In this category you will find posts that are related to programming and should be interesting for psychologists, cognitive scientists, and neuroscientists. Well, almost every researcher would probably find some of the information useful at some time!
Every research psychologist, cognitive scientist, and neuroscientist, should know how to program.. Knowing how to program and write scripts will make many of a researchers everyday tasks much easier. For instance, instead of going through line after line of raw data you can write a Python script that runs through each cell in each column. Furthermore, you get the possibility to use more advanced, and cutting edge, statistical techniques by using R statistical programming environment.
Another example might be to create experiments using PsychoPy (either by coding using Python or using the drag-and-drop interface) and the cheap and open-source Arduino microcontroller. Also, coding is fun and relaxing!
Descriptive statistics in Python are easy to calculate with Pandas. Whether you want a quick overview of your data or need summary statistics before fitting a statistical model, Pandas includes built-in functions for the most common descriptive measures. In this tutorial, you’ll learn how to calculate descriptive statistics for a Pandas DataFrame and interpret the […]
Descriptive Statistics in Python using Pandas Read More »
Learn how to reverse pandas dataframe by rows or columns.
Six Ways to Reverse Pandas dataframe Read More »
Spyder is the best Python IDE I have used for data analysis, scientific computing, and general Python development. I’ve been using it for years, and despite trying alternatives such as PyCharm, VS Code, and Rodeo, I keep coming back to Spyder. In this post, I’ll explain why it’s my preferred Python IDE, walk through the features I
Why Spyder is the Best Python IDE for Science Read More »
This post aims to show why you, as a psychology student or researcher (or any other kind of researcher or student) should learn to program. The post is structured as follows. First, I start by discussing why you should learn to program and then give some examples of when programming skills are helpful. I continue
Every Psychologist Should Learn Programming Read More »
Good resources for learning R as a Psychologist are hard to find. By that, I mean that there are so many great sites and blogs to learn R. Thus, it may be hard to find learning resources that target Psychology researchers. Outline The structure of this post is as follows. First, we start by getting
R Resources for Psychologists Read More »
I recently wrote a post on the RStudio like Python IDE Rodeo (RStudio-like Python IDEs – Rodeo and Spyder). In that post, I installed and tested Rodeo 0.44. However, Rodeo 1.0 was released in October. Rodeo 1.0 cannot be installed using Pip. Therefore, I wrote a bash script for downloading and unzipping Rodeo. Note, the
Installing Rodeo IDE on Linux Read More »
In this post I will discuss two Python Integrated Development Environments (IDE); Rodeo and Spyder. Both Python IDEs might be useful for researchers used to work with R and RStudio (a very good and popular IDE for R) because they offer similar functionalities and graphical interfaces as RStudio. That is, Rodeo and Spyder can both
RStudio-like Python IDEs – Rodeo and Spyder Read More »
I recently asked which programming language I should learn next year (i.e., 2016). In this post I will evaluate the alternatives that I have by asking the question in different places around the internet. The post will end with the choice I made and how to install the language To summarize my earlier post, I
What programming language should I learn – 2 Read More »
In this tutorial, you will learn how to use the PsychoPy function TrialHandler to create trials and correct responses to your targets in these trials. PsychoPy is an application for creating experiments for Psychology experiments. The application is written in Python, an easy programming language to learn. You can learn more about PsychoPy in my
TrialHandler – a PsychoPy tutorial Read More »
This tutorial covers the integration between R and Python using the rpy2 package. Discover how to bridge the gap between these two languages, enabling you to make use of both languages’ strengths for enhanced data analysis and visualization. This rpy2 tutorial guides you through its installation, configuration, and practical usage. Outline In this tutorial, we
R from Python – an rpy2 tutorial Read More »