Steps in 2024

steps2024.py

import pandas as pd
TARGET = 5_000_000
TARGET_RATE = TARGET / 366

data = [
        ('January', 31, 271_347),
        ('February', 29, 321_084),
        ('March', 31, 424_562),
        ('April', 30, 412_478),
        ('May', 31, 442_295),
        ('June', 30, 436_819),
        ('July', 31, 406_350),
        ('August', 31, 378_630),
        ('September', 7, 110_786),
]

data = pd.DataFrame(data, columns=['Month', 'Days', 'Steps'])

data['TotalSteps'] = data['Steps'].cumsum()
data['TotalDays'] = data['Days'].cumsum()
data['MonthRate'] = data.eval('(Steps/Days)/@TARGET_RATE')
data['Deficit'] = data.eval('TotalSteps - @TARGET_RATE * TotalDays').astype(int)
data['CummRate'] = data.eval('TotalSteps/TotalDays/@TARGET_RATE')
data['RelRate'] = data.eval('Steps/Days/( (@TARGET-TotalSteps+Steps)/(366-TotalDays+Days) )')
total_needed = TARGET - data['TotalSteps'].iloc[-1]
days_to_go = 366 - data['TotalDays'].iloc[-1]
rate_needed = total_needed / days_to_go

data.index = data.apply(lambda x: f"{x['Month']}" if x['Days'] > 28 else f"{x['Month']} ({x['Days']}d)", axis=1)
data = data.drop(columns=['Month', 'Days', 'TotalDays'])

data['Steps'] //= 100
data['Steps'] /= 10
data['Total steps (k)'] = data.eval('TotalSteps/1000').astype(int).map('{:,}'.format)
data['Deficit'] //= 1000
data.style.format("{:.1f}")

data.rename(columns=
          { 'Steps': 'Steps (k)',
           'Deficit': 'Deficit (k)',
           }, inplace=True)
data['Month rate'] = data['MonthRate'].map('{:.1%}'.format)
data['Cumm rate'] = data['CummRate'].map('{:.1%}'.format)
data['Rate needed'] = data['RelRate'].map('{:.1%}'.format)
pd.set_option('display.width', 120)

print(data[['Steps (k)', 'Total steps (k)', 'Deficit (k)', 'Month rate', 'Cumm rate', 'Rate needed']])
print(f'Deficit to catch up: {data["Deficit (k)"].iloc[-1]}k')
print(f'Rate per day needed for rest of year: {rate_needed:,.6}')

ENH Update step counts