1. Python for Quant Finance
Shivgan Joshi

2. Contents Data Handling Panda, Numpy and other libraries
Figures and chartings
Maths – Regression and Clustering
Common typos in syntax
Symbolic Computation
Connecting to SQL / MongoDB

3. When things don’t work 
Changing path from window settings
Reinstalling python
Using anaconda
Checking Ipython
Reinstalling package
Sublime + Python + anaconda

4. Panda Play Playing with Arrays Selecting Rows / Columns
Applying a function on each element of the column
Renaming or Deleting columns
Applying a function to the entire – element by element operation

5. Panda Commands Match and make data frames smaller
Group_by in data frames
Left join in Panda data frames
Saving Excel

6. Functions in Python Something to return Indentation
What to do with the starting
It only compares number?

7. Classes in Python Displaying a standard message about the things
Including everything in other classes
All utility functions in one place
When to use classes
Classes inheritance
Constructor Destructor

8. Library: Sympy
from sympy import Symbol
Symbolic Computation

9. Numpy NP
Generating random numbers

10. Dictionary Many times Data comes in the format of dictionary
Element by element play with dictionary
Keys and values

11. GIU in Python
GIU Pythons
Button
Backend
Exe generator

12. Regression and Cluster Analysis

13. Trouble maker syntax [][] – double brackets Indentataion
Panda count if the string is present

14. Fixed Income using Python
Term structure
Bond Pricing
Interest rate models
Calibration of interest rate models

15. Matplotlib library
Graphs and charts for the histograms