from HowManyMedals import howManyMedals
from FileLoader import FileLoader
loader = FileLoader()
data = loader.load('../resources/athlete_events.csv')
dico = howManyMedals(data, 'Usain St. Leo Bolt')
print(dico)
print()
dico = howManyMedals(data, 'Kjetil Andr Aamodt')
print(dico)
from FileLoader import FileLoader as loader
from HowManyMedals import howManyMedals
df = loader.load('../data/athlete_events.csv')
md = howManyMedals(df, 'Kjetil Andr Aamodt')
print(md)
#!/usr/bin/env python3
from FileLoader import FileLoader
from HowManyMedals import howManyMedals
loader = FileLoader()
data = loader.load('../resources/athlete_events.csv')
print(howManyMedals(data, 'Kjetil Andr Aamodt'))
import os
import pandas as pd
from HowManyMedals import howManyMedals
class FileLoader:
def load(path): #The argument of this method is the file path of the dataset to load. It must display a message specifying the dimensions of the dataset (e.g. 340 x 500). The method returns the dataset loaded as a pandas.DataFrame.
i = len(path) - 1
while path[i] != '.':
i -= 1
extension = path[i:len(path)]
if extension == ".txt":
file = pd.read_txt(path)
if extension == ".csv":
file = pd.read_csv(path)
print("Loading dataset of dimensions %d x %d" % (file.shape[0], file.shape[1]))
return file
def display(df, n): #Takes a pandas.DataFrame and an integer as arguments. This method displays the first n rows of the dataset if n is positive, or the last n rows if n is negative.
if n >= 0:
print(df.iloc[0:n])
else:
print(df.iloc[n - 1:-1])
pan = FileLoader
file = pan.load(os.getcwd() + "/../resources/athlete_events.csv")
print(howManyMedals(file, "Piotr ya"))