Category: Video Tutorials

  • In this post I cover how you can make line charts using the most popular data visualization libraries in Python. These are Pandas .plot method, Matplotlib, Seaborn, plotly-express and Plotnine. A common issue with line charts is overplotting, this happens when you have too many time series in the chart and it’s impossible to make something useful […]

  • Polars allows handling larger than RAM data very easily. In this post I show you with some real world data how you can work with data larger than RAM. First, let’s download the data. Some comments on the data size Now import the libraries. You will have to pip install them on your local environment. […]

  • Why is plotly-express so great? Plotly Express is a great library in Python to do data visualization. It’s quite user friendly and generates interactive plots that can be shared on a notebook or a web application. I think it’s one of the best tools in Python to do Exploratory Data Analysis (EDA) efficiently. When we […]

  • Polars is the fastest DataFrame library available today in Python. It’s a Rust library based on Arrow that has a Python binding. I think Polars will grow massively in a few years and might be able to fully replace Pandas. In the mean time, I think Polars is a perfect fit for “intermediate sized data”. […]

  • I’ve developed a video series where I teach pandas, data analysis and data visualization while working on real world datasets. I think learning to code solving an actual problem is a lot more useful than doing tutorial on a particular tool. Each video covers a different data set, this is the first video of the […]

  • In this video I cover how you can do an exploratory data analysis with Python using Pandas and matplotlib. The idea is to use an online retailer’s e-commerce dataset for the analysis. I think this is a realistic dataset, you can encounter something similar in a data science job. Here is the video with the […]