Part-to-whole Chick-Fil-A Menu Items

#30DayChartChallenge Day 1

Quick primer on the #30DayChartChallenge

The #30DayChartChallenge is a data visualisation community activity that I found out via Linkedin. Every day for the month of April 2024 has a key word prompt (see image above). For each prompt, participants all around the world come up with an original data visualisation to share.

On a whim, I decided to participate in this challenge as I think it’s a great way try something new, better understand my tools and engage with a vibrant community.

Given that this is very much a last-minute decision, I’ll choose to use Python libraries that I am familiar with. polars has already completely replaced pandas for my data manipulation needs and lets-plot is one of my favourite ggplot2 ports in Python.

import polars as pl
from lets_plot import *
LetsPlot.setup_html()

Data Prep

I have heard rumours of Chick-Fil-A looking to open it’s 1st outlet in Singapore (source), so I was inspired to make a visualisation to show the component parts of the major macro-nutrients - Protein, Carbohydrates and Fat for its popular menu items. I figure this should help me decide what I should spend my calories on when it first opens 😋.

It took a bit of a search, but as always TidyTuesdays has a suitable dataset for my needs.

fast_food = (pl
    .read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2018/2018-09-04/fastfood_calories.csv", ignore_errors=True)
    .drop("") # 1st index column is unnamed and not required
)

I planned to create a stacked bar chart so we need to manipulate the dataframe into a tidy-longer form.

chick_fil_a = (fast_food
    .filter(pl.col("restaurant")=="Chick Fil-A")
    .select(["item","total_fat","total_carb","protein"])
    .rename({'total_fat':'Fat', "total_carb":"Carbohydrates", "protein": "Protein"})
    .melt(id_vars="item", variable_name="Nutrients")
)

Nutrients in Chick-fil-a menu items

from lets_plot.mapping import as_discrete

p = (ggplot(chick_fil_a) 
    + geom_bar(
        aes(
            x=as_discrete('item', order_by='value', order=1),
            y="value",fill="Nutrients"),
            stat="identity"
        )
    + coord_flip()
    + labs(
        x= "",
        y = "Nutrients (g)",
        fill= "",
        caption = "Data: TidyTuesday 2018-09-04\nMade by: www.ddanieltan.com"
        )
    + theme_minimal2()
    + scale_fill_manual({'Protein':'#3b3561','Carbohydrates':'#E51636', 'Fat':'#ffc759'})
    + theme(
        legend_position="bottom",
        plot_caption=element_text(size=12, color='grey'),
        plot_margin=[20,50,10,0]
    )
)

p

Things I Learnt

• Lets-plot has a unique method as_discrete() to reorder categorical values, analogous to reorder() in ggplot2 Docs
• It’s really difficult to move my plot title to the left-margin of the plot instead of the axis due to the lack of a parameter like ggplot2’s plot.title.position but it’s coming soon https://github.com/JetBrains/lets-plot/issues/1027