한 개의 축에 여러 개 변수 시각화하기

• 연속형 변수일 때

  # Multiple box plots on one Axes
  fig, ax = plt.subplots(figsize=(12,10))
  data = [df_0['age'], df_1['age']]
  labels = ['normal', 'cancer']
  bp = ax.boxplot(data, vert=True, patch_artist=True)
  #fill with colors
  colors = ['lightblue', 'pink']
  for patch, color in zip(bp['boxes'], colors):
  patch.set_facecolor(color)
  
  #adding horizontal grid lines
  ax.yaxis.grid(True)
  
  plt.title('Age', fontsize= 30)
  plt.xticks([1, 2], labels, fontsize=15)
  #ax.set_ylabel('Granzyme B', fontsize=15)
  plt.show()

 

 

• 범주형 변수일 때

• import matplotlib.pyplot as plt
  
  # normal
  df_0_0 = sum(df_0['smoking'] == 0)
  df_0_1 = sum(df_0['smoking'] == 1)
  df_0_2 = sum(df_0['smoking'] == 2)
  # cancer
  df_1_0 = sum(df_1['smoking'] == 0)
  df_1_1 = sum(df_1['smoking'] == 1)
  df_1_2 = sum(df_1['smoking'] == 2)
  
  smoker = ['current', 'ex', 'non']
  num = [df_0_0, df_0_1, df_0_2]
  num_smoker = [
                [df_0_0, df_1_0], # 9, 21
                [df_0_1, df_1_1], # 16, 18
                [df_0_2, df_1_2]  # 25, 4
                ]
  type_smoker = ['current', 'ex', 'non']
  
  #print(num_smoker)
  X = np.arange(2)
  fig = plt.figure()
  ax = fig.add_axes([0,0,1,1])
  ax.bar(X + 0.00, num_smoker[0], color = 'pink', width = 0.25)
  ax.bar(X + 0.25, num_smoker[1], color = 'lightgreen', width = 0.25)
  ax.bar(X + 0.50, num_smoker[2], color = 'lightblue', width = 0.25)
  ax.legend(labels=type_smoker)
  plt.xticks([0.25, 1.25], labels, fontsize=15)
  plt.title('Smoking', fontsize= 20)
  plt.show()