def tab_print(table_name2, status):
print table_name2
import glob
tables = glob.glob('./tables/*.csv')
table_name=table_name2.split(',')
print table_name
if status==False:
for i in tables:
if table_name[0] in i.replace('./tables/','').replace('.csv',''):
from prettytable import from_csv
fp = open("./tables/"+table_name[0]+".csv", "r")
customer = from_csv(fp)
fp.close()
text2.delete('1.0', END) #For delete the text from input box
#text2.insert(INSERT, '\n\n')
text2.insert(INSERT,customer)
elif status==True:
cross_prod(table_name2)
from prettytable import from_csv
fp = open("./tables/tmp.csv", "r")
customer = from_csv(fp)
fp.close()
text2.delete('1.0', END) #For delete the text from input box
#text2.insert(INSERT, '\n\n')
text2.insert(INSERT,customer)
def makeTABLE(csvFileName):
with open(csvFileName, 'r') as csv_file:
print prettytable.from_csv(csv_file)
mailContent = csv_file.readlines()
return mailContent
def tab_print_proj(col, table_name, status):
import glob
tables = glob.glob('./tables/*.csv')
if status is False:
for i in tables:
if table_name in i.replace('./tables/','').replace('.csv',''):
from prettytable import from_csv
fp = open("./tables/"+table_name+".csv", "r")
customer = from_csv(fp)
fp.close()
text2.delete('1.0', END) #For delete the text from input box
print customer.get_string(fields=col)
text2.insert(INSERT, customer.get_string(fields=col))
else:
cross_prod(table_name)
tables = glob.glob('./tables/*.csv')
table_name=table_name.split(',')
for i in tables:
if table_name[0] in i.replace('./tables/','').replace('.csv','') or table_name[1] in i.replace('./tables/','').replace('.csv',''):
from prettytable import from_csv
fp = open("./tables/tmp.csv", "r")
customer = from_csv(fp)
fp.close()
text2.delete('1.0', END) #For delete the text from input box
print customer.get_string(fields=col)
text2.insert(INSERT, customer.get_string(fields=col))
def pprint_df(data_frame):
"""
INPUT: Pandas Data Frame
OUTPUT: A Pretty Pandas Data Frame printed to std out; returns None
"""
output = StringIO()
data_frame.to_csv(output)
output.seek(0)
print prettytable.from_csv(output)
pass
def search_student(search='id'):
if search == 'id':
print('[1] Searching by ID')
with open('student_database_final.csv', 'r') as fr:
data_table = from_csv(fr,
field_names=[
'Student ID', 'Student Name', 'Age',
'Gender', 'Department'
])
print(data_table)
choice = input('\nPlease enter your choice:\n'
'[1] Main Menu\n'
'\n'
'admin@sms:~$ ')
if choice == '1':
main.StartMain.main(self='self')
else:
print()
print('[X] Wrong Input!')
time.sleep(.50)
if operating_system == 'Linux':
os.system('clear')
elif operating_system == 'Windows':
os.system('cls')
student_database()
elif search == 'first_name':
print('[2] Searching by First Name')
with open('student_database_final.csv', 'r') as fr:
data_table = from_csv(fr,
field_names=[
'Student ID', 'Student Name', 'Age',
'Gender', 'Department'
])
print(data_table)
choice = input('\nPlease enter your choice:\n'
'[1] Main Menu\n'
'\n'
'admin@sms:~$ ')
if choice == '1':
main.StartMain.main(self='self')
else:
print()
print('[X] Wrong Input!')
time.sleep(.50)
if operating_system == 'Linux':
os.system('clear')
elif operating_system == 'Windows':
os.system('cls')
student_database()
def readCSV(csvFileName):
with open(csvFileName, 'r') as csv_file:
mailContent = prettytable.from_csv(csv_file)
print mailContent, type(mailContent)
# mailContent = "" #csv_file.readlines()
return mailContent
def __convertCsvToWarp(self, file):
with open(file, 'rb') as f:
reader = from_csv(f)
table_converted = re.sub('\n', '<br>', str(reader))
table_converted_with_tab = re.sub(' ', ' ', table_converted)
return table_converted_with_tab
def old():
memo = raw_input("\nWhich record data to show : ")
with open(memo + ".txt", "a+") as fp:
mytable = from_csv(fp)
os.system(clean)
sort(mytable)
print mytable
def mail():
with open("running_ins.csv", "r") as fp:
x = from_csv(fp)
f= open("val_table.txt","w+")
f.write(str(x))
f.close()
wb = Workbook()
ws = wb.active
with open('running_ins.csv', 'r') as f:
for row in csv.reader(f):
ws.append(row)
wb.save('all_instance_.xlsx')
with open('running_ins.csv', 'r') as book1:
r = csv.reader(book1, delimiter=',')
for row in r:
if (row[4] == 'NULL'):
write_null_id(row[0],row[1],row[2],row[3],row[4],row[5],row[6],row[7])
date=datetime.datetime.now()
date=date.strftime("%Y-%m-%d %H:%M:%S")
cmd = "cat running_ins.csv | column -t > /tmp/running.txt"
os.system(cmd)
cmd = "mutt -s 'Running Instnace and Tags "+ date +" ' -c MAIL_ID -a /tmp/running_ins.csv < /tmp/running.txt"
#os.system(cmd)
cmd = "rm -rf running*"
def show_inventory_csv(self):
"""Show inventory.csv file as a table, using PrettyTable."""
path_current_file = os.path.dirname(os.path.realpath(__file__))
printfile = f'{path_current_file}/inventory.csv'
with open(printfile, "r") as fp:
x = from_csv(fp)
print(x)
def normtable(matrix, gene_order):
lib_order = ["Experiments", "Human Liver Carcinoma", "Heatshock", "UV", "Hepatocyte GF", "Interferons", "Brain"]
x = 1 + np.shape(matrix)[0]
y = 1 + np.shape(matrix)[1]
print x, y
a = np.arange(x*y).reshape(x,y).astype('object')
for k in range(0, y):
a[0,k] = lib_order[k]
for h in range(1, x):
a[h,0] = gene_order[h-1]
for h in range(1, x):
for t in range(1,7):
a[h,t] = matrix[(h-1),(t-1)]
with open('TPMnorm_matrix.csv', 'wb') as hello:
writer = csv.writer(hello, delimiter=',')
data = a
writer.writerows(data)
fp = open("TPMnorm_matrix.csv", "r")
file = from_csv(fp)
file.align="l"
fp.close()
def show_data(category, base, list):
# creating new file to store the sorted data
with open(".sorted_file.csv", 'w', newline='') as sortedFile:
# writing header
writer = csv.DictWriter(
sortedFile,
fieldnames=['Serial', 'Movie', 'Genres', 'Director', base])
writer.writeheader()
# initializing counter to track the serial
count = 1
for i in list:
# checking if the genre row contains the given category or not
if i[1].__contains__(category):
writer.writerow({
'Serial': count,
'Movie': i[0],
'Genres': i[1],
'Director': i[2],
base: i[3]
})
# limiting the data to 20 for simplifying to user
if count == 20:
break
count = count + 1
# displaying the data in tabular form
x = from_csv(open('.sorted_file.csv', newline=''))
print(x)
def print_summary_from_csv() -> None:
print(
"----------------------------------------------------------------------"
)
print(
'Summary ("KT" means "Kernel Time", "ET" means "End-to-end Time", in microseconds; "BW" means "Bandwidth" in GB/s):'
)
with open(csv_filename, "r") as f:
table: PrettyTable = prettytable.from_csv(f)
table.field_names = [
"OP",
"Args",
"Lib",
"KT(GPU)",
"BW(GPU)",
"KT(1 CPU)",
"ET(1 CPU)",
"KT(32 CPU)",
"ET(32 CPU)",
"Desc",
]
table.del_column("Desc")
for row in table.rows:
row[2] = {"PyTorch": "PT", "OneFlow": "OF"}[row[2]]
print(table)
def history(self):
self.MSG = anal.get_all_msg(self.ACCESS_TOKEN, self.GROUP_ID)
results = anal.get_activity(self.MSG)
self.DF = results[0]
self.DATA_MONTH = results[1]
self.DATA_HOURS = results[2]
self.DATA_DAYS = results[3]
anal.graph(self.GROUP_ID, self.DF, self.DATA_MONTH,
self.DATA_HOURS, self.DATA_DAYS)
output = StringIO()
self.DF.to_csv(output)
output.seek(0)
pt = prettytable.from_csv(output)
ret = '<pre>'
ret += 'Analytics of GROUP# ' + str(self.GROUP_ID) + '<br>'
ret += 'Requested at ' + datetime.datetime.today().isoformat(' ') + '<br> <br>'
ret += 'Total Number of Messages: ' + \
str(self.DF['Message Frequency'].sum()) + '<br>'
ret += 'Total Number of Words: ' + str(self.DF['Words'].sum()) + '<br>'
ret += 'Total Likes: ' + str(self.DF['Likes Received'].sum()) + '<br>'
ret += 'Total Days: ' + str((datetime.datetime.fromtimestamp(self.MSG[0][
'created_at']) - datetime.datetime.fromtimestamp(self.MSG[-1]['created_at'])).days) + '<br>'
ret += pt.get_string() + '</pre>'
ret += '<br> <br>'
ret += '<img src= {{ act_url }}> <br> <br>'
ret += '<img src={{ m_url }}>'
ret += '<img src={{ l_url }}>'
ret += '<img src={{ r_url }}>'
return ret
def _print_total_price(price):
titles = [
{'ondemand': 'on demand'},
{'noup': '1 y no up'},
{'1yearpartup': '1 y part up'},
{'1yearfullup': '1 y full up'},
{'3yearpartup': '3 y part up'},
{'3yearfullup': '3 y full up'}
]
duration = {'hrly': 1, 'mthly': 24 * 30.5, 'yrly': 24 * 30.5 * 12}
prices = []
for t in titles:
prices.append(float(price[t.keys()[0]]))
with open('prices.csv', 'w') as f:
f.write('durat,{0}\n'.format(
','.join([x.values()[0] for x in titles]))
)
for d in sorted(duration, key=duration.get):
f.write('{0},{1}\n'.format(
d, ','.join([str(p * duration[d]) for p in prices])
))
with open('prices.csv', 'r') as f:
print(from_csv(f))
def testFunc2(data):
'''
从 csv 文件中加载数据
'''
mycsv = open(data)
print(mycsv.readline())
table = from_csv(mycsv)
mycsv.close()
print(
'===========================================table3-from csv=============================================='
)
print(table)
print(
'=================================table:SepalLength_Species===================================='
)
print(table.get_string(fields=['SepalLength', 'Species']))
print(
'=======================================table:60=>80 rows======================================'
)
print(table.get_string(start=60, end=80))
def Table(matrix, lib_order, gene_order):
a = np.arange(250).reshape(50, 5).astype('object')
i = 0
a[0, 0] = 'id'
for k in range(1, 50):
a[k, 0] = lib_order[(k - 1)]
for j in range(0, 4):
i = j + 1
a[0, i] = gene_order[j]
for u in range(1, 50):
a[u, i] = matrix[j, (u - 1)]
with open('SummaryStat.csv', 'wb') as hello:
writer = csv.writer(hello, delimiter=',')
data = a
writer.writerows(data)
fp = open("SummaryStat.csv", "r")
file = from_csv(fp)
file.align = "l"
fp.close()
print(file)
def process_string(csv_string):
"""Take a raw csv string and convert it into an ascii table"""
csv_io = StringIO.StringIO(csv_string)
table = from_csv(csv_io)
table.align = 'l'
return table.get_string()
def pretty_print_table(dfo):
from io import StringIO
import prettytable
output = StringIO()
dfo.to_csv(output)
output.seek(0)
pt = prettytable.from_csv(output)
print(pt)
def display(args):
if (os.path.isfile(args.FILE)):
fp = open(args.FILE, 'r')
mytable = from_csv(fp)
print(mytable)
fp.close()
else:
print("ERROR IN FILE DISPLAY\n")
def display(args):
if(os.path.isfile(args.FILE)):
fp = open(args.FILE,'r')
mytable=from_csv(fp)
print(mytable)
fp.close()
else:
print("ERROR IN FILE DISPLAY\n")
def listStops():
if not fileexists:
print("You don't have any past searches")
return
f = open(fname, "r")
tb = prettytable.from_csv(f)
f.close()
print(tb)
def pretty_print(df): from StringIO import StringIO import prettytable output = StringIO() df.to_csv(output, index = False, sep ='\t') output.seek(0) pt = prettytable.from_csv(output) print(pt)
def to_rst(cls, columns=None, sort_key=None):
input = StringIO(cls.to_csv(columns, sort_key))
from prettytable import from_csv
table = from_csv(input)
lines = table.get_string(hrules=True).splitlines()
# Special separator between header and rows in RST
lines[2] = lines[2].replace('-', '=')
return '\n'.join(lines)
def sale_table(): #sale list
print()
print('商品表')
goods_file = open('goods.csv', 'r')
saletb = from_csv(goods_file)
saletb.align = 'c'
saletb.sort = 'goods'
print(saletb)
goods_file.close()
def main():
""" It's script which trasnlate csv to HTML table.
"""
with open("dataset.csv", "r") as fp:
x = from_csv(fp) # read from csv by PT
y = PrettyTable.get_html_string(x) # translate to html, PT
table_html = y # store in var
html_file=open('table.html','w') # create and write
html_file=html_file.write(table_html) # add var html
def show_product_range_csv(self):
"""Show product_range.csv file as a table, using PrettyTable."""
path_current_file = os.path.dirname(os.path.realpath(__file__))
printfile = f'{path_current_file}/product_range.csv'
with open(printfile, "r") as fp:
x = from_csv(fp, field_names=["Product Name", "Product group",
"Footprint Weight"])
x_to_show = x[1:]
print(x_to_show)
def dept_tables():
#pickle.dump(dept_cnt, open('pending_departments.pkl','wb'))
#pending_departments = pickle.load(open('pending_departments.pkl','rb'))
print "Pending", sum(pending_departments.values())
print "Published", sum(dept_cnt.values())
#print set(pending_departments.items())
#print list(set(pending_departments.items()) & set(dept_cnt.items()))
#print [d for d in pending_departments.items()]
# create a list of tuples
#[(key, value)]
published_column = []
for department in pending_departments:
print ">>",department
if dept_cnt.has_key(department):
published_column.append(dept_cnt[department])
else:
published_column.append(0)
print published_column
print pending_departments
f = open('departments.csv', 'wt')
writer = csv.writer(f)
x=PrettyTable()
dept_column = [item[0] for item in pending_departments.items()]
x.add_column("Department Name", pending_departments.keys(), 'l', 't')
x.add_column("Published",published_column,'r')
x.add_column("Pending",pending_departments.values(),'r')
print x
writer.writerow(['Department Name','Pending XML','Online'])
''' Create table to add data to '''
#print u'\u2019'.encode('utf-8') .replace(u'\u2019','') #Fix bad windows chars
for department, count in sorted(pending_departments.items()):
writer.writerow([department,
count,
'',
])
f.close()
print writer
fp = open('departments.csv', 'r')
pt = from_csv(fp)
pt.align['Department Name'] = "l" # Left align city names
pt.padding_width = 1 # One space between column edges and contents (default)
print pt
'''
def Report(self):
from prettytable import PrettyTable
from prettytable import from_csv
#table from csv
path = "file location"
csv_file = open(path)
x = from_csv(csv_file)
print(x)
def Report(self):
from prettytable import PrettyTable
from prettytable import from_csv
#table from csv
path = "/Users/Danielle/Desktop/EggIE_ver2_SOFTENG/resultegg.csv"
csv_file = open(path)
x = from_csv(csv_file)
print(x)
def setUp(self):
csv_string = """City name, Area , Population , Annual Rainfall
Sydney, 2058 , 4336374 , 1214.8
Melbourne, 1566 , 3806092 , 646.9
Brisbane, 5905 , 1857594 , 1146.4
Perth, 5386 , 1554769 , 869.4
Adelaide, 1295 , 1158259 , 600.5
Hobart, 1357 , 205556 , 619.5
Darwin, 0112 , 120900 , 1714.7"""
csv_fp = StringIO.StringIO(csv_string)
self.x = from_csv(csv_fp)
def stringify_pandas(pd):
"""
:param pd: A Dataframe
:return:
"""
output = StringIO()
pd.to_csv(output)
pt = prettytable.from_csv(output)
print(pt)
def print_pandas_table(data_frame):
'''Prints pandas dataframe to table in console'''
from StringIO import StringIO
import prettytable
output = StringIO()
data_frame.to_csv(output)
output.seek(0)
pt = prettytable.from_csv(output)
print pt
def top_ten(r_type, result_file):
'''
Print top ten test result as a table in console with specified stat data
'''
result = pd.read_csv(result_file, sep=",")
print "\nTop ten in descending order " + r_type
output = StringIO()
result.groupby(["Template Name"]).mean().sort([r_type], ascending=False)[:10].to_csv(output, encoding='utf-8', sep=",")
output.seek(0)
pt = prettytable.from_csv(output)
print pt
def setUp(self):
csv_string = """City name, Area , Population , Annual Rainfall
Sydney, 2058 , 4336374 , 1214.8
Melbourne, 1566 , 3806092 , 646.9
Brisbane, 5905 , 1857594 , 1146.4
Perth, 5386 , 1554769 , 869.4
Adelaide, 1295 , 1158259 , 600.5
Hobart, 1357 , 205556 , 619.5
Darwin, 0112 , 120900 , 1714.7"""
csv_fp = StringIO.StringIO(csv_string)
self.x = from_csv(csv_fp)
def stringify_pandas(pd):
"""
:param pd: A Dataframe
:return:
"""
output = StringIO()
pd.to_csv(output)
pt = prettytable.from_csv(output)
print(pt)
def show(self):
if self.new: print('Belum ada Highscore')
else:
ranked = self.highscore_df.sort_values(by='high_score',
ascending=False)
ranked['rank'] = ranked['high_score'].rank(
ascending=False).astype('int')
ranked.head(10).to_csv('ranked.csv')
with open('ranked.csv') as csv:
table = from_csv(csv)
print(table)
def view_students():
print("\n")
border_msg(" Student's Record In Our Information System ")
try:
fp = open(student_database, "r")
file = from_csv(fp)
fp.close()
print(file)
except (csv.Error, FileNotFoundError):
print("\n" + smb.WARN + fontcolor.red(
"Something Went Wrong ! Check 'students.csv' File !"))
finally:
continue_msg()
def testFunc2(data='mycsv.csv'):
'''
从 csv 文件中加载数据
'''
mycsv = open(data)
table = from_csv(mycsv)
mycsv.close()
print '===========================================table=============================================='
print table
print '=================================table:SepalLength_Species===================================='
print table.get_string(fields=['SepalLength', 'Species'])
print '=======================================table:60=>80 rows======================================'
print table.get_string(start=60, end=80)
def executesearch(self, searchquery):
req = urllib2.Request(url + authservice)
creds = self.encodeUserData(u,p)
res = urllib2.urlopen(req,creds)
sessionxml = res.read()
sessionkey = minidom.parseString(sessionxml).getElementsByTagName('sessionKey')[0].childNodes[0].nodeValue
print "got session key: %s" % sessionkey
if not searchquery.startswith('search'):
searchquery = 'search ' + searchquery
req = urllib2.Request(url + searchservice)
req.add_header('Authorization', 'Splunk %s' % sessionkey)
search=urllib.urlencode({'search': searchquery})
res = urllib2.urlopen(req,search)
searchxml = res.read()
sid = minidom.parseString(searchxml).getElementsByTagName('sid')[0].childNodes[0].nodeValue
print "got sid: %s" % sid
searchservicesstatus = '/services/search/jobs/%s/' % sid
req = urllib2.Request(url + searchservicesstatus)
req.add_header('Authorization', 'Splunk %s' % sessionkey)
isnotdone = True
while isnotdone:
res = urllib2.urlopen(req)
searchstatus = res.read()
isdonestatus = re.compile('isDone">(0|1)')
isdonestatus = isdonestatus.search(searchstatus).groups()[0]
if (isdonestatus == '1'):
isnotdone = False
print "got search status: %s" % isdonestatus
searchserviceresults = '/services/search/jobs/%s/results?output_mode=csv&count=0' % sid
req = urllib2.Request(url + searchserviceresults)
req.add_header('Authorization', 'Splunk %s' % sessionkey)
res = urllib2.urlopen(req)
searchresults = res.read()
results = StringIO.StringIO(searchresults)
table = prettytable.from_csv(results)
print table
def read_print_csv(read_csv_list_criteria):
csv_file_path_list, csv_file_name_list = find_file_path_name(test_queries_temp_dir, read_csv_list_criteria)
if csv_file_name_list:
from prettytable import from_csv
for each_csv_file in csv_file_name_list:
file_csv = open(test_queries_temp_dir + "/" + each_csv_file , "r")
csv_table = from_csv(file_csv)
if "all_rounds" in each_csv_file:
print("\n\nSummary of all rounds for " + each_csv_file[:-4])
print(csv_table.get_string(sortby=master_header))
if "failures" in each_csv_file:
print("\n\n Failed Queries for " + each_csv_file[:-4])
print(csv_table.get_string(sortby=master_header))
if "min_comparison" in each_csv_file:
print("\n\n Fastest Execution Analysis \n")
print(csv_table.get_string(sortby=master_header))
file_csv.close()
def pickCut(Sequence):
from prettytable import from_csv
print("Which of these characterized loci is going to get lucky: ")
fp = open("cutsites.csv", "r")
pt = from_csv(fp)
fp.close()
print(pt)
cutsiteNum = int(input("Choose your cutsite (Leftmost number):"))
print("")
print("You've chosen: ")
print(pt.get_string(start = cutsiteNum-1, end = cutsiteNum))
counter = 0
for row in pt:
counter += 1
if counter == cutsiteNum:
row.border = False
row.header = False
cutsite = row.get_string(fields=["sequence"]).strip()
cutName = row.get_string(fields=["name"]).strip()
chromosome = int(row.get_string(fields=["chromosome"]).strip())
if chromosome >= 10:
filename = "Scer" + str(chromosome) + ".fasta"
else:
filename = "Scer0" + str(chromosome) + ".fasta"
ChromosomeRec=SeqIO.read(filename, "fasta")
ChromosomeSeq = ChromosomeRec.seq
if ChromosomeSeq.find(cutsite) == -1:
ChromosomeSeq = ChromosomeSeq.reverse_complement()
startInd = ChromosomeSeq.find(cutsite)
UpHomology = SeqRecord(ChromosomeSeq[startInd - 1000:startInd])
DownHomology = SeqRecord(ChromosomeSeq[startInd + 30:startInd + 1030])
return UpHomology, DownHomology
import sys from prettytable import from_csv # This file uses a third party library. PrettyTable: Display data in tables using a beautiful ASCII format. # Thank you [email protected] (code.google.com) for providing the prettytable library. # TODO: Add filter functionality (ex. filter search engines with genre: google facebook duckduckgo -> google duckduckgo) print "Run 'manageCollection.py' to append/remove Collection(s).\n" collectionsData = open("Collections.csv", "r") collectionsTable = from_csv(collectionsData) def displayUnsorted(): print collectionsTable collectionsData.close() x = raw_input("Press enter to exit.") sys.exit("Completed.") def displaySorted(): print "1. Sort by URL (default)" print "2. Sort by Genre" print "3. Sort by Description" print "4. Sort by Ranking" sortBy = raw_input("Select what you would like to sort by.") if sortBy == "1": print "Sorting by URL... This may take awhile." print collectionsTable.get_string(sortby='URL') elif sortBy == "2":
count["while"].append(sum_while)
with open('dict.csv', 'w', newline='') as csvfile:
writer = csv.writer(csvfile, delimiter= ' ',quotechar='|', quoting=csv.QUOTE_MINIMAL)
writer.writerow(["token","occurences","cycles"])
for key,value in count.items():
writer.writerow([key,value[0],value[1]])
read_fault = open("dict.csv","r")
line = read_fault.readline()
for line in read_fault:
new_line = re.sub(r"\^M","",line)
#print(new_line)
line = read_fault.readline()
read_fault.close()
reader = open("dict.csv", "r")
#reader = re.sub(r"\^M","",reader)
mytable = from_csv(reader)
print("Lookup Table Population")
print(mytable)
print("Total number of Memory Accesses is ",count["id"][0])
print("Memory Accesses")
with open('register.csv', 'w', newline='') as csvfile:
writer = csv.writer(csvfile, delimiter= ' ',quotechar='|', quoting=csv.QUOTE_MINIMAL)
writer.writerow(["ID","Accesses"])
for key,value in registers_used.items():
writer.writerow([key,value])
reader_reg = open("register.csv","r")
myreg = from_csv(reader_reg)
print(myreg)
print("For count")
with open('for.csv', 'w', newline='') as csvfile:
writer = csv.writer(csvfile, delimiter= ' ',quotechar='|', quoting=csv.QUOTE_MINIMAL)
df.drop(['min1','min2','max1','max2'],axis=1,inplace=True)
#df = df.set_index('sample')
sampleList = df['sample'].unique()
#sampleToUse = sampleList[0]
print '#'*100
print 'Cutflow for',sampleToUse
print '#'*100
dfPrint = df.loc[df['sample']==sampleToUse]
dfPrint = dfPrint.drop(['sample','errEffRel','errEffAbs'],axis=1)
#dfPrint = dfPrint.head(10)
# print
output = StringIO()
dfPrint.to_csv(output,index=False)
output.seek(0)
pt = prettytable.from_csv(output)
print pt
print
print '#'*100
print 'latex table'
print '#'*100
print
print dfPrint.to_latex(index=False)
print
def show_csv_file(name):
fp = open(name, "r")
mytab = from_csv(fp)
fp.close()
print mytab
"__VIEWSTATEGENERATOR":"413B2934",
"__EVENTVALIDATION":"/wEdAAgWGG2RY7jiUVmjHVLA3Vuhehn3bx2onw+gsGVGxW2uqPNH0QUya0tFKkgIABYfTinPqMgpP5oNyRNOFC9UkRd5TOB3/nlg9WQl65G7nSsW3XNGFTzwHLRD2v/eJGCd0ynBitcvyf0ePx5gnv8TklictmXUWyWAGbecBNn3zDP8oVEqyvt2y+R5rbK1ebIZhW17xDILuWgEcbUxmBSNbL8K",
"DropDownList_CaseType":"Confirm", #DHF Confirm
"DropDownList_AreaType":"DIST", #DIST VILLAGE
}
date = datetime.date(2014,12,10)
F = {}
for i in range(15):
data["TextBox_Start"] = date
date += datetime.timedelta(days=1)
data['TextBox_End'] = date
print data['TextBox_Start'] , data['TextBox_End']
html = requests.post('http://dengue.kcg.gov.tw/KCGDengue/Mobile.aspx', verify=False, headers=headers, data=data)
match = re.findall(u'var AREA = new Array\((.*?)\);', html.text)
match2 = re.findall(u'var NUMB = new Array\((.*?)\);', html.text)
if match == [] : continue
Area = [x.strip("'") for x in match[0].split(', ')]
Count = [ int(x) for x in match2[0].split(', ')]
final = dict(zip(Area, Count))
F[date.strftime('%Y-%m-%d')] = final
F.update(F)
df = pd.DataFrame.from_dict(F, orient='columns')
newset = df.T.fillna(0)
output = StringIO()
newset.to_csv(output,encoding='utf-8',sep=',')
output.seek(0)
print prettytable.from_csv(output)
def display_as_table(file_name_full):
with open(file_name_full, 'rb') as fd:
sum_table = from_csv(fd)
print sum_table
mpl.rcParams['lines.linewidth'] = 2
mpl.rcParams['lines.markersize'] = 3
from matplotlib.widgets import Slider
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter
import matplotlib.dates as mdates
slider_on = 1
## Open with prettytable ##
fp = open("klarup_log.csv", "rb")
table = pt.from_csv(fp)
fp.close()
d,i={},0
cols = map(list, zip(*table._rows))
for key in table.field_names:
if cols[i].replace('.','').isdigit():
d[key] = float(cols[i])
else:
d[key] = cols[i]
i+=1
d['time_datetime'] = []
for s in d['Time']:
d['time_datetime'].append( datetime.datetime.strptime( s , '%d. %B %Y %H:%M' ) )