acessing dataframe columns using dot notation with namedtuple. Typing var_df2. in jupyter lab will show column names to select as dropdown

data frame column names auto complete

from collections import namedtuple
import re
#str1, n = re.subn('[0-9]', 'X',str1)
def ntuples(df):
    list_of_names = df.columns.values
    print(list_of_names[0:2])
    list_of_names_dict = {x:x for x in list_of_names}

    Varnames = namedtuple('Varnames', list_of_names) 
    return Varnames(**list_of_names_dict)

def change_to_valid_column_names(df3):
    df3.columns=[(re.sub("[/' ()-]","_",x)) for x in df3.columns.to_list()] #replace invalid char with _
    df3.columns=[(re.sub("_+","_",x)) for x in df3.columns.to_list()] #replace 1 or more _ with single _ to compact
    # + is quantifier for 1 or more https://cheatography.com/davechild/cheat-sheets/regular-expressions/
    df3.columns=[x.replace("_","n",1) for x in df3.columns.to_list()] #cant start with underscore so change first underscore
    return (df3)

def abbreviate_names(df):
    my_ab={'Phase Noise':'PN','Phase_Noise':'PN','Phase_Noise_at':'PN',
       'Frequency':'Freq','FREQUENCY':'Freq',"Power":"Pwr",
       'Temperature':'Tmpr',
           "Carrier":"Carr",
           "Converter":"Conv",
           "TEMP_SENSOR":"TS",
           "Measured":"Meas",
           "Measurement":"Meas"
        
      }
    for word  in my_ab:
        df2.columns=[x.replace(word,my_ab[word]) for x in df2.columns.to_list()] #list comprehension to substiture abbreviations in names
    return (df)

df2=change_to_valid_column_names(df2)
df2=abbreviate_names(df2)

var_df2= ntuples(df2) # get a named tuple from columns of dataframe for autofill butfirst convert to valid names