ipykernel
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ipykernel | cheatsheets | |
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7 | 126 | |
613 | 7,238 | |
2.0% | 0.6% | |
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7 days ago | 7 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | BSD 2-clause "Simplified" License |
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ipykernel
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Why am I so terrible at Python?
The way I work is to use an interactive IPython REPL. It has a lot of features to make interactive development comfortable. I solve a problem incrementally, attempting to get a little piece of code right many times, changing it a little each time to fix bugs. Then I go back and copypaste the lines into a file and tidy it up a little. Then I go back to IPython and solve the next little stage of the problem. Maybe this style of development will be more fitting for you?
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Importing?
IPython
- IPYTHON? What's that??
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Django python manage.py shell up arrow in Git Bash
If you're talking about history in the python shell, you're probably looking for IPython.
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As we smash many of our previous COVID-19 records yet again, here's the recent cases broken down by sex and age groups.
For this kind of thing I mostly use Jupyter and the IPython kernel, with data analysis packages like numpy and pandas and matplotlib for charts.
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Jupyter notebook kernel goes offline
Otherwise you should be able to convert the .ipynb's to .py using the ipython libraries:
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Excel Never Dies
Nice product, I noticed that you are updating the next Jupyter cell; what was your solution to doing that reliably since `set_next_input` is so damn flakey?
I personally grew so frustrated with the state of GUI development in Jupyter that I tried to fix it in such a way that would allow proper message passing between cells and python code (because you can't wait on Comm events).
> https://github.com/ipython/ipykernel/pull/589
But sadly the priorities of big open source projects don't always match your own. So I had to extract that logic into my own kernel.
cheatsheets
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Matplotlib - A Python 2D plotting library.
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How to retrieve and analyze crypto order book data using Python and a cryptocurrency API
Data visualization: utilizing Python's Matplotlib for visualizing order book information.
- Matplotlib
- Ask HN: What plotting tools should I invest in learning?
- Help with an array
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Getting visual studio code to work with imported library
Name: matplotlib Version: 3.7.1 Summary: Python plotting package Home-page: https://matplotlib.org Author: John D. Hunter, Michael Droettboom Author-email: [email protected] License: PSFLocation: /home/huinker/.local/lib/python3.10/site-packages
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PSA: You don't need fancy stuff to do good work.
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses without relying on expensive or proprietary software.
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What else should I complete before applying for a data analyst role?
programming language: basic python, pandas, matplotlib -- you'll probably do these in school, but if not https://cs50.harvard.edu/python/2022/ https://matplotlib.org/
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[OC] Analyzing 15,963 Job Listings to Uncover the Top Skills for Data Analysts (update)
Analysis was done in Jupyter Notebook with Python 3.10, Pandas, Matplotlib, wordcloud and Mercury framework.
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[OC] Data Analyst Skills in need based on 15,963 job listings
Analysis was done in Jupyter Notebook with Python 3.10 kernel, Pandas, Matplotlib, wordcloud and Mercury framework to share notebook as a web application with widgets and code hidden. Gif created in Canva.
What are some alternatives?
ipython-cells - IPython extension for running code blocks in .py files
finplot - Performant and effortless finance plotting for Python
xlwings - xlwings is a Python library that makes it easy to call Python from Excel and vice versa. It works with Excel on Windows and macOS as well as with Google Sheets and Excel on the web.
manim - A community-maintained Python framework for creating mathematical animations.
akernel - Asynchronous Python Jupyter kernel
Fast-F1 - FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry
XlsxWriter - A Python module for creating Excel XLSX files.
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
copypaster - Make web forms copy-pasteable.
Keras - Deep Learning for humans
pyright - Static Type Checker for Python
geogebra - GeoGebra apps (mirror)