def vals_interpol(file, encoding): bcdata = clean_data.new_bool_col(file, encoding) est_3 = bcdata.interpolate(method='values') est_3_miss = est_3[est_3['Miss Non Miss']==False] return est_3, est_3_miss
def index_interpol(file, encoding): bcdata = clean_data.new_bool_col(file, encoding) est_4 = bcdata.interpolate(method='index') est_4_miss = est_4[est_4['Miss Non Miss']==False] return est_4, est_4_miss
def nearest_interpol(file, encoding): bcdata = clean_data.new_bool_col(file, encoding) est_2 = bcdata.interpolate(method='nearest') est_2_miss = est_2[est_2['Miss Non Miss']==False] return est_2, est_2_miss
def lin_interpol(file, encoding): #Call the function that returns the bcdata with the added T/F boolean column bcdata = clean_data.new_bool_col(file, encoding) #Call the linear interpolate method of the bcdata frame est_1 = bcdata.interpolate(method='linear') #Captures only the rows with newly interpolated values est_1_miss = est_1[est_1['Miss Non Miss']==False] return est_1, est_1_miss