How to display custom values on a bar plot

New in matplotlib 3.4.0

There is now a built-in Axes.bar_label to automatically label bar containers:

• For single-group bar plots, pass the single bar container:

  ax = sns.barplot(x='day', y='tip', data=groupedvalues)
  ax.bar_label(ax.containers[0])
  

  

• For multi-group bar plots (with hue), iterate the multiple bar containers:

  ax = sns.barplot(x='day', y='tip', hue="sex", data=df)
  for container in ax.containers:
      ax.bar_label(container)
  

  

More details:

• How to label count plots (sns.countplot and sns.catplot)
• How to label percentage counts (fmt param)
• How to label with commas as thousands separators (labels param)
• How to label thresholded bar plots
• How to label horizontal bar plots

Color-ranked version

Is there a way to scale the colors of the bars, with the lowest value of total_bill having the lightest color (in this case Friday) and the highest value of total_bill having the darkest?

1. Find the rank of each total_bill value:

   • Either use Series.sort_values:

     ranks = groupedvalues.total_bill.sort_values().index
     # Int64Index([1, 0, 3, 2], dtype="int64")
     

   • Or condense Ernest’s Series.rank version by chaining Series.sub:

     ranks = groupedvalues.total_bill.rank().sub(1).astype(int).array
     # [1, 0, 3, 2]
     

2. Then reindex the color palette using ranks:

   palette = sns.color_palette('Blues_d', len(ranks))
   ax = sns.barplot(x='day', y='tip', palette=np.array(palette)[ranks], data=groupedvalues)