old_contents: #!/usr/local/bin/python3
  # -*- coding: utf-8 -*-
  ##
  ## DM2583 Big Data in Media Technology
  ## Final project
  ##
  ## Carlo Rapisarda
  ## carlora@kth.se
  ##
  ## Plot Results
  ## Oct. 10, 2017
  ##
  
  
  import csv
  import numpy as np
  import matplotlib.pyplot as plt
  import matplotlib.patches as patches
  import matplotlib.path as path
  from matplotlib.ticker import FuncFormatter, MaxNLocator
  
  
  def plot_raw_classification(csv_file_path):
  	values = []
  	with open(csv_file_path, "r") as csv_file:
  		reader = csv.reader(csv_file, delimiter=',')
  		for line in reader:
  			values.append(float(line[1]))
  	plot_histogram(values, 15, 'Evaluation', 'Amount')
  
  
  
  def plot_histogram_old(values, bars, xlabel, ylabel):
  
  	fig, ax = plt.subplots()
  	n, bins = np.histogram(values, bars)
  
  	# get the corners of the rectangles for the histogram
  	left = np.array(bins[:-1])
  	right = np.array(bins[1:])
  	bottom = np.zeros(len(left))
  	top = bottom + n
  
  	# we need a (numrects x numsides x 2) numpy array for the path helper
  	# function to build a compound path
  	XY = np.array([[left, left, right, right], [bottom, top, top, bottom]]).T
  
  	# get the Path object
  	barpath = path.Path.make_compound_path_from_polys(XY)
  
  	# make a patch out of it
  	patch = patches.PathPatch(barpath)
  	ax.add_patch(patch)
  
  	# update the view limits
  	ax.set_xlim(left[0], right[-1])
  	ax.set_ylim(bottom.min(), top.max())
  
  	labels = ['Negative', 'Neutral', 'Positive']
  
  	def format_fn(tick_val, tick_pos):
  		if int(tick_val) in range(0,3):
  			return labels[int(tick_val)]
  		else:
  			return ''
  
  	ax.xaxis.set_major_formatter(FuncFormatter(format_fn))
  	ax.xaxis.set_major_locator(MaxNLocator(integer=True))
  
  	plt.xlabel(xlabel)
  	plt.ylabel(ylabel)
  	plt.show()
  
  
  def plot_histogram(values, bars, xlabel, ylabel):
  
  	occurrences = [0,0,0]
  	for v in values:
  		occurrences[v] += 1
  	
  	fig, ax = plt.subplots()
  	colors = ['red', 'yellow', 'green']
  	labels = ['Negative', 'Neutral', 'Positive']
  
  	labels_range = [i for i in range(len(labels))]
  
  	ax.barh(labels_range, occurrences, align='center', color=colors)
  	ax.set_yticks(labels_range)
  	ax.set_yticklabels(labels)
  	ax.set_xlabel('Tweets')
  
  	plt.title("Classification")
  	plt.show()
  
  
  # plot_raw_classification("./480ktrump_results.csv")
  
new_contents: #!/usr/local/bin/python3
  # -*- coding: utf-8 -*-
  ##
  ## DM2583 Big Data in Media Technology
  ## Final project
  ##
  ## Carlo Rapisarda
  ## carlora@kth.se
  ##
  ## Plot Results
  ## Oct. 10, 2017
  ##
  
  
  import csv
  import numpy as np
  import matplotlib.pyplot as plt
  import matplotlib.patches as patches
  import matplotlib.path as path
  from matplotlib.ticker import FuncFormatter, MaxNLocator
  
  
  def plot_raw_classification(csv_file_path):
  	values = []
  	with open(csv_file_path, "r") as csv_file:
  		reader = csv.reader(csv_file, delimiter=',')
  		for line in reader:
  			values.append(float(line[1]))
  	plot_histogram(values, 15, 'Evaluation', 'Amount')
  
  
  
  def plot_histogram_old(values, bars, xlabel, ylabel):
  
  	fig, ax = plt.subplots()
  	n, bins = np.histogram(values, bars)
  
  	# get the corners of the rectangles for the histogram
  	left = np.array(bins[:-1])
  	right = np.array(bins[1:])
  	bottom = np.zeros(len(left))
  	top = bottom + n
  
  	# we need a (numrects x numsides x 2) numpy array for the path helper
  	# function to build a compound path
  	XY = np.array([[left, left, right, right], [bottom, top, top, bottom]]).T
  
  	# get the Path object
  	barpath = path.Path.make_compound_path_from_polys(XY)
  
  	# make a patch out of it
  	patch = patches.PathPatch(barpath)
  	ax.add_patch(patch)
  
  	# update the view limits
  	ax.set_xlim(left[0], right[-1])
  	ax.set_ylim(bottom.min(), top.max())
  
  	labels = ['Negative', 'Neutral', 'Positive']
  
  	def format_fn(tick_val, tick_pos):
  		if int(tick_val) in range(0,3):
  			return labels[int(tick_val)]
  		else:
  			return ''
  
  	ax.xaxis.set_major_formatter(FuncFormatter(format_fn))
  	ax.xaxis.set_major_locator(MaxNLocator(integer=True))
  
  	plt.xlabel(xlabel)
  	plt.ylabel(ylabel)
  	plt.show()
  
  
  def plot_histogram(values, bars, xlabel, ylabel):
  
  	occurrences = [0,0,0]
  	for v in values:
  		occurrences[v] += 1
  	
  	fig, ax = plt.subplots()
  	colors = ['red', 'yellow', 'green']
  	labels = ['Negative', 'Neutral', 'Positive']
  
  	labels_range = [i for i in range(len(labels))]
  
  	ax.bar(labels_range, occurrences, color=colors)
  	ax.set_xticks(labels_range)
  	ax.set_xticklabels(labels)
  	ax.set_ylabel('Tweets')
  
  	plt.title("Classification")
  	plt.show()
  
  
  # plot_raw_classification("./480ktrump_results.csv")
  
subject: Fix bar graph