diff --git a/ex3/figures/FFT_packets_uIPs.png b/ex3/figures/FFT_packets_uIPs.png
new file mode 100644
index 0000000..5e083f1
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diff --git a/ex3/figures/tcp_packets_uIPs_timeseries.png b/ex3/figures/tcp_packets_uIPs_timeseries.png
new file mode 100644
index 0000000..0a1de7d
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diff --git a/ex3/rep-20.py b/ex3/rep-20.py
index 70be47e..a9a62f1 100644
--- a/ex3/rep-20.py
+++ b/ex3/rep-20.py
@@ -4,6 +4,9 @@ import numpy as np
 import matplotlib.pyplot as plt
 import math as m
 dataset = pd.read_csv('csv/team13_protocol.csv').fillna(0)
+dataset['timestamp'] = pd.to_datetime(dataset['timestamp'], unit='s')
+dataset = dataset.set_index('timestamp')
+print(dataset)
 p6_pkts = dataset['6 · # Packets'].tolist()
 #return number of elements in p6_pkts list
 n = len(p6_pkts)
@@ -18,6 +21,9 @@ k = range(0,n-1) #creates an array from 0 to n-1
 x = k[1:m.floor(n/2)]
 #set amp. values in the y-axis and specify the limit
 y = pkt_amp[1:m.floor(n/2)]
+plt.figure(figsize=(20,10))
+plt.tight_layout(h_pad=0.5)
+plt.subplot(2, 1, 1)
 plt.stem(x, y)
 #find max index and value
 max_k = np.flip(np.argsort(pkt_amp[1:m.floor(n/2)]))[0]
@@ -45,7 +51,8 @@ k = range(0,n_2-1) #creates an array from 0 to n-1
 #set k values in the x-axis and specify the limit
 x = k[1:m.floor(n_2/2)]
 #set amp. values in the y-axis and specify the limit
-y = pkt_amp[1:m.floor(n/2)]
+y = uIPs_amp[1:m.floor(n/2)]
+plt.subplot(2, 1, 2)
 plt.stem(x, y)
 #find max index and value
 max_k = np.flip(np.argsort(uIPs_amp[1:m.floor(n_2/2)]))[0]
@@ -54,8 +61,19 @@ plt.xlim(1, m.floor(n_2/2))
 plt.xlabel('k') #sets x-axis label
 #set y-axis label
 plt.ylabel('Amplitude [millions of unique source IPs]')
-plt.title('Amp. Spectrum for unique source IPs') #displays title
+plt.title('Amp. Spectrum for #unique source IPs') #displays title
+plt.show()
 
 print('TCP #uIPs/hour - FFT max value: ', round(max_amp / 1000000, 2))
 print('TCP #uIPs/hour - k of FFT max value: ', np.where(uIPs_amp == max_amp))
 print('TCP #uIPs/hour - period of k corresponding to FFT max value: ', n_2 / 31)
+
+# Plot TCP #pkts/hour and TCP #uIPs/hour timeseries
+plt.figure(figsize=(20,10))
+plt.tight_layout(h_pad=2)
+plt.subplot(2, 1, 1)
+dataset['6 · # Packets'].plot(xlabel='', ylabel='Number of TCP Packets', title='Number of TCP Packets over Time')
+
+plt.subplot(2, 1, 2)
+dataset['6 · # Unique Source IPs'].plot(xlabel='Time', ylabel='Number of Unique TCP Source IPs', title='Number of Unique TCP Source IPs over Time')
+plt.show()