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Best Practices for Handling Duplicate Elements in Python Lists

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Here are three awesome ways that you can use to remove duplicates in a list. These are helpful in resolving your data analytics solutions.  01. Using a Set Convert the list into a set , which automatically removes duplicates due to its unique element nature, and then convert the set back to a list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = list(set(original_list)) 02. Using a Loop Iterate through the original list and append elements to a new list only if they haven't been added before. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] for item in original_list:     if item not in unique_list:         unique_list.append(item) 03. Using List Comprehension Create a new list using a list comprehension that includes only the elements not already present in the new list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] [unique_list.append(item) for item in original_list if item not in unique_list] All three methods will result in uni
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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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