In this folder you will find Jupyter Notebooks containing code examples for many of my blogposts (https://www.marsja.se). There are also notebooks containing the code for some of my Videos on my YouTube Channel. The main theme of the blog posts, right now, is data visualization, manipulation, and analysis using Python. For instance, you will find Pandas tutorials, Seaborn tutorials, and Statsmodels tutorials (e.g., Python ANOVA).
Here are different Notebooks containing the code examples for some of the Pandas Tutorials:
Note books for different Data Visualization Tutorials:
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Kernel Estimation, Cumulative Distribution Function, Delta Plot, & Conditional Accuracy Function: Different data visualization techniques for response time data
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Python Data Visualization Tutorial: How to Create a Scatter Plot
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How to Make Scatter Plots using Python - Here we work with the following Seaborn methods: scatterplot, regplot, lmpot, and pairplot. We learn how to make scatter plots with regression lines, change the color and markers of Seaborn plots, rotate the ticks labels, and much more.
For some data analysis techniques we may want to use R. This because it may not yet be implemented in Python. Here are some Jupyter Notebooks for one Python package called Rpy2:
In this section we find the code examples, in form of Jupyter Notebooks, for the Python data analysis tutorials;
Here, there are some Jupyter Notebooks for carrying out summary statistics using Python, Pandas, Scipy, and other useful Python packages
Here we have Python ANOVA Notebooks. There is also one Notebook for carrying out ANOVA using R.