22 of 100: Curved stacked bar chart in matplotlib

Comments

1. i6ty3

   September 13, 2024 at 8:22 pm

   I would suggest using a sine, or cosine function to achieve the desired output instead of repeating arcs. In addition to making the figure look better, the number of lines the code should decrease as well.

   I wish I could attach a figure, but here is what I am talking about.

   x = np.linspace(0,np.pi*20, 1000)
   y = np.sin(x)
   plt.plot(x,y, linewidth = 3, solid_capstyle=’round’)
   plt.plot(x[:700],y[:700], linewidth = 10, solid_capstyle=’round’)
   plt.ylim(-30,30)

   Let me know, if you think I should write the entire code for this one.

   Reply

   • Ruth Pozuelo Martinez

     September 13, 2024 at 8:32 pm

     You are right, that would be more efficient!. Let me know if you re-write it otherwise I will do it 🙂

     Reply

     • i6ty3

       September 14, 2024 at 8:01 am

       import matplotlib.pyplot as plt
       import numpy as np
       import pandas as pd

       color_dict = {“Norway”: “#2B314D”, “Denmark”: “#A54836”, “Sweden”: “#5375D4″, }

       xy_ticklabel_color, xy_label_color, grid_color, datalabels_color =’#101628′,”#101628”, “#C8C9C9”, “#757C85”

       data = {
       “year”: [2004, 2022, 2004, 2022, 2004, 2022],
       “countries” : [ “Denmark”, “Denmark”, “Norway”, “Norway”,”Sweden”, “Sweden”,],
       “sites”: [4,10,5,8,13,15]
       }
       df= pd.DataFrame(data)

       df = df.sort_values([ ‘year’,’sites’], ascending=False ).reset_index(drop=True)
       df[‘ctry_code’] = df.countries.astype(str).str[:2].astype(str).str.upper()
       df[‘year_lbl’] =”‘”+df[‘year’].astype(str).str[-2:].astype(str)

       sort_order_dict = {“Denmark”:2, “Sweden”:3, “Norway”:1, 2004:4, 2022:5}
       df = df.sort_values(by=[‘year’,’countries’,], key=lambda x: x.map(sort_order_dict))
       #map the colors of a dict to a dataframe
       df[‘color’]= df.countries.map(color_dict)

       max_sites = df[df.year == df.year.max()][‘sites’].to_list()
       min_sites = df[df.year == df.year.min()][‘sites’].to_list()
       colors = df.color.unique()
       countries = df[‘ctry_code’].unique()
       y_axis= [0,1,2]

       fig, ax = plt.subplots(figsize=(6,6),sharex=True, sharey=True, facecolor = “#FFFFFF”, zorder= 1)

       smoothing = 100

       for y_ax, max_site, min_site,color in zip(reversed(y_axis), max_sites,min_sites,colors):
       x = np.linspace(0, np.pi * max_site, smoothing* max_site)
       y = np.sin(x)*.06
       ax.plot(x,y+y_ax, linewidth = 3, solid_capstyle=’round’, color = color)
       ax.plot(x[:smoothing*min_site],y[:smoothing*min_site]+y_ax, linewidth = 10, solid_capstyle=’round’, color = color)

       #add data labels
       ax.text(x[-1],y[-1]+y_ax + .1, max_site, size = 12, color= datalabels_color, ha = ‘center’)
       ax.text(x[min_site*smoothing], y[min_site*smoothing]+y_ax+.1,min_site , size = 12, color= datalabels_color, ha = ‘center’, va = ‘bottom’)

       ax.yaxis.set_ticks(y_axis, labels = reversed(countries),weight=’bold’)
       ax.spines[[‘left’, ‘top’,’bottom’,’right’]].set_visible(False)
       ax.tick_params(axis=’both’, which=’major’, labelsize=12, length=0, color= xy_ticklabel_color)
       ax.set(xlim=[-1, (max(max_sites)+1)*np.pi], ylim=[ min(y_axis)-1, max(y_axis) + 1])
       ax.set_xticks([])

       #add annotations
       ax.annotate(df.year.min(), xy = (min_sites[0]*np.pi, max(y_axis)+.25), xytext=(min_sites[0]*np.pi-0.85, max(y_axis) + .75 ),
       color=’black’, size = 12, weight = “bold”,
       arrowprops=dict( arrowstyle=’-‘,color = xy_label_color ) ,
       annotation_clip=False)

       ax.annotate(df.year.max(), xy = (max_sites[0]*np.pi, max(y_axis) +.25), xytext=(max_sites[0]*np.pi-0.85, max(y_axis) + .75),
       color=’black’, size= 12, weight = “bold”,
       arrowprops=dict( arrowstyle=’-‘,color = xy_label_color ) ,
       annotation_clip=False)

       Reply

       • Ruth Pozuelo Martinez

         September 14, 2024 at 10:49 pm

         Now it looks exactly the same, thanks for the feedback!

         Reply