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+In [ ]:
+
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+
+#Constructing dataframe
+df = pd.DataFrame(list(zip(time_scale, messag_size,tx_time_filt)),
+ columns =['Time Scale', 'Message Size','Transmission Time'])
+#Converting the type of data into float and integer
+
+df["Transmission Time"] = pd.to_numeric(df["Transmission Time"], downcast='float')
+df["Message Size"] = pd.to_numeric(df["Message Size"], downcast='integer')
+
+#Plot with all data captured
+figure1, (ax1,ax2) = plt.subplots(2,1)
+
+df.plot(y="Transmission Time",ax=ax1,color='blue',style='.',legend=False)
+ax1.set_xlabel('Measure')
+ax1.set_ylabel('Tx Time(ms)')
+ax1.minorticks_on()
+ax1.grid(which='major', linestyle='-', linewidth='0.5', color='red')
+ax1.grid(which='minor', linestyle=':', linewidth='0.5', color='black')
+
+df.plot(y="Message Size",ax=ax2,color='green',style='.',legend=False)
+ax2.set_xlabel('Measure')
+ax2.set_ylabel('Message Size(Bytes)')
+ax2.minorticks_on()
+ax2.grid(which='major', linestyle='-', linewidth='0.5', color='red')
+ax2.grid(which='minor', linestyle=':', linewidth='0.5', color='black')
+
+
+#Zoomed plot from last plot, centered at a high deviation of transmission time"
+figure2, (ax1,ax2) = plt.subplots(2,1)
+
+df.plot(y="Transmission Time",ax=ax1,color='blue',style='.',legend=False)
+ax1.set_xlim(20250, 20750)
+ax1.set_xlabel('Measure')
+ax1.set_ylabel('Tx Time(ms)')
+ax1.minorticks_on()
+ax1.grid(which='major', linestyle='-', linewidth='0.5', color='red')
+ax1.grid(which='minor', linestyle=':', linewidth='0.5', color='black')
+
+df.plot(y="Message Size",ax=ax2,color='green',style='.',legend=False)
+ax2.set_xlim(20250, 20750)
+ax2.set_xlabel('Measure')
+ax2.set_ylabel('Message Size(Bytes)')
+ax2.minorticks_on()
+ax2.grid(which='major', linestyle='-', linewidth='0.5', color='red')
+ax2.grid(which='minor', linestyle=':', linewidth='0.5', color='black')
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