In the posts in this category you will find Python scripts. Python is said to be one of the easiest programming language to learn. Learning one language will also make it easier to learn another, much more advanced, one. As a Bachelor student in the cognitive science programme I got to take Python courses. However, it was not before I started my Ph.D years that I realized how much use I had because I knew some programming.
For a psychology researcher Python might be ideal since it is relatively easy to learn and there is a huge Python community to get help from. How to build experiments using free and open-source tools such as PsychoPy, OpenSesame, Expyriment, and PyEPL is, for instance, something you could find in this category.
This Pandas tutorial will teach us how to work with Pandas dataframes. We will learn how to read and write Excel (i.e., xlsx) and CSV files using Pandas. Moreover, we will also learn how to add a column to Pandas dataframe object, and how to remove a column. Finally, we will learn how to subset […]
A Basic Pandas Dataframe Tutorial for Beginners Read More »
In this short post, I will show you a quick fix for the error “unsupported operand type(s) for +: ‘float’ and ‘NoneType’” with Pyvttbl. In earlier posts, I have shown how to carry out ANOVA using Pyvttbl (among other packages. See posts 1, 2, 3, and 4 for ANOVA using pyvttbl). However, Pyvttbl is not
Step-by-step guide for solving the Pyvttbl Float and NoneType error Read More »
In this post, PyCharm vs Spyder will be compared. If you have followed my blog you may have noticed that a lot of focus has been put on how to learn programming (particularly in Python). I have also written about Integrated Development Environments (IDEs). I think that an IDE may, in fact, be very useful
PyCharm vs Spyder: a quick comparison of two Python IDEs Read More »
In this short post, we are going to revisit the topic of how to carry out descriptive statistics in Python. In the previous post, I used Pandas (but also SciPy and Numpy, see Descriptive Statistics Using Python) but now we will only use Numpy. The descriptive statistics we will calculate are the central tendency (in
How to do Descriptive Statistics in Python using Numpy Read More »
One of the great things with programming is that you can automate things that is boring. For instance, as a student I often got schedules in the form of Word documents. I prefer to have all my activities in a digital calendar and used to manually enter every class, seminar, and so on from a
How to use Python to create an iCalendar file from a Word table Read More »
In this video you learn how to create a Flanker task using the Python package Expyriment. If you don’t know Expyriment it is an open-source library. You can program your experiments and run on Linux, Windows, and OS-x computers and Android devices. In the tutorial you will get familiar with Expyriment and get to create
Python Video Tutorial: Creating a Flanker Task using Expyriment Read More »
Inspired by my post for the JEPS Bulletin (Python programming in Psychology), where I try to show how Python can be used from collecting to analyzing and visualizing data, I have started to learn more data exploring techniques for Psychology experiments (e.g., response time and accuracy). Here are some methods, using Python, for visualization of
Exploring response time distributions using Python Read More »
Python is gaining popularity in many fields of science. This means that there also are many applications and libraries specifically for use in Psychological research. For instance, there are Python packages for collecting data, doing basic statistics, and analyzing brain imaging data. In this post, I have collected some useful Python packages for researchers within
Best Python libraries for Psychology researchers Read More »
PsychoPy, as I have previously written about (e.g., Free and Useful Software and PsychoPy tutorial) is really a great Python tool for creating Psychology experiments. You can write Python code by either using “code view” or importing the package in your favorite IDE. Furthermore, you can use the builder mode and just drag and drop different
PsychoPy video tutorials Read More »
Previously I have shown how to analyze data collected using within-subjects designs using rpy2 (i.e., R from within Python) and Pyvttbl. In this post I will extend it into a factorial ANOVA using Python (i.e., Pyvttbl). In fact, we are going to carry out a Two-way ANOVA but the same method will enable you to
Two-way ANOVA for repeated measures using Python Read More »