If you search with the term “ice cream float” instead of “spider”, there are plenty of recipes!

E.g.

• https://www.confessionsofachocoholic.com/recipes/champagne-ice-cream-floats
• https://vinepair.com/wine-blog/4-wine-cream-floats/
• https://www.lemonsforlulu.com/rose-sparkling-wine-float/

I’m not willing to try it since I don’t like wine, but I encourage you to give it a go and report back!

I did it when I was in my 20s a few times and I hated it. Tasted suspiciously like vomit.

However I did not give up there. The grown up spider/icecream soda involves tonic water, french vanilla icecream, crushed strawberries and a dash of gin, imo.

One thing I learnt in making the jump to Linux as a daily driver is to keep all my documents and files on a separate partition. There are so many distros that I wanted to test a few, and I got sick of copying 600GB around all the time. Much easier to keep them separated on a partition away from the boot partition.

Be careful what you wish for. Mine was when half my hometown started telling my mother they saw me stuffing my face with chips in the background of a One News report when I was meant to be in class.

Everyone might get their 15 minutes of fame, but it may not be for a good reason. Try not to be a murderer or an Elon Musk.

You might just be the person that the news videos falling over in the wind to demonstrate how windy it is today. Still counts.

Fudge, I forgot to complete it! I got halfway through and started having an existential crisis about my identity ha ha and thought I’ll come back later and fix this.

I’m curious, can we have something like automation in LibreOffice? I mean like in VBA, where I can pull data and export excel charts.

Just roll with the LibreCalc charts.

It’s the data that’s important, perfectly rendered gradients on histogram bars is less important.

You could do this with python and a couple of libraries. This is just an example, but you could import the data from a DB or use a CSV file.

import matplotlib.pyplot as plt
import numpy as np

# Pie chart data
labels = ['Category A', 'Category B', 'Category C', 'Category D', 'Category E']
sizes = [30, 25, 20, 15, 10]
colors = ['#ff9999','#66b3ff','#99ff99','#ffcc99','#c2c2f0']

# Pie chart
plt.figure(figsize=(8, 8))
plt.pie(sizes, labels=labels, colors=colors, autopct='%1.1f%%', startangle=140)
plt.title('Sample Pie Chart')
plt.axis('equal') # Equal aspect ratio ensures that pie is drawn as a circle.
plt.show()

# Histogram data
data = np.random.normal(0, 1, 1000) # Generate 1000 random data points with a normal distribution

# Histogram
plt.figure(figsize=(10, 6))
plt.hist(data, bins=30, color='#66b3ff', edgecolor='black')
plt.title('Sample Histogram')
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.show()