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- import pandas as pd
- import numpy as np
- import datetime
- import json
- import os
- cols2drop = [ 'hasImages', 'maxLapAvgRunCadence', 'groupRideUUID', 'avgJumpRopeCadence',
- 'maxJumpRopeCadence', 'curatedCourseId', 'matchedCuratedCourseId',
- 'startzeit', 'moderateIntensityMinutes', 'vigorousIntensityMinutes',
- 'month', 'year' ]
- def mtb_table(df) :
- df = df.reset_index().drop('index', axis=1, errors='ignore')
- df['month'] = df['startTimeLocal'].dt.month
- df['year'] = df['startTimeLocal'].dt.year
- df['movingDuration'] = df['movingDuration'].map(lambda x: round(x/3600,2))
- df.drop( cols2drop , axis=1, inplace=True ) # drop unnecessary columns
- df = df.sort_values('startTimeLocal', ascending=[False])
- return df
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