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Step-by-Step Guide to Reading Different Files in Python

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 In the world of data science, automation, and general programming, working with files is unavoidable. Whether you’re dealing with CSV reports, JSON APIs, Excel sheets, or text logs, Python provides rich and easy-to-use libraries for reading different file formats. In this guide, we’ll explore how to read different files in Python , with code examples and best practices. 1. Reading Text Files ( .txt ) Text files are the simplest form of files. Python’s built-in open() function handles them effortlessly. Example: # Open and read a text file with open ( "sample.txt" , "r" ) as file: content = file.read() print (content) Explanation: "r" mode means read . with open() automatically closes the file when done. Best Practice: Always use with to handle files to avoid memory leaks. 2. Reading CSV Files ( .csv ) CSV files are widely used for storing tabular data. Python has a built-in csv module and a powerful pandas library. Using cs...
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Robotics These Skills You Need

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Robotics is a combination of multiple skills. Out of those many skills similar to B.Tech Electronics skill sets. I am sharing for your quick reference the complete skillset.


These skills are very much needed to become a Robotics Developer


PROGRAMMING

  • Mat lab - Familiarity with command-line and external functions using MATLAB library; import/export of data; graphing/plotting functions & data; rudimentary animation
  • Python, C / C++ familiarity
  • ROS- Robot Operating System (ROS) - Optional (Good to know)
  • Program Constructs- Sequencing, Selection, Iteration & Recursion
  • Data Organization- Arrays, Lists, Pointers

COMPUTERS

  • Tools Productivity: SW (MS Office - Excel / Word / PowerPoint / Project)
  • Operating Systems
  • Windows or Apple-OS - use of personal laptop computer Linux or Ubuntu

MATHEMATICS

  • Linear Algebra Inversion, Eigenvalues, Null-Space
  • Linear Differential Eq. Matrix-Algebra & -Manipulation
  • Basic Calculus Derivatives, Gradients, Chain Rule
  • Numerical Integration Basic Computational Implementation, e.g. Runge-Kutta 4
  • Fourier Analysis

Newtonian Physics

  • Newton-Euler Mechanics (Forces, torques, mass/inertia, Equations of motion) System State Degrees of Freedom & Constraints to fully describe a system’s behavior mathematically.

CONTROLS

  • Control Systems, Controls Fundamentals (transfer functions; bode plots; stability-margin; time-response of LTI systems; PID compensators).

Basic Electronics

  • Electronics- Basic experience with practical circuits (elements, interactions, PCBs) Mechanisms- Some design and fabrication experience (Concept -> CAD -> Fabrication) Documentation -Basic skills in document structuring and technical writing.

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