Haydar Ali Ismail haydarai

## Split independent-target.py
X = bos.drop('PRICE', axis = 1)
Y = bos['PRICE']

## Mean Squared Error.py
mse = sklearn.metrics.mean_squared_error(Y_test, Y_pred)
print(mse)

## Summary statistics.py
print(bos.describe())

## Insert price column.py
bos['PRICE'] = boston.target
print(bos.head())

## Add colum names.py
bos.columns = boston.feature_names
print(bos.head())

## Convert to data frame.py
bos = pd.DataFrame(boston.data)
print(bos.head())

## Dataset shape.py
print(boston.data.shape)

## Check keys.py
print(boston.keys())

## hello-world.py
from mrjob.job import MRJob

class mrWordCount(MRJob):

    def mapper(self, key, line):
        for word in line.split(' '):
            yield word.lower(), 1

    def reducer(self, word, occurrences):
        yield word, sum(occurrences)

## input.txt
I am Sam

I am Sam
Sam I am

That Sam I am
That Sam I am
I do not like
that Sam I am
	mse = sklearn.metrics.mean_squared_error(Y_test, Y_pred)
	print(mse)
	from mrjob.job import MRJob

	class mrWordCount(MRJob):

	def mapper(self, key, line):
	for word in line.split(' '):
	yield word.lower(), 1

	def reducer(self, word, occurrences):
	yield word, sum(occurrences)
	I am Sam

	I am Sam
	Sam I am

	That Sam I am
	That Sam I am
	I do not like
	that Sam I am