weight.py

from pandas import read_csv
from pandas import DataFrame
from pandas import Grouper
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

DATES_FASTED_ON = {"16/4/2020", "17/4/2020", "18/4/2020", "19/4/2020", "20/4/2020", "21/4/2020", "22/4/2020", "8/5/2020", "9/5/2020", "10/5/2020", 
"11/5/2020", "18/5/2020", "22/5/2020", "23/5/2020", "24/5/2020", "25/5/2020", "26/5/2020", "27/5/2020", "28/5/2020", "5/6/2020", "6/6/2020",}


plt.rcParams["figure.figsize"] = (60,15)
df = pd.read_csv("Daily Summaries.csv")
last_x_entries = 80
interpolate = True
pull_close = False

if pull_close:
  df = df[df["Average weight (kg)"].notnull()]

dates = df["Date"].tail(last_x_entries)
mins = df["Min weight (kg)"].tail(last_x_entries)
means = df["Average weight (kg)"].tail(last_x_entries)
maxs = df["Max weight (kg)"].tail(last_x_entries)

# Must be one of ['linear', 'time', 'index', 'values', 'nearest', 'zero', 
# 'slinear', 'quadratic', 'cubic', 'barycentric', 'polynomial', 'krogh', 
#'piecewise_polynomial', 'pchip', 'akima', 'spline', 'from_derivatives']
method='linear'
order=1

if interpolate:
  mins, means, maxs = mins.interpolate(method=method, order=order), means.interpolate(method=method, order=order), maxs.interpolate(method=method, order=order)

# Finding indexes of dates fasted on
def consecutive(data, stepsize=1):
    return np.split(np.array(data), np.where(np.diff(data) != stepsize)[0]+1)

fast_dates_indexes = sorted([np.where(dates == date)[0][0] for date in DATES_FASTED_ON])
fasting_sections = [(min(group), max(group)) for group in consecutive(fast_dates_indexes)]


fig, ax = plt.subplots()

# Highlight fasting indexes
for start_date_index, end_date_index in fasting_sections:
  if start_date_index == end_date_index:
    start_date_index -= 0.20
    end_date_index += 0.20
  ax.axvspan(start_date_index, end_date_index, alpha=0.2, color='lightgreen')


plt.plot(dates, mins, 'o-', color='g', label='Min')
plt.plot(dates, maxs, 'o-', color='r', label='Max')
plt.plot(dates, means, 'o-', color='b', label='Mean')
plt.fill_between(dates, mins, maxs, alpha=0.1)


plt.xlabel('Date')
plt.ylabel('Weight (kg)')
plt.savefig('weight.png')
plt.show()