#!/usr/bin/env python

#PLOTDATA Plots the data points x and y into a new figure

# PLOTDATA(x,y) plots the data points and gives the figure axes labels of

# population and profit.

# ====================== YOUR CODE HERE ======================

# Instructions: Plot the training data into a figure using the

# "figure" and "plot" commands. Set the axes labels using

# the "xlabel" and "ylabel" commands. Assume the

# population and revenue data have been passed in

# as the x and y arguments of this function.

#

# Hint: You can use the 'rx' option with plot to have the markers

# appear as red crosses. Furthermore, you can make the

# markers larger by using plot(..., 'rx', 'MarkerSize', 10);

#figure; # open a new figure window

#X = data(:, 1); y = data(:, 2);

#m = length(y); # number of training examples

# Plot Data

# Note: You have to complete the code in plotData.m

#plotData(X, y);

import pandas as pd

import matplotlib.pyplot as plt

data = pd.read_csv('ex1data1.txt')

print data.head()

f = plt.figure()

p = plt.scatter(data.population,data.profit,s=15,marker='x')

p.axes.set_title('A Scatter Plot')

p.axes.yaxis.label.set_text('Profit in $10,000s')

p.axes.xaxis.label.set_text('Population of City in 10,000s')

# Is there some better way to do that in matplotlib?

# p.axes.yaxis.set_label_text('blah') works but is about the same length.

f.show()

# ============================================================