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.
# import all required packages
import pandas as pd
from sklearn.metrics import cohen_kappa_score
As part of the exploratory analysis, people were asked questions about the frequency and enjoyment of plan creation in general, and for walking specifically.
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