diff --git a/img/comparison.png b/img/comparison.png
index e3e1e90..16840bb 100644
Binary files a/img/comparison.png and b/img/comparison.png differ
diff --git a/src/comparison.py b/src/comparison.py
index 9d0cc49..a5fe3ec 100644
--- a/src/comparison.py
+++ b/src/comparison.py
@@ -3,6 +3,7 @@
 import numpy as np
 from collections import defaultdict
 import sys
+import datetime
 
 def fips_to_name(FIPS):
     map = defaultdict(lambda: FIPS)
@@ -14,20 +15,25 @@ def fips_to_name(FIPS):
     return map[FIPS]
 
 def comparison(FIPS_1='44003', FIPS_2='01125'):
-    months = {
-        'May':'05-31-2021',
-        'June':'06-30-2021',
-        'July':'07-31-2021',
-        'August':'08-31-2021',
-        'September':'09-30-2021',
-        'October':'10-31-2021',
-        'November':'11-30-2021'
-        }
+    months = pd.read_csv("months.csv")
+    dates = months.date.to_list()
+    #x = [0, 1, 2, 3, 4, 5, 6]
+    #labels = ['May', 'June', 'July', 'August', 'September', 'October', 'November']
+    x = []
+    labels = []
     file_list = []
-    for month, csv_date in months.items():
-        df = pd.read_csv('data/Merge/vaccinations-and-deaths-' + csv_date +'.csv', converters={'FIPS' : str})
+    i = 0
+    #To update x, y labels of county-view graph from dates in csv
+    for date in dates:
+        datetime_object = datetime.datetime.strptime(date, "%m-%d-%Y")
+        month_Name = datetime_object.strftime("%B")
+        month_year= datetime_object.strftime("%b")+"-"+datetime_object.strftime("%y")
+        labels.append(month_year)
+        x.append(i)
+        i= i+1
+        df = pd.read_csv('data/Merge/vaccinations-and-deaths-' + date +'.csv', converters={'FIPS' : str})
         df['Deaths_Per_1e5'] = df['Deaths'] / df['Census2019_18PlusPop'] * 1e5
-        df['Month'] = month
+        df['Month'] = month_Name
         file_list.append(df)
     merged_df = pd.concat(file_list)
     cleaned_df = merged_df[merged_df['FIPS'].str.contains(FIPS_1+"|"+FIPS_2)]
@@ -47,13 +53,15 @@ def comparison(FIPS_1='44003', FIPS_2='01125'):
     FIPS_2_death = FIPS_2_death['Deaths_Per_1e5']
 
     fig,ax1 = plt.subplots() 
-    x = [0, 1, 2, 3, 4, 5, 6]
-    labels = ['May', 'June', 'July', 'August', 'September', 'October', 'November']
+    
+    plt.tick_params(axis='x', rotation=30 ,direction='out', length=len(x))
+    plt.figure(figsize=(len(x), 100))
     x = np.arange(len(labels))
-    width = 0.35 
+    width = 0.35
     ax1.set_xticks(x, labels)
     ax1.set_ylim(0, 100)
-    ax1.set_xlim(0,6)
+    ax1.set_xlim(-1,len(x))
+    
     ax1.set_title('18+ Vaccination Rates and Deaths in '+FIPS_1_name+" and "+FIPS_2_name, wrap=True)
     ax1.set_xlabel('Month 2021')
     ax1.set_ylabel('Percent Vaccinated') 
diff --git a/src/scatters.py b/src/scatters.py
index 21ba4b2..1276db4 100644
--- a/src/scatters.py
+++ b/src/scatters.py
@@ -6,6 +6,7 @@
 import matplotlib.pyplot as plt
 import sys
 import numpy as np
+import datetime
 
 def scatter(month):
     df = pd.read_csv('data/Merge/vaccinations-and-deaths-'+month+'.csv', converters={'FIPS' : str})
@@ -16,13 +17,17 @@ def scatter(month):
     x = df[xlabel]
     y = df[ylabel]
     area = df['Census2019_18PlusPop'] / 1e6     #population in millions
+    
+    #To display date in interantional date format on the animation
 
+    IDF_date = date1 = datetime.strptime(month, '%m-%d-%Y').strftime('%Y-%m-%d')
+    
     fig, ax = plt.subplots()
     ax.set_xlabel("Percent of Population (+18) Considered Fully Vaccinated")
     ax.set_ylabel("Deaths per 100K")
     ax.set_xlim(0,100)
     ax.set_ylim(0,400) #[KR] changed from 500 limit to 400 limit
-    ax.set_title("Vaccine Effectiveness Snapshot as of: "+ month)
+    ax.set_title("Vaccine Effectiveness Snapshot as of: "+ IDF_date)
     fig.set_size_inches(8,6)
     ax.spines['top'].set_visible(False) #[MR] Removes top spine
     ax.spines['right'].set_visible(False) #[MR] Removes right spine