diff --git a/data analysis/__pycache__/superscript.cpython-37.pyc b/data analysis/__pycache__/superscript.cpython-37.pyc
new file mode 100644
index 00000000..8cb176ff
Binary files /dev/null and b/data analysis/__pycache__/superscript.cpython-37.pyc differ
diff --git a/data analysis/superscript.py b/data analysis/superscript.py
index 0c98034a..f2c45db3 100644
--- a/data analysis/superscript.py	
+++ b/data analysis/superscript.py	
@@ -1,11 +1,13 @@
-#Titan Robotics Team 2022: Data Analysis Script
+#Titan Robotics Team 2022: Super Script
 #Written by Arthur Lu & Jacob Levine
 #Notes:
 #setup:
 
-__version__ = "1.0.4.000"
+__version__ = "1.0.4.001"
 
 __changelog__ = """changelog:
+1.0.4.001:
+    - grammar fixes
 1.0.4.000:
     - actually pushes to firebase
 1.0.3.001:
@@ -37,82 +39,84 @@ import os
 import glob
 import numpy as np
 
-# Use a service account
-cred = credentials.Certificate('keys/firebasekey.json')
-firebase_admin.initialize_app(cred)
+def titanservice():
+    
+    # Use a service account
+    cred = credentials.Certificate('keys/firebasekey.json')
+    firebase_admin.initialize_app(cred)
 
-db = firestore.client()
+    db = firestore.client()
 
-#get all the data
+    #get all the data
 
-analysis.generate_data("data/bdata.csv", 100, 5, -10, 10)
+    analysis.generate_data("data/bdata.csv", 100, 5, -10, 10)
 
-source_dir = 'data'
-file_list = glob.glob(source_dir + '/*.csv') #supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
-data = []
-files = [fn for fn in glob.glob('data/*.csv') 
-         if not os.path.basename(fn).startswith('teams')]
+    source_dir = 'data'
+    file_list = glob.glob(source_dir + '/*.csv') #supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
+    data = []
+    files = [fn for fn in glob.glob('data/*.csv') 
+             if not os.path.basename(fn).startswith('teams')]
 
-#for file_path in file_list:
-#	if not os.path.basename(file_list).startswith("teams")
-#		data.append(analysis.load_csv(file_path))
+    #for file_path in file_list:
+    #	if not os.path.basename(file_list).startswith("teams")
+    #		data.append(analysis.load_csv(file_path))
 
-for i in files:
-	data.append(analysis.load_csv(i))
+    for i in files:
+            data.append(analysis.load_csv(i))
 
-stats = []
-measure_stats = []
-teams = analysis.load_csv("data/teams.csv")
+    stats = []
+    measure_stats = []
+    teams = analysis.load_csv("data/teams.csv")
 
-#assumes that team number is in the first column, and that the order of teams is the same across all files
-#unhelpful comment
-for measure in data: #unpacks 3d array into 2ds
+    #assumes that team number is in the first column, and that the order of teams is the same across all files
+    #unhelpful comment
+    for measure in data: #unpacks 3d array into 2ds
 
-	measure_stats = []
+            measure_stats = []
 
-	for i in range(len(measure)): #unpacks into specific teams
+            for i in range(len(measure)): #unpacks into specific teams
 
-		ofbest_curve = [None]
-		r2best_curve = [None]
+                    ofbest_curve = [None]
+                    r2best_curve = [None]
 
-		line = measure[i]
+                    line = measure[i]
 
-		#print(line)
+                    #print(line)
 
-		x = list(range(len(line)))
-		eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
+                    x = list(range(len(line)))
+                    eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
 
-		beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
+                    beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
 
-		#print(eqs, rmss, r2s, overfit)
-		
-		ofbest_curve.append(beqs)
-		ofbest_curve.append(brmss)
-		ofbest_curve.append(br2s)
-		ofbest_curve.append(boverfit)
-		ofbest_curve.pop(0)
+                    #print(eqs, rmss, r2s, overfit)
+                    
+                    ofbest_curve.append(beqs)
+                    ofbest_curve.append(brmss)
+                    ofbest_curve.append(br2s)
+                    ofbest_curve.append(boverfit)
+                    ofbest_curve.pop(0)
 
-		#print(ofbest_curve)
+                    #print(ofbest_curve)
 
-		beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
+                    beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
 
-		r2best_curve.append(beqs)
-		r2best_curve.append(brmss)
-		r2best_curve.append(br2s)
-		r2best_curve.append(boverfit)
-		r2best_curve.pop(0)
+                    r2best_curve.append(beqs)
+                    r2best_curve.append(brmss)
+                    r2best_curve.append(br2s)
+                    r2best_curve.append(boverfit)
+                    r2best_curve.pop(0)
 
-		#print(r2best_curve)
-		
-		measure_stats.append(teams[i] + ["|"] +  list(analysis.basic_stats(line, 0, 0)) + ["|"] + list(analysis.histo_analysis(line, 1, -3, 3)) + ["|"] + ofbest_curve + ["|"] + r2best_curve)
+                    #print(r2best_curve)
+                    
+                    measure_stats.append(teams[i] + ["|"] +  list(analysis.basic_stats(line, 0, 0)) + ["|"] + list(analysis.histo_analysis(line, 1, -3, 3)) + ["|"] + ofbest_curve + ["|"] + r2best_curve)
 
-	stats.append(list(measure_stats))
-	
-json_out = {}
-		
-for i in range(len(stats)):
-        json_out[files[i]]=str(stats[i])
+            stats.append(list(measure_stats))
+            
+    json_out = {}
+                    
+    for i in range(len(stats)):
+            json_out[files[i]]=str(stats[i])
 
-print(json_out)
+    print(json_out)
 
-db.collection(u'stats').document(u'stats-noNN').set(json_out)
+    db.collection(u'stats').document(u'stats-noNN').set(json_out)