In [1]:
import pandas as pd
import re
In [2]:
mtdata = pd.read_csv('mousetrackercorrected.csv')
In [3]:
includelist = pd.read_csv('n=452 subjectID.csv', header = None)
includelist = includelist[0].values
In [4]:
mtdata.loc[mtdata['subject'].isin(includelist)]
Out[4]:
In [5]:
mtdata['RESPONSE1'] = [x for x in mtdata['resp_1'].str.extract(r'..(\d*)_.(\d*)', expand = True).values]
mtdata['RESPONSE2'] = [x for x in mtdata['resp_2'].str.extract(r'..(\d*)_.(\d*)', expand = True).values]
In [6]:
mtdata.head()
Out[6]:
if error == 0, then selfish, and that's response 1? if 1 then altruistic
ERROR 0 REPSPONSE 0 ERROR 1 RESPONSE 0 ERROR 0 RESPONSE 1 ERROR 1 RESPONSE 1
In [7]:
tempdata = pd.DataFrame(columns = ('RESPONSE','ERROR','RESPONSE1','RESPONSE2'))
tempdata['RESPONSE'] = mtdata['response']
tempdata['ERROR'] = mtdata['error']
tempdata['RESPONSE1'] = mtdata['RESPONSE1']
tempdata['RESPONSE2'] = mtdata['RESPONSE2']
tempdata['SELFISHCHOICESELFMORE'] = 0
tempdata['SELFISHCHOICEGROUPMORE'] = 0
In [8]:
tempdata.head()
Out[8]:
In [9]:
SELFISHCHOICESELFMORE = []
SELFISHCHOICEGROUPMORE = []
for row in tempdata.iterrows():
if (row[1][0] == 1) & (row[1][1] == 0) | ((row[1][0] == 2) & (row[1][1] == 1)):
try:
SELFISHCHOICESELFMORE.append(int(row[1][2][0]) - int(row[1][3][0]))
SELFISHCHOICEGROUPMORE.append((int(row[1][2][0]) + int(row[1][2][1])) - (int(row[1][3][0]) + int(row[1][3][1])))
except:
SELFISHCHOICESELFMORE.append(None)
SELFISHCHOICEGROUPMORE.append(None)
elif ((row[1][0] == 2) & (row[1][1] == 0)) | ((row[1][0] == 1) & (row[1][1] == 1)):
try:
SELFISHCHOICESELFMORE.append(int(row[1][3][0]) - int(row[1][2][0]))
SELFISHCHOICEGROUPMORE.append((int(row[1][3][0]) + int(row[1][3][1])) - (int(row[1][2][0]) + int(row[1][2][1])))
except:
SELFISHCHOICESELFMORE.append(None)
SELFISHCHOICEGROUPMORE.append(None)
In [10]:
tempdata = tempdata.drop(['RESPONSE1','RESPONSE2', 'RESPONSE', 'ERROR'], axis = 1)
tempdata['SELFISHCHOICESELFMORE'] = SELFISHCHOICESELFMORE
tempdata['SELFISHCHOICEGROUPMORE'] = SELFISHCHOICEGROUPMORE
In [11]:
outdata = pd.concat([mtdata,tempdata], axis = 1)
In [13]:
outdata.to_csv('mousetrackercorrected9.16.2016.csv')