public-data-food-analysis-3 0.2.0

This project analyzes data from a few input sources.

Public data food analysis

Install

pip install public_data_food_analysis_3

For data analysis on the Columbia study

import public_data_food_analysis_3.columbia as pdfac
import pandas as pd

df = pdfac.make_table(pdfac.read_logging_data('data/col_test_data')\
                      , pd.read_excel('data/col_test_data/toy_data_17May2021.xlsx'))

df

	mCC_ID	Participant_Study_ID	Study Phase	Intervention group (TRE or HABIT)	Start_Day	End_day	Eating_Window_Start	Eating_Window_End	phase_duration	caloric_entries	...	logging_day_counts	%_logging_day_counts	good_logging_days	%_good_logging_days	good_window_days	%_good_window_days	outside_window_days	%_outside_window_days	adherent_days	%_adherent_days
0	yrt1999	2	S-REM	TRE	2021-05-12	2021-05-14	00:00:00	23:59:00	3 days	7	...	3	1.00	2	0.666667	3	1.00	0	0.0	2	0.666667
1	yrt1999	2	T3-INT	TRE	2021-05-15	2021-05-18	08:00:00	18:00:00	4 days	8	...	3	0.75	2	0.500000	1	0.25	2	0.5	1	0.250000

2 rows × 26 columns

df.iloc[0]

mCC_ID                                           yrt1999
Participant_Study_ID                                   2
Study Phase                                        S-REM
Intervention group (TRE or HABIT)                    TRE
Start_Day                            2021-05-12 00:00:00
End_day                              2021-05-14 00:00:00
Eating_Window_Start                             00:00:00
Eating_Window_End                               23:59:00
phase_duration                           3 days 00:00:00
caloric_entries                                        7
mean_daily_eating_window                           13.75
std_daily_eating_window                        11.986972
earliest_entry                                       4.5
2.5%                                              4.5375
97.5%                                            27.5625
duration mid 95%                                  23.025
logging_day_counts                                     3
%_logging_day_counts                                 1.0
good_logging_days                                      2
%_good_logging_days                             0.666667
good_window_days                                       3
%_good_window_days                                   1.0
outside_window_days                                    0
%_outside_window_days                                0.0
adherent_days                                          2
%_adherent_days                                 0.666667
Name: 0, dtype: object

df.iloc[1]

mCC_ID                                           yrt1999
Participant_Study_ID                                   2
Study Phase                                       T3-INT
Intervention group (TRE or HABIT)                    TRE
Start_Day                            2021-05-15 00:00:00
End_day                              2021-05-18 00:00:00
Eating_Window_Start                             08:00:00
Eating_Window_End                               18:00:00
phase_duration                           4 days 00:00:00
caloric_entries                                        8
mean_daily_eating_window                        8.666667
std_daily_eating_window                         8.504901
earliest_entry                                       7.5
2.5%                                                 7.7
97.5%                                               23.9
duration mid 95%                                    16.2
logging_day_counts                                     3
%_logging_day_counts                                0.75
good_logging_days                                      2
%_good_logging_days                                  0.5
good_window_days                                       1
%_good_window_days                                  0.25
outside_window_days                                    2
%_outside_window_days                                0.5
adherent_days                                          1
%_adherent_days                                     0.25
Name: 1, dtype: object