def get_df():
df_getter = EffortDfGetter(origin='json')
return df_getter.get()
import time
import eda_fuctions
from strava_db import EffortDfGetter
if __name__ == '__main__':
t = time.time()
df_getter = EffortDfGetter(origin='mongo')
df = df_getter.get(300000)
print 'Retrieved dataframe with {} efforts in {:.2f} seconds'.format(df.shape[0], time.time()-t)
# Random mongo searches for stats
# Number of athletes with > 5 efforts
'''
db.segment_efforts.aggregate( [
{
$group: {
_id: '$athlete.id',
total_eff: { $sum: 1 }
}
},
{
$match: {
total_eff: { $gt: 5 }
}
},
{
$group: {
_id: '$_id.total_eff',
def get_df():
df_getter = EffortDfGetter(origin='json')
return df_getter.get()
import time
import eda_functions
from strava_db import EffortDfGetter
if __name__ == '__main__':
t = time.time()
df_getter = EffortDfGetter(origin='json')
df = df_getter.get()
print 'Retrieved dataframe with {} efforts in {:.2f} seconds'.format(df.shape[0], time.time()-t)
