
Kaggle is a popular online platform for data science and machine learning competitions, datasets, and tutorials. You can find high-quality data on Kaggle to practice data analysis. I have uploaded some of my data on Kaggle to share it with others. Recently, I’ve begun learning machine learning, and one of the most fundamental datasets for this purpose is the Titanic dataset. By visiting the website below, you can download the Titanic survivor data and practice machine learning with this foundational…
How to Perform Cumulative Sum in R?
Data created Cumulative Sum per group © 2022 – 2023 https://agronomy4future.com
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?…
How to run R codes in Visual Studio Code? A Step-by-Step Guide
Visual Studio Code is a free and open-source code editor developed by Microsoft. It is a versatile editor that supports a wide range of programming languages, including, but not limited to, R, Python, SQL, JavaScript, TypeScript, Java, C#, and many others. The software provides a unified and user-friendly interface for developers working with different languages, making it a popular choice across various programming communities. Now, I’m working on my SQL code in Visual Studio Code, and recently, I’ve also been…
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…
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,…
How to convert an uploaded data table to a data frame in R?
Let’s say I uploaded a 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()…
How to Upload Data from GitHub Using R and Python?
I have soybean yield data that I want to upload to Github and access from R. First, let’s upload the data to Github. The data should be in .csv format. Click Add file, choose Upload files, and, after uploading, select the Raw button to view the data in .csv format as text. and you can find the address for this data, starting with https://raw.githubusercontent.com/… Let’s copy this address. Next, I’ll bring this data into R from Github. Before that, let’s…
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
Example of a Time Series Graph for Temperature Using R
© 2022 – 2023 https://agronomy4future.com
2024 Mission Statement
Manifesto: Transform each day into a canvas with a work of art as a project, shaped by the strokes of life. [1] I strive to make today better than yesterday. [1.1] In 2024, I document my daily life with a single photo that encapsulates each day.[1.2] In 2024, I compile my top 10 news on a weekly, and monthly basis.[1.3] In 2024, I write one column per month on my blog.[1.4] In 2024, I set daily, weekly, and monthly goals…
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…
[슬기로운 어바나-샴페인 생활 101] 어바나-샴페인 맛집 탐방
“슬기로운 어바나-샴페인 생활 101” 은 제가 초기 정착 때 경험한 것들을 시간별로 정리해서 새롭게 오시는 분들에게 필요한 정보를 공유하는 것을 목적으로 하는 프로젝트 입니다. 목차 1. 한국에서 어바나-샴페인 (Urbana-Champaign) 가는 방법 2. 어바나-샴페인에서 집 구하기 가이드 3. 일리노이 주 운전면허 필기시험 기출문제 한국어 번역: 이것만 보고 가시면 무조건 필기 합격!! 4. 일리노이주 운전면허 신청 방법 5. UIUC 학생증/교직원 카드 신청하기 6. 은행계좌 개설하기 7. 의료보험 가입하기 8. 대중교통 (버스) 이용하기 9. 학교 식당 (Dining hall) 10. 한식재료 구매하기 ### S1….
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 This value is the same as that in the column. © 2022 –…
[슬기로운 어바나-샴페인 생활 101] 세금 환급 (Tax Refund) 받기 (feat. 세금환급 대행 회사 추천)
“슬기로운 어바나-샴페인 생활 101” 은 제가 초기 정착 때 경험한 것들을 시간별로 정리해서 새롭게 오시는 분들에게 필요한 정보를 공유하는 것을 목적으로 하는 프로젝트 입니다. 목차 1. 한국에서 어바나-샴페인 (Urbana-Champaign) 가는 방법 2. 어바나-샴페인에서 집 구하기 가이드 3. 일리노이 주 운전면허 필기시험 기출문제 한국어 번역: 이것만 보고 가시면 무조건 필기 합격!! 4. 일리노이주 운전면허 신청 방법 5. UIUC 학생증/교직원 카드 신청하기 6. 은행계좌 개설하기 7. 의료보험 가입하기 8. 대중교통 (버스) 이용하기 9. 학교 식당 (Dining hall) 10. 한식재료 구매하기 ### S1….
[슬기로운 어바나-샴페인 생활 101] Chicago 여행 하기
“슬기로운 어바나-샴페인 생활 101” 은 제가 초기 정착 때 경험한 것들을 시간별로 정리해서 새롭게 오시는 분들에게 필요한 정보를 공유하는 것을 목적으로 하는 프로젝트 입니다. 목차 1. 한국에서 어바나-샴페인 (Urbana-Champaign) 가는 방법 2. 어바나-샴페인에서 집 구하기 가이드 3. 일리노이 주 운전면허 필기시험 기출문제 한국어 번역: 이것만 보고 가시면 무조건 필기 합격!! 4. 일리노이주 운전면허 신청 방법 5. UIUC 학생증/교직원 카드 신청하기 6. 은행계좌 개설하기 7. 의료보험 가입하기 8. 대중교통 (버스) 이용하기 9. 학교 식당 (Dining hall) 10. 한식재료 구매하기 ### S1….
Vertical Text Alignment in R
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…
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…
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…
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…
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….
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,…
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…
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…
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…
How to draw boxplot graph using R?
Python Data Preprocessing: Practice
Before diving into in-depth data analysis, a crucial step is data preprocessing. This essential process not only ensures better data quality but also significantly improves the efficiency of your analysis. In this guide, I will introduce a range of powerful Python methods for data preprocessing, equipping you with the tools to optimize your data for more accurate and insightful analysis. I use Goolge Colab when using Python because it’s more user friendly. Please refer how to setup Google Colab in…
The Science of Apical Dominance: Why Topping is Critical for Hemp Plants?
In hemp cultivation, “topping” refers to the process of selectively cutting off the upper portion of the plant during its vegetative (growth) phase. This practice holds a central and essential role in plant training, as it encourages horizontal growth and optimizes light utilization, resulting in increased yields. When a plant is topped, the two auxiliary buds located just below the cut site develop into full-fledged branches, often taking on a Y-shaped structure. These secondary branches can also be subjected to…