def load_study_notes_data(): # Load study notes data from a JSON file (e.g., 'bionic_turtle_frm_part1.json') with open('bionic_turtle_frm_part1.json') as f: return json.load(f)
# Display the concept map plt.show()
# Create a directed graph to represent the concept map G = nx.DiGraph() bionic turtle frm part 1 study notes free download
# Example usage: topic = 'Financial Markets and Products' generate_concept_map(topic)
# Add nodes and edges based on the study notes data for concept in study_notes_data[topic]: G.add_node(concept['name']) for subtopic in concept['subtopics']: G.add_node(subtopic['name']) G.add_edge(concept['name'], subtopic['name']) def load_study_notes_data(): # Load study notes data from
The Bionic Turtle FRM (Financial Risk Manager) Part 1 study notes are a comprehensive resource for candidates preparing for the FRM exam. To create an interesting feature, we'll design a Python-based tool that generates concept maps to help visualize relationships between key concepts in the study notes.
A concept map illustrating the relationships between key concepts, subtopics, and formulas for the topic "Financial Markets and Products". import networkx as nx import matplotlib
import networkx as nx import matplotlib.pyplot as plt
Concept Map Generator
def generate_concept_map(topic): # Load relevant study notes data (e.g., from a JSON file) study_notes_data = load_study_notes_data()
# Position nodes and draw the graph pos = nx.spring_layout(G) nx.draw_networkx_nodes(G, pos) nx.draw_networkx_labels(G, pos) nx.draw_networkx_edges(G, pos, edge_color='gray')
