In [5]:

    

import pandas as pd
import glob
import os
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style("darkgrid")

import numpy as np
import re
import time
import datetime
import matplotlib.dates as mdates
from math import ceil

from collections import Counter


    

In [6]:

    

def extract_split_data(data):    
    content = re.findall("\[(.*?)\]", data)
   
    values = []
    for c in content[0].split(","):
        c = (c.strip()[1:-1])
        if len(c)>21:  
            x, y = c.split("#")
            values.append(int(x))
           
    return values


    

In [7]:

    

# begin/end/during: variance, slope,
sessionCount = 0
veryBeginning = []
nearEnd = []
duringGame = []

size = 6 # half

for url in glob.glob("/Users/xueguoliang/Desktop/tmp/*.csv"):
    
    player = pd.read_csv(url, delimiter=";")
    
    for session in player['GSR']:       
        rate = extract_split_data(session)
        
        if len(rate)>10:
            veryBeginning.append(rate[0:10])
            nearEnd.append(rate[-11:-1])
            if len(rate)%2 == 0:
                duringGame.append(rate[len(rate)//2-size+1:len(rate)//2+size-1])
            else:
                duringGame.append(rate[len(rate)//2-size+1:len(rate)//2+size-1])
                
        sessionCount += 1


    

In [8]:

    

print ("We have collected {} game sessions.".format(sessionCount))


    

    




We have collected 214 game sessions.

In [14]:

    

fig, ax = plt.subplots(3, 2, figsize=(15,15))
labels = ["Postive", "Negative"]

########################################## Begin ##################################################

std_begin = []
slope_begin = []
for item in veryBeginning:
    slope_begin.append((item[-1]-item[0])/(len(item)-1))
    std_begin.append(round(np.std(item), 2))
    
begin_pos = sum([1 for x in slope_begin if x > 0])
begin_nag = sum([1 for x in slope_begin if x < 0])
dict_begin = {1:begin_pos, 2:begin_nag}

ax[0][0].set_title("Distribution of STD for Beginning of game")
ax[0][0].hist(std_begin, bins=50, range=(min(std_begin), max(std_begin)))
ax[0][0].set_xlim([0,100])

ax[0][1].set_title("Distribution of Slope(+,-) for Beginning of game")
ax[0][1].bar(range(len(dict_begin)), dict_begin.values(), color='g')

ax[0][1].set_xticklabels(("","","Positive","","","", "Negative"))

########################################## During #################################################

std_during = []
slope_during = []    
for item in duringGame:
    slope_during.append((item[-1]-item[0])/(len(item)-1))
    std_during.append(round(np.std(item), 2))

during_pos = sum([1 for x in slope_during if x > 0])
during_nag = sum([1 for x in slope_during if x < 0])
dict_during = {1:during_pos, 2:during_nag}

ax[1][0].set_title("Distribution of STD for During of game")
ax[1][0].hist(std_during, bins=50, range=(min(std_during), max(std_during)))
ax[1][0].set_xlim([0,300])

ax[1][1].set_title("Distribution of Slope(+,-) for Beginning of game")
ax[1][1].bar(list(dict_during.keys()), dict_during.values(), color='g')

ax[1][1].set_xticklabels(("","","Positive","","","", "Negative"))


########################################## End ###################################################
    
std_end = []
slope_end = []
for item in nearEnd:
    slope_end.append((item[-1]-item[0])/(len(item)-1))
    std_end.append(round(np.std(item), 2))
    
end_pos = sum([1 for x in slope_end if x > 0])
end_nag = sum([1 for x in slope_end if x < 0])
dict_end = {1:end_pos, 2:end_nag}

ax[2][0].set_title("Distribution of STD for End of game")
ax[2][0].hist(std_end, bins=50, range=(min(std_end), max(std_end)))
ax[2][0].set_xlim([0,100])

ax[2][1].set_title("Distribution of Slope(+,-) for End of game")
ax[2][1].bar(list(dict_end.keys()), dict_end.values(), color='g')

ax[2][1].set_xticklabels(("","","Positive","","","", "Negative"))
#plt.xlim([0,100])
plt.show()