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NumPy is a fundamental library for numerical computing in Python, offering powerful tools for working with large arrays and matrices. It's widely used in various fields such as data science, machine learning, engineering, and scientific research.
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東工大の「Python早見表」が非常に有益。 Pythonの基本構文から始まり、リスト、辞書といったデータ構造の操作方法、例外処理、そしてNumPy、Matplotlibといった主要ライブラリの基本までを網羅。単なるチートシートではなく、体系的な知識の整理に役立つ こちら👉 chokkan.github.io/python/index.h…
Below are few popular Python libraries explained in brief : - NumPy: fast math & arrays. - Pandas: data analysis. - Matplotlib/Seaborn: charts. - SciPy: scientific computing. - Scikit-learn: machine learning. - TensorFlow/Keras/PyTorch: deep learning. - Flask/Django: web apps.
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『Pythonではじめるオープンデータ分析』ご恵贈いただきました。 この本いいですね。オープンデータがどんなもので、どうやって分析するのか、分析した結果をどう活用するか、順序立てて分かりやすく書いてありますamzn.to/4qMKVCH
Why python is insane for algorithmic trading: 1. Visualization: Plotly ($0) 2. Data analysis: Pandas ($0) 3. Market Data: OpenBB ($0) 4. Technical indicators: TA-lib ($0) 5. Machine Learning: Scikit Learn ($0) Total cost: $0
I imported numpy as "np" NumPy makes array operations efficient and powerful. 💪 #PythonArrays #Meditechy 3/4: Array Operations 🔄 Basic Operations: As seen in NB Indexing: Access elements using indices. Slicing: Extract subsets easily. Shape: Check the array's dimensions
Learning python is a continuous process🔁 You have to keep revising concepts to get strong hands on them.💪🐍 Here are the basics of python's 'functions' and 'data types' cheat sheets to archive just that🔽👍
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i honestly had a lot of fun futzing with numpy arrays (once i understood how to do it without just using the solving function)
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"it's Python, you do anything and it allocates" How true is this? I modified CPython to print when it allocates an integer object Then added numbers in a for-loop 100k times My terminal got spammed with 101006 allocations Why? Let's explore the internals of CPython:
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I imported numpy as "np" NumPy makes array operations efficient and powerful. 💪 #PythonArrays #Meditechy 3/4: Array Operations 🔄 Basic Operations: As seen in NB Indexing: Access elements using indices. Slicing: Extract subsets easily. Shape: Check the array's dimensions
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I imported numpy as "np" NumPy makes array operations efficient and powerful. 💪 #PythonArrays #Meditechy 3/4: Array Operations 🔄 Basic Operations: As seen in NB Indexing: Access elements using indices. Slicing: Extract subsets easily. Shape: Check the array's dimensions
Average of the highs/0 inputs in a two dimensional array #pythonarrays #pythonprogramming #pythonarray
Python Arrays: A Comprehensive Guide for Beginners Are you new to programming and curious about working with arrays in Python? websolutioncode.com/python-arrays-… #websolutioncode.com #pythonarrays
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