Python for Data Analysis

1. Data types and arrays in NumPy

2. Performing Array Calculations in NumPy

3. Array operations in NumPy

4. Indexing and sorting arrays in NumPy

5. Objects in Pandas

6. Operations on data in Pandas

7. Combining datasets in Pandas

8. Vectorized operations on strings in Pandas

9. Working with time series in Pandas

10. Data visualization using Matplotlib library: line graphs and scatter plots

11. Matplotlib library: error visualization, density plots, legend and color settings

12. Matplotlib library: subgraphs, explanatory labels and division settings

13. Building three-dimensional graphs in Matplotlib

14. Displaying geographic data with Basemap

15. Visualization using the Seaborn library

16. Scikit-learn features

17. Overview and features of machine learning libraries in Python