Features

1. Read a txt file representing multiple graphs

a. Each individual graph will be represented as an object that contains attributes representing metadata (name, date, description, etc) and each individual graph object will have a pd dataframe representing the graph as an adjacency matrix and a dictionary whose values are sets of tuples representing the adjacency lists

b. Each object will then be appended into a python list (or maybe a numpy array) which will represent a collection of graphs

2. Low Level Transformations

a. Adding nodes

b. Adding edges

c. Deleting nodes

d. Deleting edges