from utils import find_in_vardict l = Loader() # l.load("limestone_2020.csv", "limestone") # l.load("iron.csv", "iron") # l.load("iron.csv", "iron2") l.load("MBSComtrade.csv", "mbs") # print(l.vardict.var_dict) c = Cleaner(l.vardict) #c.remove_null("limestone") #c.mapper("limestone", "Year", {2020:"This_year"}, new_var=True, new_var_name="this_var") #c.joiner("limestone", "iron") # print(c.vardict.show_data("limestone")) c.fill_backward("mbs") #c.merger(["limestone", "iron", "iron2"], new_var=True, new_var_name="merged") p = Processor(c.vardict) #p.normalize("mbs","trade_flow_desc", new_var=True, new_var_name="mbs_scaled") p.onehotencoder("mbs", "trade_flow_desc", new_var=True, new_var_name="mbs_encoded") print(p.vardict.show_data("mbs_encoded")) #print(p.vardict.show_data("merged")) # df = find_in_vardict(c.vardict, 'limestone') # df = df['data'] # df_nan = df["Netweight (kg)"].isnull()