Planning habits and enjoyment analysis¶

Author: Andrei Stefan
Date: 09-11-2023
Required files: data/anonymised_data/anonymised_data_prescreening.csv
Output files: no output files

This file contains the code to reproduce the results about how often people plan and how much they enjoy it. This is part of Table 4.1.

In [1]:
# import all required packages
import pandas as pd

from sklearn.metrics import cohen_kappa_score

Frequency of enjoyment of creating plans, Table 4.1¶

As part of the exploratory analysis, people were asked questions about the frequency and enjoyment of plan creation in general, and for walking specifically.

In [2]:
def demographic():
    """
    Function to print the demographic data, number of participants and samples, and number of people who finished the post-questionnaire.
    
    Args: none
    Returns: none.
    """
    
    # get the prescreening data into another dataframe
    df_prescreening = pd.read_csv("../../../data/anonymised_data/anonymised_data_prescreening.csv")
    
    # calculate the necessary demographic details
    print("Average number of plans in general", df_prescreening.loc[:, 'Number of plans general'].mean())
    print("Average number of plans for walking", df_prescreening.loc[:, 'Number of plans for walking'].mean())
    print()
    print("Feeling about creating plans in general", df_prescreening.loc[:, 'Feeling about creating plans in general'].mean())
    print("Feeling about creating plans for walks", df_prescreening.loc[:, 'Feeling about creating plans for walks'].mean())
    
demographic()
Average number of plans in general 7.307017543859649
Average number of plans for walking 2.3508771929824563

Feeling about creating plans in general 2.745614035087719
Feeling about creating plans for walks 1.456140350877193