Question 1: Create a Dataframe having 8 columns namely, A,B,C,D,E,F,G,H with the following properties: 1) Number of rows: 2500, Number of columns: 8 2) Create a Dataframe with random integers ranges from 0 to 3 3) Values of Column A = Column B + Column C 4) Values of Column H = Column G - Column A Question 2: For the dataframe created in Q1, create a new dataframe by choosing following columns [A, B, C, D, E, F], create a bayesian model with the following edges ('A', 'B'), ('C', 'B'), ('C', 'D'),('E', 'F'). Estimate the model parameters of node 'B' using Bayesian Estimator. Carry out the following tasks: 1. Create a dataframe as instructed in question 1 2. Create a new dataframe by choosing the following columns [A, B, C, D, E, F] 3. Create a Bayesian model with the following edges ('A', 'B'), ('C', 'B'), ('C', 'D'),('E', 'F') 4. Estimate the model parameters of node 'B' using Bayesian Estimator 5. Write all the output in a .csv file
question1 #To be given to students import pandas as pd import numpy as np import random np.random.seed(2) data = pd.DataFrame() ##Write your code here question2 from pgmpy.models import BayesianModel from pgmpy.estimators import BayesianEstimator #write code here print(node_B_cpds) #write output to a file np.savetxt("/code/output/output2.csv", node_B_cpds, delimiter=",")
Here is data frame
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