diff --git a/py_scripts/mining_hq.py b/py_scripts/mining_hq.py
index 0c628de..9ccbff3 100644
--- a/py_scripts/mining_hq.py
+++ b/py_scripts/mining_hq.py
@@ -1,6 +1,7 @@
 # Instantiating Main Python Script File
 # Collects stuff from the rest of the scripts
 import pandas as pd
+import scout
 import numpy as np
 import seaborn as sns
 import digger
@@ -24,9 +25,9 @@ games_merged_dat = digger.write_joined_df(games_sales, games_review_final)
 games_merged_dat.to_csv("datasets/videogames/games_merged.csv")
 
 # Loading Crime Datasets
-crime_CA = pd.read_excel('datasets/crime/clean_crime_canada_dataset.xlsx')
+crime_CA = pd.read_excel("datasets/crime/clean_crime_canada_dataset.xlsx")
 
-crime_US = pd.read_csv('datasets/crime/report.csv')
+crime_US = pd.read_csv("datasets/crime/report.csv")
 
 year_interval = gunner.year_interval(crime_US, crime_CA, "report_year", "year")
 
@@ -57,15 +58,19 @@ GLO_col_list = [
 # Collecting Split-Up Datasets
 games_merged_dat = gunner.drop_kick(NA_col_list, games_merged_dat)
 
-sale_tri_split = gunner.trisect_by_year(games_merged_dat, 'Year', year_interval)
+sale_tri_split = gunner.trisect_by_year(games_merged_dat, "Year", year_interval)
 
 # Displaying Acquired Data
 print("Acquired Datasets:\n")
-print(sale_tri_split[0].head(5),
-sale_tri_split[1].head(5),
-sale_tri_split[2].head(5))
+print(sale_tri_split[0].head(5), sale_tri_split[1].head(5), sale_tri_split[2].head(5))
 
 print("Dataset Info:\n")
 sale_tri_split[0].info()
 sale_tri_split[1].info()
 sale_tri_split[2].info()
+
+# Load merged gammas
+
+gammas = pd.read_csv("datasets/videogames/games_merged.csv")
+gammas["User_Score"] = scout.cure_depression(gammas, "User_Score")
+print(gammas["User_Score"])