pandas python and probability Part 2

So I may have a really weird way going about figuring this stuff out.
I pound in code, break it tons of times and then keep googling until I find what I need to fix each break. 

I have a very strong feeling the test first crowd would be furious with me....

But,  here it goes.

I wanted to create a training set for my machine learning experiment.
This is the order in which I did that:
   1) create the pandas database
    pd.set_option('max_columns', 100)
   train_data = { 'run number': [0], #'run number:' as key produces NaN results
                'odd probability': [0.50],
                'even probability': [0.50],
                }
   train_prob_data = pd.DataFrame(train_data, columns = ['run number', 'odd      
                     probability', 'even probability'])
   2) create a list of random numbers
      

    def create_data():
        datalist = []
        for coin_toss in range(100):
            rand_num = randint(1, 20)
            datalist.append(rand_num)
        return datalist

  3)  make a recursive method to create a tuple list of odd probablities
       and even probabilities( this errored out as returning a NoneType because
       I was not 'returning' the function at the end of the else clause. I was just   
       running the method again instead)

  def get_prob_data(alist, count, even_count, odd_count, max_count, probs_list):
    """
    ((With alist = list of randomly chosen numbers))
    ((count first set to 0, then incremented each recursion))
    ((max_count being the length of alist - 1, ))
    ((probs_list = initially empty,  add probs for odd and even in tuple))
    ((return the probs_list))
    """

    if count >= max_count:
        return probs_list
    else:
        total = len(probs_list) + 2
        item = alist[count]
        if item % 2 == 0:
            new_total = total + 1
            even_count += 1
            count += 1
            add_even = round(even_count / new_total, 2)
            add_odd = round(1.00 - add_even, 2)
            probs_list.append((add_even, add_odd))

        elif item %2 != 0:
            new_total = total + 1
            odd_count += 1
            count += 1
            add_odd = round(odd_count / new_total, 2)
            add_even = round(1.00 - add_odd, 2)
            probs_list.append((add_even, add_odd))

        return get_prob_data(alist, count, even_count, odd_count, max_count, probs_list)

    4)  add these probabilites from the list returned from recursion to the pandas 
         database.

def add_probs(db, probs):
    """
    db = database to be appended
    probs = tuple list : [(even probability, odd probability)]
    """
    max_probs = len(probs) - 1
    for i in range(max_probs):
        data_evens = probs[i][0]
        data_odds = probs[i][1]
        #print(i, "\n", data_evens, data_odds)
        db = db.append({'run number': i, 'even probability': data_evens, 'odd probability': data_odds}, ignore_index=True)
        #db2 = db.append({'odd probability': data_odds}, ignore_index = True)
        ### NOOOO!!!frames = [db1, db2]
        ### NO !!!! db = pd.concat(frames)
        #print("===========>> for loop ======")
    return db 

I overloaded my command prompt at first.  I had the odd probabilities, and even probabilities in separate lists, and was trying to add them to the database separately with concat.  Not sure why in the world I thought I should put them in separate.  It froze on the 23rd loop trying to concat the two databases I was appending.  I learn a lot through breaking stuff. 
There are some helpful links in the whole code at the bottom.

5) A method to wrap it all together and send back the new database:

def create_panda_set(db):
    """
    Use create_data to return a list with 100 chosen 'random()' numbers
    use recursive get_prob_data to return a probability set for odd, and even
    numbers from create_data list.
    Create empty panda database, put the probabilities and count into
    the empty database.
    """
    alist = create_data()
    max_count = len(alist) - 1
    probs_list = []
    start_index = 0
    odd_count = 1
    even_count = 1
    #print(alist, max_count, odd_list, even_list)
    #x = get_prob_data(alist, start_index, max_count, odd_list, even_list)
    #print(x)
    probs_list = get_prob_data(alist, start_index, even_count, odd_count, max_count, probs_list)
    # add even list to training data:
    newdb = add_probs(db, probs_list)
    return newdb
 
6)  A lot of print statements, logging, trial and error, then ran for success:


def test_it():
    print(train_prob_data)
    new = create_panda_set(train_prob_data)
    print("^*^" * 10)
    #print(new)
    print(new.head())
    print(new.tail())

#create_panda_set()
test_it()


 Picture of final product:

######  The whole code ######


#  Machine learning experiment Part 2

import pandas as pd
from random import randint
import logging
import sys

##############  experiment part 2 ##############
# resources:
#           1) https://stackoverflow.com/questions/16597265/appending-to-an-empty-data-frame-in-pandas
#           2) https://docs.python.org/3/library/logging.html
#           3) https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.append.html
#           4) https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html
#           5) https://stackoverflow.com/questions/15819050/pandas-dataframe-concat-vs-append

# pandas data set up:
pd.set_option('max_columns', 100)
train_data = { 'run number': [0], #'run number:' as key produces NaN results
                'odd probability': [0.50],
                'even probability': [0.50],
                }
train_prob_data = pd.DataFrame(train_data, columns = ['run number', 'odd probability', 'even probability'])
# logger set up:
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
def create_data():
    datalist = []
    for coin_toss in range(100):
        rand_num = randint(1, 20)
        datalist.append(rand_num)
    return datalist

def get_prob_data(alist, count, even_count, odd_count, max_count, probs_list):    """
    ((With alist = list of randomly chosen numbers))
    ((count first set to 0, then incremented each recursion))
    ((max_count being the length of alist - 1, ))
    ((odd_prob = empty list on initial, then appended as calculated))
    ((even_pron = empty list on initial, then appended as calculated))
    ((return the count, odd_prob list, and even_prob list.))
    """

    if count >= max_count:
        # lots of prints, and logger here,
        # the effect of not 'returning' the get_prob_data()
        return probs_list
    else:
        total = len(probs_list) + 2
        item = alist[count]
        if item % 2 == 0:
            new_total = total + 1
            even_count += 1
            count += 1
            add_even = round(even_count / new_total, 2)
            add_odd = round(1.00 - add_even, 2)
            probs_list.append((add_even, add_odd))

        elif item %2 != 0:
            new_total = total + 1
            odd_count += 1
            count += 1
            add_odd = round(odd_count / new_total, 2)
            add_even = round(1.00 - add_odd, 2)
            probs_list.append((add_even, add_odd))

        return get_prob_data(alist, count, even_count, odd_count, max_count, probs_list)

#############  bad zoot ##############
        #event = 'recursion else clause: get_prob_data()\n alist len = %s\n oddlist len = %s\n, evenlist len= %s\n, current# = %s\n, max_count = %s'

        #length_alist = len(alist)
        #length_odd_prob = len(odd_prob)
        #length_even_prob = len(even_prob)
        #current_digit = item

        #logger.info(event, length_alist, length_odd_prob, length_even_prob, current_digit, max_count)
        #get_prob_data(alist, count, max_count, odd_prob, even_prob)
##########################################

def add_probs(db, probs):
    """
    db = database to be appended
    probs = tuple list : [(even probability, odd probability)]
    """
    max_probs = len(probs) - 1
    for i in range(max_probs):
        data_evens = probs[i][0]
        data_odds = probs[i][1]
        #print(i, "\n", data_evens, data_odds)
        db = db.append({'run number': i, 'even probability': data_evens, 'odd probability': data_odds}, ignore_index=True)
##########  bad zoot ###########
        #db1 = db.append({'even probability': data_evens}, ignore_index = True)
        #db2 = db.append({'odd probability': data_odds}, ignore_index = True)
        ### NOOOO!!!frames = [db1, db2]
        ### NO !!!! db = pd.concat(frames)
        #print("===========>> for loop ======")
########################
    return db



def create_panda_set(db):
    """
    Use create_data to return a list with 100 chosen 'random()' numbers
    use recursive get_prob_data to return a probability set for odd, and even
    numbers from create_data list.
    Create empty panda database, put the probabilities and count into
    the empty database.
    """
    alist = create_data()
    max_count = len(alist) - 1
    probs_list = []
    start_index = 0
    odd_count = 1
    even_count = 1
########  damn it Moon Moon! #######
    #print(alist, max_count, odd_list, even_list)
    #x = get_prob_data(alist, start_index, max_count, odd_list, even_list)
    #print(x)
#################
    probs_list = get_prob_data(alist, start_index, even_count, odd_count, max_count, probs_list)
    newdb = add_probs(db, probs_list)
    return newdb




def test_it():
    print(train_prob_data)
    new = create_panda_set(train_prob_data)
    print("^*^" * 10)
    #print(new)
    print(new.head())
    print(new.tail())


test_it()