This project was done to understand the Python visualization package, Plotly.
Note this is a modified project from kaggle
Github performs a static render notebooks and it doesn't include the embedded HTML/JavaScript that makes up a plotly graph. Because of that, I have paste this project notebook in a Notebook Viewer for rich view of the project.
Here a multiple choice response from Kaggle ML and Data Science Survey data was analyse for insight, the insight are presented through plotly interactive plots such as bar plot, scatterplot, pie plot etc,.
Matplotlib
Pandas
Seaborn
Numpy
- Male gender dominate the tech world by 81.9% while 16.7% are Female.
- Online platforms are the most used medium for training.
- When it comes to starting a course in Data Science, Coursera dominates followed by Udacity. While for learning platforms, Kaggle dominates followed by online courses.
- Basic laptop (Macbook) is enough to follow data science trends.
- United States is the country with the highst median salaries ($108k) followed by Switzerland($104.3k).
- Median wage of male is higher than median wage of female.
- It seems that women are underpaid after 35yrs and they are out of labor force especially after their 50s in non-US countries.
- The rate of software engineers is higher in men than it is in women as in 2018 survey. Male - 23%, Female - 12.7%.
- The rate of data analyst is higher in women than it is in men as in 2018 survey. Female - 21.2%, Male - 13.3%.
- Data scientists and machine learning engineers are not only highly paid, they also have higher job satisfaction.
- Although experiences of most respondents in coding are lower than 5 years, employment rate is quite high (65.3%).
Check out the notebook for more insights.