This solution Won Contest

TCS-Talent-Ocean Round 2 Submission

Problem Statement: Find suitable candidates for project based on required skills and candidates skills

Approach to solve problem:
My approach to solve given problem includes following steps:

1. Get data
2. Data extraction
3. Data cleansing
4. Data manipulation
5. Calculation of matching factor
6. Get suitable candidates on the basis of matching factor

Algorithm:

1. Start
2. Create two dataframes for candidate and project details.
3. Extract required columns ( project id, location, required skills ) from main dataframe of project.
4. Data extraction: Extract required columns ( candidate id, location, skills ) from main dataframe of candidate.
5. Data manipulation: Convert both dataframes data into lower case for simplicity of comparison.
6. Data cleansing: for both dataframes replace multiples by one. Example : java programming, java language, core java, programming in java, java se can be replaced by simple one-word java.
7. Calculate matching factor of every candidate for every project Matching factor = 90% of (matching skills) + 10% of (location match)
8. Get top 5 candidates having high matching factor for the project.
9. Final dataframe (project id, location, required skills, top 5 suitable candidates, matching factor for top 5 candidates.)

Flowchart:

Data visualization:

1. Matching factor vs projects
   This graph shows project against matching factor
   
   

2. Matching factors range
   In below graph, orange green shows number of projects which has matching factor between 41 – 60% and so on.
   
   

Requirements:
Programming language: Python 3
Python library: Pandas, matplotlib, numpy
Tool used: Google Colab

Time complexity :
Time complexity to reach solution using above mentioned approach is:
T(n) = O(Log( n²))