ThiagoFPMR

# Parameters for our Synthetic Network

num_of_nodes = 100 # Total number of nodes (which are, in our case, people)
edges_per_node = 4 # Amount of relations a given person(node) will have by default
prob_of_triangle  = 0.1 # Chance of a triangle happening given a relation

# Defining The Network

G = nx.powerlaw_cluster_graph(num_of_nodes, edges_per_node, prob_of_triangle)

ThiagoFPMR

def scatter_y_label (var):
  if var == 'total_cases':
    return 'Percentage Infected'
  elif var == 'total_tests':
    return 'Percentage Tested'
  elif var == 'total_deaths':
    return 'Percentage Dead'
  elif var == 'total_recovered':
    return 'Percentage Recovered'

ThiagoFPMR

import dash
from dash.dependencies import Output, Input
import dash_core_components as dcc
import dash_html_components as html
import plotly.express as px
import pandas as pd


external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)

ThiagoFPMR

import dash
from dash.dependencies import Output, Input
import dash_core_components as dcc
import dash_html_components as html
import plotly.express as px
import pandas as pd


external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)

ThiagoFPMR

ThiagoFPMR

# Defining the functio we'll use to convert the columns to snakecase

def to_snakecase (cols):
  map_dict = {}
  for col in cols:
    map_dict[col] = col.lower().strip().replace(' ', '_')
  return map_dict

# Defining the function we'll use to change the country names to the same format

ThiagoFPMR

ThiagoFPMR

ThiagoFPMR

ThiagoFPMR