Intro-to-machine-learning/outlier/enron_outliers.py

#!/usr/bin/python

import pickle
import sys
import matplotlib.pyplot
sys.path.append("../tools/")
from feature_format import featureFormat, targetFeatureSplit


### read in data dictionary, convert to numpy array
data_dict = pickle.load( open("../final_project/final_project_dataset.pkl", "r") )
features = ["salary", "bonus"]
data = featureFormat(data_dict, features)
max_ = list(data_dict.keys())[list(data_dict.values()).index(max(data_dict.values()))]
print (max_)
### your code below



for point in data:
    salary = point[0]
    bonus = point[1]
    matplotlib.pyplot.scatter( salary, bonus )

matplotlib.pyplot.xlabel("salary")
matplotlib.pyplot.ylabel("bonus")
matplotlib.pyplot.show()