code: def stacked_barplot(
      df,
      bar_width="auto",
      colors="bgrcky",
      labels="index",
      rotation=90,
      legend_loc="best",
  ):
      """
      Function to plot stacked barplots
  
      Parameters
      ----------
      df : pandas.DataFrame
          A pandas DataFrame where the index denotes the
          x-axis labels, and the columns contain the different
          measurements for each row.
      bar_width: 'auto' or float (default: 'auto')
          Parameter to set the widths of the bars. if
          'auto', the width is automatically determined by
          the number of columns in the dataset.
      colors: str (default: 'bgrcky')
          The colors of the bars.
      labels: 'index' or iterable (default: 'index')
          If 'index', the DataFrame index will be used as
          x-tick labels.
      rotation: int (default: 90)
          Parameter to rotate the x-axis labels.
      legend_loc : str (default: 'best')
          Location of the plot legend
          {best, upper left, upper right, lower left, lower right}
          No legend if legend_loc=False
  
      Returns
      ---------
      fig : matplotlib.pyplot figure object
  
      Examples
      -----------
      For usage examples, please see
      https://rasbt.github.io/mlxtend/user_guide/plotting/stacked_barplot/
  
      """
      # Setting the positions and width for the bars
      pos = np.array(range(len(df.index)))
  
      if bar_width == "auto":
          width = 1 / (len(df.columns[1:]) * 2)
      else:
          width = bar_width
  
      if labels == "index":
          labels = df.index
  
      color_gen = cycle(colors)
  
      label_pos = [pos]
  
      # Plotting the bars
      fig, ax = plt.subplots(figsize=(12, 6))
  
      plt.bar(
          pos,
          df.iloc[:, 0],
          width,
          alpha=0.8,
          color=next(color_gen),
          label=df.columns[0],
      )
  
      for i, c in enumerate(df.columns[1:]):
          bar_pos = [p + width * (i + 1) for p in pos]
          label_pos.append(bar_pos)
          plt.bar(
              bar_pos,
              df.iloc[:, i + 1],
              width,
              alpha=0.5,
              color=next(color_gen),
              label=c,
          )
  
      # Setting axis labels and ticks
  
      label_pos = np.asarray(label_pos).mean(axis=0) + width * 0.5
  
      ax.set_xticks(label_pos)
      ax.set_xticklabels(
          labels, rotation=rotation, horizontalalignment="center"
      )
  
      # Setting the x-axis and y-axis limits
      plt.xlim(min(pos) - width, max(pos) + width * 7)
  
      if legend_loc:
          plt.legend(loc=legend_loc, scatterpoints=1)
      return fig
  
imports: from itertools import cycle
  import matplotlib.pyplot
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: stacked_barplot(df, bar_width, colors, labels, rotation, legend_loc) and returns: fig