Integration in Python
Making Your Academic Life Much Easier with Python — #PySeries#Episode 21
Hi, in this episode we gonna solve some integration using Python.
SymPy is a Python library for symbolic mathematics. It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python.
This is my first attempt at working integrals in python, since I have some difficulties in algebra :)
Fundamental Calculus Theorem:
Now, from the calculation, we know that the area defined is given by:
To start off on our journey, open your Colab Notebook.
Let’s get it on!
First, import these libraries:
%matplotlib inlineimport matplotlib.pyplot as pltimport numpy as npimport sympy as sy
Now please answer these 5 question (just 5:)
01#PyEx — Python — Definite Integral:
Calculate the integral of the function bellow and make the graph:
02#PyEx — Python — Python — Definite Integral:
Calculate the integral of the function bellow and make the graph:
03#PyEx — Python— Definite Integral:
Calculate the integral of the function bellow and make the graph:
04#PyEx — Python — Python — Definite Integral:
Now the hard part:Calculate the definite integral of the function, first by hand, them, using Python lambda function, and solve this:
05#PyEx — Python — Python — Definite Integral:
The hard part, again:
Given these 2 fuctions f(x)& g(x):
Calculate the area between the two functions and present a graph;)
From now on it’s up to you!
If you are feeling rusty, see the answer in the notebook below, prepared just for your enjoyment!
If you find this post helpful, please consider to subscribe to the Jungletronics for more posts like this, and much, much more…
Until next time!
I wish you excellent day!
Be safe!
Cheers!
Colab Notebook Anwers link:)
Google Drive link:)
Google Colab Notebooks are here:
Credits & References
Integrating functions in python by kitchingroup.cheme.cmu.edu
Taking Derivatives in Python by Dario Radečić
Calculate Derivative Functions in Python by Erik W
Higher Order Partial Derivatives
Integration by calc-again.readthedocs.io
Cálculo com Python by phkonzen.github.io
Fundamental theorem of calculus by wikipedia.org
Introduction — What is Symbolic Computation? by docs.sympy.org
Sympy : Symbolic Mathematics in Python by scipy-lectures.org
Posts Related:
00Episode#PySeries — Python — Jupiter Notebook Quick Start with VSCode — How to Set your Win10 Environment to use Jupiter Notebook
01Episode#PySeries — Python — Python 4 Engineers — Exercises! An overview of the Opportunities Offered by Python in Engineering!
02Episode#PySeries — Python — Geogebra Plus Linear Programming- We’ll Create a Geogebra program to help us with our linear programming
03Episode#PySeries — Python — Python 4 Engineers — More Exercises! — Another Round to Make Sure that Python is Really Amazing!
04Episode#PySeries — Python — Linear Regressions — The Basics — How to Understand Linear Regression Once and For All!
05Episode#PySeries — Python — NumPy Init & Python Review — A Crash Python Review & Initialization at NumPy lib.
06Episode#PySeries — Python — NumPy Arrays & Jupyter Notebook — Arithmetic Operations, Indexing & Slicing, and Conditional Selection w/ np arrays.
07Episode#PySeries — Python — Pandas — Intro & Series — What it is? How to use it?
08Episode#PySeries — Python — Pandas DataFrames — The primary Pandas data structure! It is a dict-like container for Series objects
09Episode#PySeries — Python — Python 4 Engineers — Even More Exercises! — More Practicing Coding Questions in Python!
10Episode#PySeries — Python — Pandas — Hierarchical Index & Cross-section — Open your Colab notebook and here are the follow-up exercises!
11Episode#PySeries — Python — Pandas — Missing Data — Let’s Continue the Python Exercises — Filling & Dropping Missing Data
12Episode#PySeries — Python — Pandas — Group By — Grouping large amounts of data and compute operations on these groups
13Episode#PySeries — Python — Pandas — Merging, Joining & Concatenations — Facilities For Easily Combining Together Series or DataFrame
14Episode#PySeries — Python — Pandas — Pandas Dataframe Examples: Column Operations
15Episode#PySeries — Python — Python 4 Engineers — Keeping It In The Short-Term Memory — Test Yourself! Coding in Python, Again!
16Episode#PySeries — NumPy — NumPy Review, Again;) — Python Review Free Exercises
17Episode#PySeries — Generators in Python — Python Review Free Hints
18Episode#PySeries — Pandas Review…Again;) — Python Review Free Exercise
19Episode#PySeries — MatlibPlot & Seaborn Python Libs — Reviewing theses Plotting & Statistics Packs
20Episode#PySeries — Seaborn Python Review — Reviewing theses Plotting & Statistics Packs
21Episode#PySeries —Integration in Python — Making Your Academic Life Much Easier with Python (this one)