Its V3 actually, Updated Data Points... Better Data..

Code Updated,
Better Model,
Implemeted Using Random Forest Model Highest accuracy...
Traing took more than 1hr

AQI.py → AQI_Ploter.py

@@ -9,37 +9,28 @@
 # generic doesnot work
 # feture_extraction_combine.pt line 70: getattribuute error
 def avg_data(year):
-    temp_i=0
     average=[]
     location = "Data/air_quality_data/air_quality_data" + str(year) + ".csv"
-    for rows in pd.read_csv(location,chunksize=24):
-        add_var=0
+    df = pd.read_csv(location)
+    for val in df['pm25']:
         avg=0.0
-        data=[]
-        df=pd.DataFrame(data=rows)
-        for index,row in df.iterrows():
-            data.append(row['PM2.5'])
-        for i in data:
-            if type(i) is float or type(i) is int:
-                add_var=add_var+i
-            elif type(i) is str:
-                if i!='NoData' and i!='PwrFail' and i!='---' and i!='InVld':
-                    temp=float(i)
-                    add_var=add_var+temp
-        avg=add_var/24
-        temp_i=temp_i+1
-
+        if type(val) is float or type(val) is int:
+            avg = avg + val
+        elif type(val) is str:
+            if val!='' and val!='NoData' and val!='PwrFail' and val!='---' and val!='InVld':
+                temp=float(val)
+                avg = avg + temp
         average.append(avg)
     return average
 
 
 if __name__=="__main__":
-    year_days = {2013:365, 2014:364, 2015:365}
-    for year in range(2013,2016):
+    year_days = { 2014 : 365, 2015 : 365, 2016 : 366, 2017 : 365, 2018 : 365, 2019 : 365, 2020 : 366, 2021 : 365, 2022 : 273 }
+    for year in range(2014,2017):
         plot_year = avg_data(year)
         lable_data = str(year) + " data"
         plt.plot(range(0,year_days[year]),plot_year,label=lable_data)
-    plt.xlabel('Day')
-    plt.ylabel('PM 2.5')
-    plt.legend(loc='upper right')
+        plt.xlabel('Day')
+        plt.ylabel('PM 2.5')
+        plt.legend(loc='upper right')
     plt.show()