diff --git a/Assets/Temporal_Graph/Bitcoin/Bitcoin_Code_Style/Bitcoin_code_style.py b/Assets/Temporal_Graph/Bitcoin/Bitcoin_Code_Style/Bitcoin_code_style.py
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index 0000000000000000000000000000000000000000..f9153771df4b3eb67ac8d184e22148660c93265f
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+++ b/Assets/Temporal_Graph/Bitcoin/Bitcoin_Code_Style/Bitcoin_code_style.py
@@ -0,0 +1,76 @@
+####################################################################################################################
+
+# Program Name : code_style.py 
+# Description  : Python code for Temporal Graph Visualisation
+# Author       : Mohamed Feroz Khan and Ramaguru sir
+# Created Date : 27-Nov-2022
+# Last Updated : 13-April-2023
+# Execution    : Python code_style.py
+####################################################################################################################
+
+
+import networkx as nx
+import matplotlib.pyplot as plt
+import pandas as pd
+import pathpy as pp
+
+df=pd.read_excel('Backup_BCT_BTC_500.xlsx')
+t = pp.TemporalNetwork()
+
+[t.add_edge(df['address'][i],df['balance'][i],int(df['time'][i])) for i in range(len(df))]
+
+# style for first node
+
+style1 = {    
+  'ts_per_frame': 1, 
+  'ms_per_frame': 2000,
+  'look_ahead': 2, 
+  'look_behind': 2, 
+  'node_size': 15, 
+  'inactive_edge_width': 2,
+  'active_edge_width': 4, 
+  'label_color' : '#ffffff',
+  'label_size' : '24px',
+  'label_offset': [0,5],
+  'active_node_color' : '#003800'
+  }
+
+# style for second node
+
+style2 = {    
+  'ts_per_frame': 1, 
+  'ms_per_frame': 2000,
+  'look_ahead': 2, 
+  'look_behind': 2, 
+  'node_size': 15, 
+  'inactive_edge_width': 2,
+  'active_edge_width': 4, 
+  'label_color' : '#ffffff',
+  'label_size' : '24px',
+  'label_offset': [0,5],
+  }
+
+stylenode = { 
+	'ts_per_frame': 1, 
+  	'ms_per_frame': 2000,
+  	'look_ahead': 2, 
+  	'look_behind': 2, 
+  	'node_size': 15, 
+  	'inactive_edge_width': 2,
+  	'active_edge_width': 4
+} 
+
+# loop and style for the node
+
+i=0
+for i in range(len(df)):
+	if df['time'][i] == 1:
+    		pp.visualisation.plot(t, **style1)
+	elif df['time'][i] == 2:
+    		pp.visualisation.plot(t, **style2)
+	else:
+    		pp.visualisation.plot(t, **style1)
+
+# visualisation for the given dataset
+
+pp.visualisation.export_html(t, 'my_temporal_network_sample.html')
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