I was trying to plot an area graph with these values.

y1=[26.8,24.97,25.69,24.07]
y2=[21.74,19.58,20.7,21.09]
y3=[13.1,12.45,12.75,10.79]
y4=[9.38,8.18,8.79,6.75]
y5=[12.1,10.13,10.76,8.03]
y6=[4.33,3.73,3.78,3.75]

df = pd.DataFrame([y1,y2,y3,y4,y5,y6])

cumsum = df.cumsum()
cumsum

I was able to do the area part, however I don´t know how to add the specific numbers in the graph.

labels = ["Medical", "Surgical", "Physician Services", "Newborn", "Maternity", "Mental Health"]
x = [1,2,3,4]
years = [2011,2012,2013,2014]

fig, ax = plt.subplots()
plt.title("Overall, inpatient costs have decreased in 2011")
ax.stackplot(x, y1,y2,y3,y4,y5,y6, labels=labels, colors = sns.color_palette("Blues")[::-1])
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)

plt.legend(bbox_to_anchor=(1.05, 1), loc="upper left")
display()

This is the current output, but does not match the desired output

The output should look something like this.

CodePudding user response：

• Since there is already a dataframe, use
  • I think a stacked bar plot is a cleaner presentation of the data because the data is discrete, not continuous. The lines in the area plot imply a continuous dataset.
    • See this

      CodePudding user response：

      You could add the following snippet at the end of your code:

      for i, c in df.iteritems():
          v2 = 0
          for v in c:
              v2  = v
              ax.text(i 1, v2, f'${v:.2f}')
      

      output:

      

      CodePudding user response：

      I change these lines in your code:

      fig, ax = plt.subplots(figsize=(10,7))
      ax.stackplot(years, y1,y2,y3,y4,y5,y6, labels=labels, colors = sns.color_palette("Blues")[::-1])
      plt.legend(bbox_to_anchor=(1.1, 1), loc="upper left")
      

      And add these lines and get what you want:

      df2 = df.cumsum()
      
      for id_col, col in df2.iteritems():
          prev_val = 0
          for val in col:
              ax.annotate(text='${}'.format(round((val - prev_val),2)), xy=(years[id_col],(val)), weight='bold')        
              prev_val = val
      
      plt.xticks(years)
      

      Output:

      

      Whole code:

      import matplotlib.pyplot as plt
      import pandas as pd
      import seaborn as sns
      
      y1=[26.8,24.97,25.69,24.07]
      y2=[21.74,19.58,20.7,21.09]
      y3=[13.1,12.45,12.75,10.79]
      y4=[9.38,8.18,8.79,6.75]
      y5=[12.1,10.13,10.76,8.03]
      y6=[4.33,3.73,3.78,3.75]
      labels = ["Medical", "Surgical", "Physician Services", 
                "Newborn", "Maternity", "Mental Health"]
      years = [2011,2012,2013,2014]
      fig, ax = plt.subplots(figsize=(10,7))
      plt.title("Overall, inpatient costs have decreased in 2011", weight='bold')
      ax.spines['right'].set_visible(False);ax.spines['top'].set_visible(False)
      ax.spines['bottom'].set_visible(False);ax.spines['left'].set_visible(False)
      ax.stackplot(years, y1,y2,y3,y4,y5,y6, labels=labels, 
                   colors = sns.color_palette("Blues")[::-1])
      
      df2 = pd.DataFrame([y1,y2,y3,y4,y5,y6]).cumsum()
      for id_col, col in df2.iteritems():
          prev_val = 0
          for val in col:
              ax.annotate(text='${}'.format(round((val - prev_val),2)), 
                          xy=(years[id_col],(val)) , weight='bold')        
              prev_val = val
      
      plt.xticks(years)
      plt.xlabel('Year')
      plt.ylabel('Cost (USD)')
      plt.legend(bbox_to_anchor=(1.1, 1), loc="upper left")
      plt.show()