Count_and_plot-MLSsalarydata2019

Data source: MLS Players Association. 
  （http://s3.amazonaws.com/mlspa/June-1-2019-Salaries-Alphabetical-Web.pdf?mtime=20190612135339）
  
  #count numbers of players in each club and each position
  #plot

import matplotlib.pyplot as plt
import pandas as pd

MLS2019_df = pd.read_csv('MLS_s_2019.csv')
def MLS2019(df,*args):
  count={}
  for col_name in args:
    col = df[col_names]
    for entry in col:
      if entry in count.keys():
        count[entry] += 1
      else:
        count[entey] = 1
  return count

club = MLS2019(MLS2019_df, 'Company')
position = MLS2019(MLS2019_df, 'Position(s)')

clubs = [[k,v] for k,v in club.items()]
x,y = zip(*clubs)
plt.polt(x,y)
plt.show()

positions = [[k,v] for k,v in position.items()]
x1,y1 = zip(*positions)
plt.plot(x1,y1)
plt.show()

##end