better preprocessing

better_preprocess.py

@@ -0,0 +1,24 @@
+import pandas as pd
+import numpy as np
+
+df=pd.read_csv("25k_IMDb_movie_Dataset.csv")
+df=df.drop(columns=['Run Time'])
+df['Rating']=df['Rating'].str.replace("no-rating","0")
+df['Rating']=pd.to_numeric(df['Rating'])
+df['User Rating']=df['User Rating'].str.replace("K","000")
+df['User Rating']=df['User Rating'].str.replace("M","000000")
+df['User Rating']=pd.to_numeric(df['User Rating'])
+df=df.drop("path",axis=1)
+df['year']=df['year'].str.replace("-","")
+
+mumbojumbo=["(",")","I","V"," ","X"]
+for a in mumbojumbo:
+    df['year']=df['year'].str.replace(a,"")
+
+df['year']=np.where(df['year']=="","1900",df['year'])
+df['year']=df['year'].fillna("1900")
+df['year']=df['year']+"-01-01"
+df['year']=pd.to_datetime(df['year'])
+
+
+df.to_csv("data.csv")