Stories about crops and statistics (plus coding)
I have one big dataset. Let’s upload to R. This data has 96,319 data rows. I want to use some part of this data. How can I randomly extract some data from the whole dataset. First, I’ll add number from 1 to the end of the data row to provide ID of each data row. … Read more
Stepwise selection, forward selection, and backward elimination are all methods used in the context of building statistical models, specifically regression models, where the goal is to select the most relevant predictors. In this section, I’ll introduce one by one. Let’s generate one dataset. This dataset includes grain yield data, along with measurements of stem biomass, … Read more
When uploading data to R, we first need to check the data structure before analyzing it. Here are some tips for checking the data structure in R. First, I’ll upload a dataset from my GitHub. In this dataset, let’s check the structure of the data. ■ Code to display the first or last certain rows … Read more
Today, I’ll introduce one method for data normalization, utilizing the biomass with N and P uptake data available on my GitHub. I also aim to create regression graphs illustrating the relationship between biomass and either nitrogen or phosphorus. First, I’ll generate a regression graph for biomass with either nitrogen or phosphorus to observe the data … Read more
Let’s say we collected relative light intensity data across a wide range of the light spectrum in an LED experiment. and I’d like to create light spectrum curves regarding relative light intensity. First, I’ll define wavelength colors. The color at different ranges of wavelengths is always the same, so if we run this code, we … Read more
In my previous post, I introduced the necessity of data normalization in visualizing data. By following that post, you may gain an understanding of how we can organize data according to our preferences. □ Why is data normalization necessary when visualizing data? Today, I’ll introduce various methods for data normalization, utilizing the biomass with N … Read more
In the hemp field, we planted hemp seeds last week (on 4/14), and now we’re awaiting emergence from the soil.
Data normalization is necessary when visualizing data for several key reasons, and I believe the most important reason is for scale uniformity. Different data variables can have vastly different scales and units. For example, grain yield might be in Mg/ha, while nutrient contents might typically range from %. Normalizing these data to a common scale … Read more
Here is one dataset, and I’ll use facet_wrap() to create bar graphs. First, let’s summarize the data. Then, I’ll create a bar graph using facet_wrap() to divide panels by irrigation. Now, I want to draw a y-axis border for the ‘Irrigation_Yes’ panel. We can achieve this simply by adding scales=”free”. We aim to develop open-source … Read more
Setting up experimental design according to your experiment goal is the first step to achieve your experiment’s success. In Agronomy studies, experimental design involves the combination of treatments deployed in the field, and these treatments should be randomized. Randomization is important in experimental design as it helps our experiments avoid biases due to physical or … Read more
□ How to convert character to POSIXct format in R? In my previous post, I created a curve graph like the one shown below. The curve on the graph appears to be not very smooth, and I want to make it smoother. Therefore, I will add geom_smooth(), but the method will be method=”gam” code summary: … Read more
Here is one dataset Let’s check the data type of each variable. The time column is in character format. When opening the data in Excel, it is considered text. I wish to create a time series graph, but this cannot be accomplished when the variables are in text format. Therefore, we need to convert the … Read more
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 … Read more
□ Creating an Azure SQL Database: A step-by-step guide In my previous post, I introduced how to set up Azure SQL Database. Today, let’s practice some SQL coding! 1) to create data table I just created two data tables YieldData, and BiomassData. 2) to summarize data I will summarize the data tables by calculating the … Read more
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 … Read more
TimeBlocks Project Track, visualize, empower: crafting purposeful, balanced lives through time blocks.
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, … Read more
DALL·E3, developed by OpenAI, is an advanced AI model capable of generating images from textual descriptions. It can create images based on a wide variety of prompts, ranging from straightforward descriptions to more imaginative or abstract concepts. ChatGPT – DALL·E (openai.com) I requested images from DALL·E depicting Agrivoltaics farming, and these are the results.
Quantifying pre- and post-anthesis heat waves on grain number and grain weight of contrasting wheat cultivars The study titled “Quantifying pre- and post-anthesis heat waves on grain number and grain weight of contrasting wheat cultivars” investigates the impact of heat stress on wheat productivity. As temperatures rise, wheat faces challenges in maintaining grain yield. Heat … Read more
In my previous post, I demonstrated how to create a data table using Python. If you’re interested, please refer to the post below. ■ How to create a data table in Python? I’ll summarize this data by mean and standard error. full code: https://github.com/agronomy4future/python_code/blob/main/How_to_summarize_data_using_Python.ipynb
When creating a data table in R, it seems simple. How about using Python? © 2022 – 2023 https://agronomy4future.com
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If you update to ChatGPT Plus version, we can access Data Analyst, and “you can create graphs by texting instead of coding“. Let’s upload a dataset into Data Analyst. This dataset contains data about Fe uptake on wheat grains. If you run the following R code, you can download the data from my GitHub. After … Read more
Today, I’ll introduce how to filter variables after uploading data to SAS Studio. First, let’s upload data to SAS Studio. I’ll summarize data based on Treatment_modified. I want to summarize for each unique ID. So, I’ll add numbers from 1 up to the end. and I’ll summarize data again. Then, I’ll download this data to … Read more
In 2024, one of my goals is to learn machine learning and publish a crop physiology paper in an academic journal using machine learning. While taking online or offline courses of machine learning, I discovered Kaggle, a popular platform for data science and machine learning competitions, datasets, and tutorials. Kaggle provides excellent datasets for practicing … Read more
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 … Read more