Imports

ParaUtils/__init__.py

@@ -1,4 +1,7 @@
 #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
 def t2f(S):
@@ -6,7 +9,7 @@ def t2f(S):
         return None
     m,s = ('0:%s' % S).split(':')[-2:]
     try:
-        return np.round(60*int(m) + float(s),2)
+        return numpy.round(60*int(m) + float(s),2)
     except:
         return -1
 
@@ -21,7 +24,7 @@ def f2t(S):
     return f'{m:02}:{s:02}.{round(hs*100):02}'
 
 #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':100,'SportClass':[8,9,10,11,12,13,14]},
     {'Stroke':'Backstroke','Distance':50,'SportClass':[1,2,3,4,5]},
@@ -37,7 +40,7 @@ CSG = pd.DataFrame([
 ]).explode('SportClass').reset_index(drop=True)
 
 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 (
         DF
         #Makes .dot notation easier
@@ -58,3 +61,7 @@ def parse_WPS_rankings(DF):
         #Drop excess columns
         .pipe(lambda df: df['Gender SportClass Distance Stroke Result Seconds SDMS_ID NPC Given_Name Family_Name Date'.split()])
     )
+
+
+
+__version__ = "0.1"