diff --git a/python/data science/fbPercentActive.py b/python/data science/fbPercentActive.py
index 1306819..3b7ca94 100644
--- a/python/data science/fbPercentActive.py	
+++ b/python/data science/fbPercentActive.py	
@@ -19,14 +19,14 @@ data = []
 def population(country):
 	countryCode = pycountry.countries.search_fuzzy(country)[0].alpha_3
 	res = requests.get('https://restcountries.eu/rest/v2/alpha/' + countryCode)
-	return json.loads(res.content)['population']
+	return int(json.loads(res.content)['population'])
 
 for td1, td2 in zip(tds[::2], tds[1::2]):
 	frame = {}
 	frame['country'] = td1.text.strip()
-	frame['active'] = td2.text.strip()
+	frame['active'] = int(td2.text.strip()) * 1000000
 	frame['population'] = population(frame['country'])
-	frame['percentActive'] = (int(frame['active']) * 1000000 / int(frame['population'])) * 100
+	frame['percentActive'] = (frame['active'] / frame['population']) * 100
 	data.append(frame)
 
 # Save the data
diff --git a/python/data science/fbPercentActive_res.csv b/python/data science/fbPercentActive_res.csv
index 2045ed0..a1e6aa2 100644
--- a/python/data science/fbPercentActive_res.csv	
+++ b/python/data science/fbPercentActive_res.csv	
@@ -1,21 +1,21 @@
 ,country,active,population,percentActive
-0,India,340,1295210000,26.250569405733433
-1,United States,200,323947000,61.738494259863494
-2,Indonesia,140,258705000,54.11569161786591
-3,Brazil,130,206135893,63.065193600223715
-4,Mexico,98,122273473,80.14821007006155
-5,Philippines,88,103279800,85.20543223360231
-6,Vietnam,71,92700000,76.59115426105717
-7,Thailand,54,65327652,82.6602492922905
-8,Egypt,47,91290000,51.484280863183265
-9,Bangladesh,46,161006790,28.570223653300587
-10,Pakistan,45,194125062,23.18093271233572
-11,Colombia,38,48759958,77.93279887566761
-12,United Kingdom,38,65110000,58.36277069574566
-13,Turkey,37,78741053,46.98946558410896
-14,France,33,66710000,49.46784590016489
-15,Argentina,31,43590400,71.11657612685362
-16,Italy,31,60665551,51.099840830589336
-17,Nigeria,31,186988000,16.578603974586603
-18,Germany,28,81770900,34.24201029950753
-19,Peru,27,31488700,85.74504504790607
+0,India,340000000,1295210000,26.250569405733433
+1,United States,200000000,323947000,61.738494259863494
+2,Indonesia,140000000,258705000,54.11569161786591
+3,Brazil,130000000,206135893,63.065193600223715
+4,Mexico,98000000,122273473,80.14821007006155
+5,Philippines,88000000,103279800,85.20543223360231
+6,Vietnam,71000000,92700000,76.59115426105717
+7,Thailand,54000000,65327652,82.6602492922905
+8,Egypt,47000000,91290000,51.484280863183265
+9,Bangladesh,46000000,161006790,28.570223653300587
+10,Pakistan,45000000,194125062,23.18093271233572
+11,Colombia,38000000,48759958,77.93279887566761
+12,United Kingdom,38000000,65110000,58.36277069574566
+13,Turkey,37000000,78741053,46.98946558410896
+14,France,33000000,66710000,49.46784590016489
+15,Argentina,31000000,43590400,71.11657612685362
+16,Italy,31000000,60665551,51.099840830589336
+17,Nigeria,31000000,186988000,16.578603974586603
+18,Germany,28000000,81770900,34.24201029950753
+19,Peru,27000000,31488700,85.74504504790607