Data Science with Python - Advanced Concepts
In this Hands-on lab, you will be challenged on your knowledge of Python for Data Science, particularly on three important aspects: Programming, Data Management, and Visualization. Here, we will mainly focus on three Python libraries: Pandas, Bokeh, and Matplotlib. Those are indeed the fundamental libraries to perform data analysis, management, and visualization using Python.
Before starting this lab, you are strongly encouraged to take the following courses:
- Data Wrangling with Pandas.
- Data Visualisation with Python using Matplotlib.
- Interactive Data Visualization with Python using Bokeh.
- Python Programming.
Your data manipulation and visualization skills will be challenged, and by the end of this lab, you should have a deep understanding of how Python is used in Data Science.
- Senior Data Scientists
- Python Backend Developers
- Manipulate data using Pandas
- Build a structured application using Python
- Create an enriched plot using Matplotlib
- Map a Python Dictionary into a Pandas DataFrame's column
- Join two (or more) DataFrames
- Multiple aggregation using Pandas
Andrea is a Data Scientist at Cloud Academy. He is passionate about statistical modeling and machine learning algorithms, especially for solving business tasks.
He holds a PhD in Statistics, and he has published in several peer-reviewed academic journals. He is also the author of the book Applied Machine Learning with Python.