All the analysis and visualizations do not require any special installation. All the libraries are available in Anaconda distribution (using Python 3).
This is my first major exercise for the Data Science Nanodegree Program in Udacity (Write a Blog Post). I chose this topic because it is very relevant to someone like me who wants succeed in the Data Science field. Here are the key questions I wanted to answer:
- Are there major differences in salary among the different data science roles?
- What are the essential technical skills to do well in data science?
- Does educational background play a huge part?
- How much does continuous learning on online platforms help? To answer my questions I used the 2019 Kaggle ML and DS Survey.
The main analysis and data exploration can be found in the Jupyter Notebook (Winning in the Data Science Field.ipynb).
The raw data for the survey is also included (multiple_choice_responses.csv).
For a quick glance at all the questions included in the survey, this file is useful: questions_only.csv
The whole article can be found through a Medium post publicly available through this link
I'm grateful to Udacity for enabling me to write my first blog post. Thanks also to Kaggle for being an awesome source of free datasets. Lastly, big thanks to my fiancé for proofreading my article and providing valuable inputs.