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self-development's Introduction

Self-Development and Personal Branding

GitHub issues GitHub forks GitHub stars GitHub license

A Project Repository to Show Case my Skills

Table of Contents

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Quick Start

GitHub is an excellent place to showcase skills, codes and enthusiasm for open source. The repository is dedicated for my learning purpose, but you are welcome to open any PR or raise an issue. Check the contribution guidelines and code of conduct for more details. The repository is divided into sections, or by programming language that I generally use.

This repository falls under GPL 3.0 license, and the CODEOWNERS file is featured. Do update the file if you are contributing to this repository, and your name/ID will be highlighted. If you want to use any part of the code for academic purpose, do cite this repository.

Getting Started

🗂️ Contents are arranged by platforms, and language. I mainly work on 🔣 python and related tools for ✳️ Data Science & Analyst Application Development (for more details check 🔗 profile). List of known/required modifications include:

  • ⚠️ Directory structure is not uniformed/completed.
  • 🚫 Some links may return 404 as some repositories are now not available.
  • ⛔ Code commit history is cluttered, as some repositories are now merged into self-development to keep development/learning work together.

Settings & Configurations

🤓 Being a tech-enthusiast 💻, I spent much time and efforts in polishing ⚙️ my own working environment to perfection! Well, with experience 🧑 and maturity many settings and configurations 🛠️ are revamped and modified. I have kept a dedicated 🧲 GitLab Repository 🔗 that helps me track the environment and a quick-setup if things go south! However, with the below 👇 mentioned links, you can directly look for a particular settings (if you wish to do so). Do put a 🌟 if you find my projects useful!

IDEs Python Libraries

🔀 Navigation & Quick-Links

⚠️ monorepo ⚠️ 
  🛡️ monorepo:
      that is multiple files, projects are accumulated in this repository.
  🛠️ quick-links:
      for most required sections are provided, do raise a PR if a link is not working.
  ✂️ merged-repo:
      previously, different repositories were used, however the idea is dropped, and all codes are merged.
  📅 calendar:
      a calendar sections is being created, which will showcase coding platform solutions by date.

The repository is divided into the following below mentioned subdirectory which are available with their own set of README.md files, and other optional files (like template/boilerplate codes). Quickly navigate to the sections mentioned below.

  • 📊 Courses for Skills Development : with the advent of MOOCs many courses are available, and this section showcases study materials and code files used in the course. The courses are again subdivided by platforms, like

self-development's People

Contributors

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Stargazers

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Watchers

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Forkers

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self-development's Issues

[Bug]: [Enhancement]: Structuring Project

Contact Details

No response

What happened?

The project and subdirectories need a significant restructuring, as the codes, files, and information are haphazardly available. The following suggestions are to be addressed:

  • create directories separated by topics,
  • put all template/boilerplate files separated by topics, and
  • reduce folder/directory name (longpath) issue and inconsistency.

Python Version

3.9.12 (default)

What type of operating system are you using?

Windows 10, Linux (debian/ubuntu/mint/etc.)

Relevant log output

No response

Code of Conduct

  • I agree to follow this project's Code of Conduct

[Bug]: Filling NaN Values

Contact Details

No response

What happened?

Null values are not automatically populated using df.fillna({}, inplace = True) command. [commit: 949cc1d] but works when using df = df.fillna({}) command.

Python Version

3.9.12 (default)

What type of operating system are you using?

Windows 10

Relevant log output

No response

Code of Conduct

  • I agree to follow this project's Code of Conduct

[Enhancement]:

Contact Details

No response

Explain the Feature/Enhancement?

The LeetCode directory progress bar can be automated using a python script:

Code of Conduct

  • I agree to follow this project's Code of Conduct

[Bug]: Wrong Implementation of Finding

Contact Details

No response

What happened?

The method .find() reports all elements to be present in the Singly Linked Lists even when not present.
image

  • Check the .find() method with a mock-up code.
  • Check .next() and .head() method implementation.

Python Version

3.9.12 (default)

What type of operating system are you using?

Windows 10

Relevant log output

llist = SinglyLinkedList()
llist.append(10) # add a new element

# find the new element in the linked list
llist.find("not present") # returns True

Code of Conduct

  • I agree to follow this project's Code of Conduct

[Enhancement]: Require Repository Description & Documentations

Contact Details

No response

Explain the Feature/Enhancement?

As under community guidelines, the description needs to be added to the repository.

Related Tasks List

A list of additional tasks that are tracked and needs to be ✅ completed before closing this issue are mentioned below. (NOTE: these tasks may not be in a specific order, and is added when required/raised).

Code of Conduct

  • I agree to follow this project's Code of Conduct

[Enhancement]: Creating a Reference Table for LeetCode Daily Challenges

Contact Details

No response

Explain the Feature/Enhancement?

LeetCode provides daily challenges. Use a section to showcase all the solved problems featured in this challenge. In addition, also add comments and keywords (i.e. SEO) to increase view traffics.

  • Create a <details> ... </details> Tagging Template
  • Create a year followed by a month selection to keep the view at a minimum level.
  • Create a redirect URL schema and provide keywords.
  • #15

Code of Conduct

  • I agree to follow this project's Code of Conduct

Statistical Information is not Displayed on Type Casting

Overview

A type casting function is developed (based on this link) to reduce the memory usage of a dataframe. However, using the function the statistical information is missing when using pd.describe() feature.

Steps to Reproduce

  1. Use the pd.describe() method w/o any modifications, results in:
    image
  2. Now, define/import reduce_mem_usage
  3. Using the same function, the output is changed as:
    image

Expected Behavior

Should be able to use all statistical features.

Actual Behavior

Direct describe function is not working, but using native numpy functions (like np.quantile(trn_data["f_00"], 0.95)) works.

Context

Python Version : 3.9
Operating System : Windows 10 (Version: 21H2, OS Build: 19044.1682)

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