Today, our theme is dinosaurs, which made me think about the Datasaurus Dozen! This wild set of datasets is an extension of the famous Anscombe’s Quartet. Despite having completely different-looking distributions when plotted, every single one of the Datasaurus Dozen datasets has the exact same summary statistics. The Datasaurus Dozen is a great reminder for all us data folks to always look beyond summary statistics like the mean and standard deviation to truly understand what’s going on ...| ddanieltan.com
Today’s theme is a data day, so I went over to browse the interesting datasets available from the Asian Development Bank. I found this dataset that shows the inflation levels for Asian countries from 2019 to 2023, with forecasted numbers for 2024 and 2025. As always, I enjoy analysing data from my home region as it’s less widely covered on a global news. So I thought to focus my chart on Southeast asia, in particular, I wanted to highlight the volatile inflation levels experienced by coun...| ddanieltan.com
Weather Today’s theme is Weather and I while searching for inspiration I came across these beautiful wind rose charts from the Lets-Plot gallery.opted for a simple interpretation of showing the changing monthly temperature distribution over a year. Data is taken from a Python version of Forecasting: Principles and Practise. As always, I like to adapt the examples to my home country of Singapore and data for Singapore’s wind readings was provided by Iowa State University’s Iowa Environme...| ddanieltan.com
Today’s theme is Historical and I opted for a simple interpretation of showing the changing monthly temperature distribution over a year. Data is taken from a Python version going through what I consider the best time series textbook, Forecasting: Principles and Practise. Codeimport polars as plfrom lets_plot import*LetsPlot.setup_html()bikes = pl.read_csv('https://raw.githubusercontent.com/nshahpazov/fpp-in-python/master/data/bikes/day.csv')daily_temp = (bikes .filter(pl.col("yr") ==1) # 2...| ddanieltan.com
Family For today’s #30DayChartChallenge, the theme is “Family.” I must admit, my mind initially wandered to the Kardashians – but let’s move on from that little embarrassment! I’ve been eager to experiment with Sunburst charts during this challenge. In my opinion, these visually striking charts have a unique ability to convey hierarchical relationships in a captivating way. Fortunately for me, the Python Plotly library comes equipped with a pre-built sunburst module, making my tas...| ddanieltan.com
Today’s theme is Waffle and I would like to create a waffle chart. Waffle charts are excellent for displaying and comparing proportions or part-to-whole relationships within a dataset. They are particularly useful when you want to show how a whole is divided among different categories or segments. However, my visualisation library of choice lets-plot does not have a pre-made “geom” or layer specifically for waffle charts. This means that I have got to get a bit more hands-on to make one...| ddanieltan.com
Note This post is my contribution to this year’s #30DayChartChallenge. Check out my Day 1 post to learn more. Makeover Makeover day has arrived, folks! Time to dust off those old relics from the ancient data catacombs and give them a fresh coat of paint. Today’s lucky candidate? A vintage scatter matrix plot taken from an introductory Data Science course I took many years ago. The original scatter matrix plot, seen in the “Before” image, uses both histograms and scatter plots in a 4 p...| ddanieltan.com
Note This post is my contribution to this year’s #30DayChartChallenge. Check out my Day 1 post to learn more. Neo Today’s theme is Neo, and since I couldn’t immediately think of an associated chart, I decided to go with my first instinct: create something related to the groundbreaking 1999 movie, The Matrix. I remember watching The Matrix as a kid and being amazed by its mind-bending plot, cool 90s fashion, and fluid action scenes. Codeimport numpy as npimport polars as plfrom PIL impor...| ddanieltan.com
