Starting an analysis of the global arms trade in the last 60 years between state and non-state actors! > 25k transactions between > 250 actors, in @neo4j after @Python_Pandas#data cleaning. Not that informative visual but the scale and density are amazing to me. #dataisbeautiful
I love @code ! They have excellent remote computing support. Its really fast and It just works! Plus the extensions make things so much more customizable =] Highly recommend it!
So I need to take some time to write some code for simulations.
It's still WFH here these days so, I'm logging into my lab machine remotely. I do most of my coding in #Python3 with @numpy_team & @Python_Pandas. Code in #vim, visualise in @ProjectJupyter
Why do you guys use?
No habla bien de Pandas.
En realidad Pandas está muy bueno, pero es muy sofisticado. Agrega una capa de abstracción bien hecha pero pesada a Python. Necesaria en algunas ocasiones, pero en mi experiencia tiene que ser muy justificado su uso.
Proposition for the next pandas library update:
df.contains('substring')
should become a shortcut for:
df[df.columns[df.columns.str.contains(‘substring’)]]
If there exists a short alternative, I am all ears :)
@Python_Pandas#pandas#coding#DataScience#MachineLearning
Happy you like it, thanks! It was made entirely through #opensource software. Trajectories calculated through #AIMD were rendered through @blender with a bit of @Python_Pandas scripting to differentiate the three species. Then side and top views were merged through @shotcutapp
@Python_Pandas - For reading and modifying data in any file format .
For Plotting results: @matplotlib .
If you have good knowledge of python only use function of pandas nto reading file and converting to list or
dictionary.
Me: 14 hour a day
30 days for learning this.