Optimal difficulty for learning vs for motivation

Provisional analysis of FIDE data set to build difficulty-learning and difficulty-motivation curves

Tom Stafford, August 2016, t.stafford@shef.ac.uk @tomstafford


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import pandas as pd #data munging 
import numpy as np #number functions
import os #directory and file functions
import pylab as plt #graphing functions
import socket #machine id
import seaborn as sns
from matplotlib.font_manager import FontProperties

print "working directory = " + os.getcwd()

#----------------- load data"
gamedatloc='gamedat_tenpc.csv' #10% of the players in the full dataset

games=pd.read_csv(gamedatloc,index_col=0)
print "N games in data  = " + str(len(games)) #not all of these can be used because of missing data


working directory = /home/tom/Desktop/FIDEchess
N games in data  = 1180701

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