def csvopen(csv, **kwargs):
try:
f = csv.open(csv.path, encoding=csv.encoding, **kwargs)
except (TypeError, ValueError): # TypeError for py2 ValueError for py3
f = csv.open(csv.path, **kwargs)
yield f
try:
f.close()
except AttributeError:
pass
def csvopen(csv, **kwargs):
try:
f = csv.open(csv.path, encoding=csv.encoding, **kwargs)
except (TypeError, ValueError): # TypeError for py2 ValueError for py3
f = csv.open(csv.path, **kwargs)
yield f
try:
f.close()
except AttributeError:
pass
def sample_csv(csv, length=8192, **kwargs):
if csv.path is None or not os.path.exists(csv.path):
mgr = NamedTemporaryFile(suffix='.csv', mode='wb+')
else:
mgr = csv.open(mode='rb')
with mgr as f:
with tmpfile(csv.canonical_extension) as fn:
with open(fn, mode='wb') as tmpf:
tmpf.write(f.read(length))
yield fn
def sample_csv(csv, length=8192, **kwargs):
if csv.path is None or not os.path.exists(csv.path):
mgr = NamedTemporaryFile(suffix='.csv', mode='wb+')
else:
mgr = csv.open(mode='rb')
with mgr as f:
with tmpfile(csv.canonical_extension) as fn:
with open(fn, mode='wb') as tmpf:
tmpf.write(f.read(length))
yield fn
def get_sample(csv, size=16384):
if os.path.exists(csv.path) and csv.mode != 'w':
f = csv.open(csv.path)
try:
return f.read(size)
finally:
try:
f.close()
except AttributeError:
pass
return ''
def generate_activities_from_data(filename, delimiter, n, exponent, a, b, nu,
epsilon):
activities = dict()
with csv.open(filename, delimiter=delimiter) as contactList:
for contactData in contactList:
t = contactData[0]
i = contactData[1]
j = contactData[2]
try:
# increment the degree assuming undirected
activities[t][i, j] += 1
activities[t][j] += 1
except:
activities[t] = np.zeros(n)
activities[t][i] = 1
activities[t][j] = 1
return activities # or should it be the average
import csv, itertools, json
def cluster(rows):
result = []
for key, group in itertools.groupby(rows, key=lambda r: r[0]):
group_rows = [row[1:] for row in group]
if len(group_rows[0]) == 2:
result.append({key: dict(group_rows)})
else:
result.append({key: cluster(group_rows)})
return result
if __name__ == '__main__':
s = '''\
Gondwanaland,Bobs Bits,Operations,nuts,332
Gondwanaland,Bobs Bits,Operations,bolts,254
Gondwanaland,Maureens Melons,Operations,nuts,123
'''
rows = list(csv.open('county_state.csv'))
r = cluster(rows)
print json.dumps(r, indent=4)
stadanrdDust_patch,
averagePoint,
meanPoint,
medianPoint
],
bbox_to_anchor=(1.05, 0.95),
loc=2,
borderaxespad=0.)
# eventually return what we have done
return ax
# this is the main script, note that we have imported pyplot as plt
rangedata = {}
f = csv.open('csvData_withDavidTags.csv', 'rb', encoding='utf-8')
reader = csv.reader(f)
for row in reader:
i = row
Name = str(i[0])
Low_min = float(i[2])
Low_max = float(i[4])
Low_Average = float(i[3])
Max_min = 0
Max_max = 0
Max_Average = 0
Top_min = 0
Top_max = 0
Top_Average = 0
Max = float(i[1])
Method = str(i[11])