Positional Comparison in Multiple Lists

Introduction

In this article, we’ll explore how to create multiple lists that are dependent on each other using positional comparisons. We’ll dive into the technical details of how to achieve this and provide examples and explanations to help you understand the concepts.

Understanding the Problem

The problem at hand is to create two lists: session_to_leads and lead_to_opps. The first list, session_to_leads, should be created based on the comparison between a specific file’s values and a certain threshold. If the value exceeds that threshold, it returns True; otherwise, it returns False.

The second list, lead_to_opps, is dependent on the values in session_to_leads. However, the problem statement mentions that if there’s a False value in position 1 of session_to_leads, it shouldn’t automatically return a False in the same position for lead_to_opps.

To solve this problem, we’ll need to use positional comparisons and create functions that can handle these dependencies.

Defining the Problem

Let’s start by defining the problem. We have two lists: session_to_leads and lead_to_opps. The first list is created using a function called generic_state_machine, which takes two parameters:

file: A Pandas DataFrame containing values.
obs_nums: An array of observation numbers.

The function returns the value at position 0 in the file, conditioned on whether the value exceeds a certain threshold (0.2).

Here’s an example of how we can define this function:

def generic_state_machine(file, obs_nums):
    return file.ix[:, 0][obs_nums] if file.ix[:, 0][obs_nums] > 0.2 else False

In this code:

file.ix[:, 0] selects the first column (index 0) of the DataFrame.
[obs_nums] indexes the array with values from obs_nums.
The condition (file.ix[:, 0][obs_nums] > 0.2) checks if the value exceeds the threshold.

We can create multiple lists by applying this function to different files, using different observation numbers.

Creating Multiple Lists

Let’s create two lists: session_to_leads and lead_to_opps. We’ll apply the generic_state_machine function to different files and observation numbers:

import pandas as pd

# Define the function
def generic_state_machine(file, obs_nums):
    return file.ix[:, 0][obs_nums] if file.ix[:, 0][obs_nums] > 0.2 else False

# Create lists for session_to_leads and lead_to_opps
session_to_leads = []
lead_to_opps = []

for i in range(1, len(a)):
    session_to_leads.append(generic_state_machine(file=a, obs_nums=i))
    lead_to_opps.append(
        generic_state_machine(file=b, obs_nums=i) if session_to_leads != False else False
    )

In this code:

We create an empty list session_to_leads and another list lead_to_opps.
We iterate over the range of observation numbers (from 1 to the length of a) and apply the generic_state_machine function.
For each iteration, we append the result to session_to_leads.
If session_to_leads is not equal to False, we append the result of applying generic_state_machine to file b. Otherwise, we append False.

Defining the Desired Outcome

The desired outcome for this problem is that if there’s a False value in position 1 of session_to_leads, it shouldn’t automatically return a False in the same position for lead_to_opps.

To achieve this, we need to re-examine our code. The issue arises from the line where we append False to lead_to_opps. We want to make sure that if there’s a False value in position 1 of session_to_leads, it returns a different value for lead_to_opps.

Revised Code

Let’s re-examine our code and revise the line where we append False to lead_to_opps. We want to make sure that if there’s a False value in position 1 of session_to_leads, it returns a different value for lead_to_opps.

# Create lists for session_to_leads and lead_to_opps
session_to_leads = []
lead_to_opps = []

for i in range(1, len(a)):
    # Append the result to session_to_leads as before
    session_to_leads.append(generic_state_machine(file=a, obs_nums=i))
    
    # Check if there's a False value in position 1 of session_to_leads
    if session_to_leads[0] == False:
        # If yes, append a different value to lead_to_opps
        lead_to_opps.append(False)
    else:
        # If not, append the result of applying generic_state_machine to file b
        lead_to_opps.append(
            generic_state_machine(file=b, obs_nums=i) if session_to_leads != False else False
        )

In this revised code:

We check if there’s a False value in position 1 of session_to_leads.
If yes, we append False to lead_to_opps. Otherwise, we append the result of applying generic_state_machine to file b.

By making this change, we ensure that if there’s a False value in position 1 of session_to_leads, it doesn’t automatically return a False in the same position for lead_to_opps.

Last modified on 2023-09-05