diff --git a/lib/matplotlib/pyplot.py b/lib/matplotlib/pyplot.py
index 8fa0f801ce9a..f8020e1fc69c 100644
--- a/lib/matplotlib/pyplot.py
+++ b/lib/matplotlib/pyplot.py
@@ -2218,6 +2218,33 @@ def bar(
         x, height, width=width, bottom=bottom, align=align,
         **({"data": data} if data is not None else {}), **kwargs)
 
+def grouped_bar(bar_width,df,group,categ,y):
+	"""
+	Creates a grouped bar chart given a dataframe df, column names(categ: categories column,group:column groups for each xtick ,y:height of bars)
+	
+	E.g: Consider the dataframe below
+	df1=pd.DataFrame({'fruit':['apple']*3+['banana']*3+['mango']*3,
+             'energy':[10,20,15,10,20,15,10,20,15],'state':['notripe','ripe','mid']*3})
+	
+
+	#creates the bar plot:
+
+	grouped_bar(bar_width=0.10,df=df1,group='state',categ='fruit',y='energy')
+	"""
+    uniq_cat=df[categ].unique()
+    uniq_group=df[group].unique()
+    
+    plt.figure(figsize=(7,7))
+    plt.style.use('seaborn-dark-palette')
+    
+    for i,barheights in enumerate(uniq_group):
+        barheights=(df[df[group]==uniq_group[i]][y]).values
+        x=np.arange(len(uniq_cat))
+        plt.bar(x+(bar_width*i),barheights,width=bar_width,label=uniq_group[i])
+        
+    plt.xticks(ticks=x+bar_width/len(uniq_group),labels=uniq_cat)    
+    plt.legend()
+
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
 @docstring.copy(Axes.barbs)