Mike/ParaUtils
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edeymc 2025-11-05 18:52:56 -08:00
parent 6d1ed90997
commit 47f891ef41
1 changed files with 11 additions and 4 deletions
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15
ParaUtils/__init__.py
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@ -1,4 +1,7 @@
#Bits and bobs used for many different projects. Junk drawer module #Bits and bobs used for many different projects. Junk drawer module
import pandas
import numpy
#Useful functions for parsing race-like durations, and normalizing their string reps #Useful functions for parsing race-like durations, and normalizing their string reps
def t2f(S): def t2f(S):
@ -6,7 +9,7 @@ def t2f(S):
return None return None
m,s = ('0:%s' % S).split(':')[-2:] m,s = ('0:%s' % S).split(':')[-2:]
try: try:
return np.round(60*int(m) + float(s),2) return numpy.round(60*int(m) + float(s),2)
except: except:
return -1 return -1
@ -21,7 +24,7 @@ def f2t(S):
return f'{m:02}:{s:02}.{round(hs*100):02}' return f'{m:02}:{s:02}.{round(hs*100):02}'
#Canada Summer Games eligible events #Canada Summer Games eligible events
CSG = pd.DataFrame([ CSG = pandas.DataFrame([
{'Stroke':'Butterfly','Distance':50,'SportClass':[1,2,3,4,5,6,7]}, {'Stroke':'Butterfly','Distance':50,'SportClass':[1,2,3,4,5,6,7]},
{'Stroke':'Butterfly','Distance':100,'SportClass':[8,9,10,11,12,13,14]}, {'Stroke':'Butterfly','Distance':100,'SportClass':[8,9,10,11,12,13,14]},
{'Stroke':'Backstroke','Distance':50,'SportClass':[1,2,3,4,5]}, {'Stroke':'Backstroke','Distance':50,'SportClass':[1,2,3,4,5]},
@ -37,7 +40,7 @@ CSG = pd.DataFrame([
]).explode('SportClass').reset_index(drop=True) ]).explode('SportClass').reset_index(drop=True)
def parse_WPS_rankings(DF): def parse_WPS_rankings(DF):
'''Takes a pandas datafram, usually loaded from an excel file, and cleans it up for use''' '''Takes a pandas dataframe, usually loaded from an excel file, and cleans it up for use'''
return ( return (
DF DF
#Makes .dot notation easier #Makes .dot notation easier
@ -57,4 +60,8 @@ def parse_WPS_rankings(DF):
#Drop excess columns #Drop excess columns
.pipe(lambda df: df['Gender SportClass Distance Stroke Result Seconds SDMS_ID NPC Given_Name Family_Name Date'.split()]) .pipe(lambda df: df['Gender SportClass Distance Stroke Result Seconds SDMS_ID NPC Given_Name Family_Name Date'.split()])
) )
__version__ = "0.1"