Python-for-data-science

Checkout all my learnings in Python for Data science here. Starting from the essentials of python to various libraries like Numpy, Pandas, Matplotlib, Seaborn, you will get to check all of them out here.

If you are looking to brush up most important topics in python (before entering into numpy, pandas.....), just check out these two files mentioned below:

1. Python basics
2. Python essentials

If you are looking to cover most of the things python has got to offer (before entering into numpy, pandas.....). Check all of them in below mentioned sequence:

1. AA_Strings
2. AA_Numbers & Booleans
3. Input & Output
4. Operating thru python
5. Conditional statements
6. Sequences ft Python
   i. List
   ii. Tuples
   iii. Dictionaries
   iv. Sets
   
7. Avoiding Reps (Functions, Looping & Iterating)
8. OOPS

Topics covered

Python - Almost everything one needs to know right from scratch (basics) to advance

Numpy

1. Installing numpy
2. Importing/Loading numpy
3. Creating a numpy array
4. Creating a multidimensional numpy array
5. Range vs Arange function
6. Creating matrix of zeros, ones, diagonal matrix (ones)
7. Reshape vs Resize
8. Generating random values : Linspace(evenly spaced values between 2 no.), rand (sd), randn (nd), randint (ud)
9. Indexing & Slicing
10. Conditional Indexing
11. Broadcasting
12. Creating a copy of data set