Python Analytics Libraries: Pandas, Matplotlib & More

Learning Python? Chris Bruehl says these are the analytics libraries to know... 1. Pandas - THE analytics library in Python, which will allow you to manipulate, aggregate, pivot, and analyze your data with an arsenal of analytics tools 2. Matplotlib & Seaborn - plot your data with visually appealing and highly customizable charts and graphs 3. Plotly & Dash - create beautiful charts and interactive dashboards 4. SQLAlchemy - access a database directly, and write SQL queries to gather your data for further analysis 5. openpyxl - read and write data to and from Excel Workbooks - write Excel formulas, create Excel charts, and much more, without ever needing to open Excel directly 6. Requests & Scrapy - great libraries for gathering data from the web 7. scikit-learn - build powerful predictive models with one of the most widely used machine learning tools out there 8. TensorFlow & Pytorch - want to try your hand at deep learning? These two libraries are the industry standards for next gen machine learning 9. NLTK - have a word problem to solve? Use NLTK to get your text data to talk Knowing these libraries will allow you to tackle many of the problems data people need to solve. But of course, Python has LOTS of additional libraries. Have a favorite library that we didn't mention? Let us know below 👇 Want more great Python content like this? Follow Chris Bruehl, our Lead Python Instructor! #learn #python #data #analysis #datascience