Use the sacramento.csv file attached to complete the following task. Create a file, sacramento.py, that loads the .csv file and runs a logistic regression. The regression should predict whether or not a house has 1 or more than one bathroom based on beds, sqft, and price, in that order. Note: you will not need to upload the .csv to CodeGrade because I have pre-loaded it. ● You will need to create a new variable from baths, and it should make it such that those observations of 1 bath correspond to a value of 0, and those with more than 1 bath correspond to a 1. ● Make sure to add a constant using sm.add_constant(X) ● Your file should print the results in this way: print(mod.params.round(2)) print(mod.pvalues.round(2)) print('The smallest p-value is for sqft') csv: https://drive.google.com/file/d/1dAsFlD6W5T1lay68bF4aI3-P8cu4mbYa/view?usp=sharing
Use the sacramento.csv file attached to complete the following task. Create a file, sacramento.py, that loads the .csv file and runs a logistic regression. The regression should predict whether or not a house has 1 or more than one bathroom based on beds, sqft, and price, in that order. Note: you will not need to upload the .csv to CodeGrade because I have pre-loaded it. ● You will need to create a new variable from baths, and it should make it such that those observations of 1 bath correspond to a value of 0, and those with more than 1 bath correspond to a 1. ● Make sure to add a constant using sm.add_constant(X) ● Your file should print the results in this way: print(mod.params.round(2)) print(mod.pvalues.round(2)) print('The smallest p-value is for sqft')
csv: https://drive.google.com/file/d/1dAsFlD6W5T1lay68bF4aI3-P8cu4mbYa/view?usp=sharing
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