Common functions

functions.py

def make_autopct(values):
    def my_autopct(pct):
        total = sum(values)
        val = int(round(pct*total/100.0))
        return '{p:.1f}%  ({v:d})'.format(p=pct,v=val)
    return my_autopct
  
def plotPieChart(column):
  freq_count = Counter(df[column])
  fig, ax = plt.subplots(figsize=(15, 7), subplot_kw=dict(aspect="equal"))
  patches, texts, autotexts = ax.pie(freq_count.values(), labels=freq_count.keys(), autopct=make_autopct(freq_count.values()), textprops=dict(color="w", size=12, weight='bold'))
  ax.legend(patches, freq_count.keys(), loc="upper left")
  ax.set_title(column)
  plt.show()
  
def plotHorzBar(column):
  data = df[column]
  count = {}
  for d in data:
    words = d.split(";")
    for w in words:
      if w in count.keys():
        count[w] = count[w] + 1
      else:
        count[w] = 1
  
  y_pos = np.arange(len(count.keys()))
  plt.barh(y_pos,count.values())
  plt.yticks(y_pos, count.keys())
  plt.show()

def plotBar(column):
  data = df[column]
  data = data.dropna()
  count = {1:0,2:0,3:0,4:0,5:0}
  for d in data:
    count[d] = count[d] + 1

  y_pos = range(1,6)
  plt.bar(y_pos,count.values())
  plt.yticks(y_pos, count.keys())
  plt.title("1 - highly disagree, 5 - highly agree")
  plt.show()  
  
def plotWordCloud(column):
  data = df[column]
  data = data.dropna()
  text = data.to_string()

  wordcloud = WordCloud(width = 900, height = 500, random_state=1, background_color='salmon', colormap='Pastel1', collocations=False, stopwords = STOPWORDS).generate(text)

  plt.figure(figsize=(20, 15))
  # Display image
  plt.imshow(wordcloud) 
  # No axis details
  plt.axis("off");
  
def summarizeFeedback(column):
  data = df[column]
  data = data.dropna()
  text = data.to_string()

  summ_per = summarize(text, ratio = 0.30)
  summ = Markdown('<h3>{}</h3>'.format(summ_per))
  return summ