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.
In Python, it is possible to print numbers in scientific notation using base functions and NumPy. Specifically, using three different methods, you will learn how to use Python to print large or small (i.e., floating point) numbers in scientific notation. In the final two sections, before concluding this post, you will also learn how to […]
Python Scientific Notation & How to Suppress it in Pandas & NumPy Read More »
In this Python data visualization tutorial, we will learn how to create a violin plot in Python with Matplotlib and Seaborn. We can carry out several techniques for visualizing data (see the post 9 Data Visualization Techniques You Should Learn in Python for some examples). Violin plots combine both the box plot and the histogram.
How to Make a Violin plot in Python using Matplotlib and Seaborn Read More »
In this Python data analysis tutorial, you will learn how to perform a paired sample t-test in Python. First, you will learn about this type of t-test (e.g. when to use it, the assumptions of the test). Second, you will learn how to check whether your data follow the assumptions and what you can do
How to use Python to Perform a Paired Sample T-test Read More »
In this tutorial, related to data analysis in Python, you will learn how to deal with your data when it is not following the normal distribution. One way to deal with non-normal data is to transform your data. In this post, you will learn how to carry out Box-Cox, square root, and log transformation in
How to use Square Root, log, & Box-Cox Transformation in Python Read More »
In this Python tutorial, you will learn how to 1) perform Bartlett’s Test, and 2) Levene’s Test. Both are tests that are testing the assumption of equal variances. Equality of variances (also known as homogeneity of variance, and homoscedasticity) in population samples is assumed in commonly used comparison of means tests, such as Student’s t-test
Levene’s & Bartlett’s Test of Equality (Homogeneity) of Variance in Python Read More »
In this Pandas tutorial, you will learn how to count occurrences in column using the value_counts() method.
Pandas Count Occurrences in Column – i.e. Unique Values Read More »
In this short NumPy tutorial, you will learn how to convert a float array to an integer array in Python.
How to Convert a Float Array to an Integer Array in Python with NumPy Read More »
In this post, you will learn how to carry out the non-parametric test known as Mann-Whitney U test with Python. Specifically, you will learn how to carry out this test with SciPy and Pingouin.
How to Perform Mann-Whitney U Test in Python with Scipy and Pingouin Read More »
In this post, you will learn how to install specific packages with pip.
Pip Install Specific Version of a Python Package: 2 Steps Read More »
In Pandas, you can convert a column (string/object or integer type) to datetime using the to_datetime() and astype() methods. Furthermore, you can also specify the data type (e.g., datetime) when reading your data from an external source, such as CSV or Excel. In this Pandas tutorial, we will learn how to convert a column, containing
Pandas Convert Column to datetime – object/string, integer, CSV & Excel Read More »
