I have a small algorithm like this one.
I coded it in python
import pandas as pd
raw = pd.read_csv
i = 0
T = pd.DataFrame(columns = ['Values'])
singleT = raw.mean() + raw.std()
T = T.append(singleT, ignore_index=True)
if i == 0:
raw = raw.where(raw<T.iloc[i,:])
i += 1
while True:
singleT = raw.mean() + raw.std()
T = T.append(singleT, ignore_index=True)
if T.iloc[i,:].values == T.iloc[i-1,:].values:
break
background = T.iloc[i,:].values
else:
raw = raw.where(raw<T.iloc[i,:])
i += 1
print ('iteration{:02}'.format(i))
However, the loop didn't get pass i = 1 and keep repeating, the whole T array is filled with value when i = 1. I tried several modifications to my code but they also didn't work at all.
Any advice on how to fix this problem would be appreciated!
Thank you very much
Edit: I have inserted one tab for the last 4 lines, as you guys suggested to make sure the else belong to while, but now it has syntax invalid error
Edit2: Here is the correct code for this problem, it will not enter the infinite loop.
i = 0
T = pd.DataFrame(columns = ['Pulse counts'])
singleT = raw.mean() + raw.std()
T = T.append(singleT, ignore_index=True)
if i == 0:
filtered = raw.where(raw<T.iloc[i,:])
i += 1
while True:
singleT = filtered.mean() + filtered.std()
T = T.append(singleT, ignore_index=True)
if T.iloc[i,:].values == T.iloc[i-1,:].values or T.iloc[i-1,:].values == 0:
background = T.iloc[i-1,:].values
break
else:
filtered = filtered.where(filtered<T.iloc[i,:])
print ('iteration{}'.format(i))
i += 1
Try this way :
import pandas as pd
raw = pd.read_csv
i = 0
T = pd.DataFrame(columns = ['Values'])
singleT = raw.mean() + raw.std()
T = T.append(singleT, ignore_index=True)
while True:
singleT = raw.mean() + raw.std()
T = T.append(singleT, ignore_index=True)
if T.iloc[i,:].values == T.iloc[i-1,:].values:
background = T.iloc[i,:].values
break
else:
raw = raw.where(raw<T.iloc[i,:])
#i += 1
print ('iteration{:02}'.format(i))
i += 1
if your indentation is correct, the else part:
else:
raw = raw.where(raw<T.iloc[i,:])
i += 1
print ('iteration{:02}'.format(i))
doesn't belong to the if but to the while, which has a different meaning: it is executed only if loop ends without a break (less-known feature, also available with for which saves the need to define a flag when break has been reached)
So i is never incremented: infinite loop.
Related
I am trying to Call Api in a while loop and append the dataframe. But it is not appending .
#Max timestamp
MaxTs = 1635876000
api_key = "api_key"
cnt = 0
while cnt < 4:
url = f"https://min-api.cryptocompare.com/data/v2/histohour?fsym=BTC&tsym=USD&limit=2000&toTs={MaxTs}&api_key={api_key}"
r = requests.get(url)
data = r.json()
price_df = pd.DataFrame(data['Data']['Data'])
i = 0
reccnt = 2000
while i < reccnt:
currTs = price_df.iloc[i]['time']
if currTs < MaxTs:
MaxTs = currTs
i = i + 1
if cnt == 0:
#Copying the Orginal df to new df.
newdf = price_df.copy()
else:
#when counter increases append the df.
newdf.append(price_df)
print(MaxTs)
cnt = cnt + 1
You should increase cnt inside the while loop, not outside.
But after you perform a correction you will get several copies of the same price_df. Is that what you are trying to get?
What am I doing to deserve this warning from Python? Would like to avoid errors, if the warning is telling me something...
if DELfile.exists():
print(DELfile)
sectorDEL = pd.read_csv(DELfile, sep=';', header=0, float_precision='round_trip')
if i == 1:
sectorDELmax = sectorDEL
i = i + 1
else:
k = 0
for sensor in sectorDEL['SENSOR_NO']:
if sectorDEL['DAMAGE_EQUIVALENT_LOAD'][k] > sectorDELmax['DAMAGE_EQUIVALENT_LOAD'][k]:
sectorDELmax['DAMAGE_EQUIVALENT_LOAD'][k] = sectorDEL['DAMAGE_EQUIVALENT_LOAD'][k]
k = k + 1
else:
print('Could not find ' +str(DELfile))
return None
Working for single symbol
todate = zerodha.get_trade_day(datetime.now().astimezone(to_india) - timedelta(days=0))
fromdate = zerodha.get_trade_day(datetime.now().astimezone(to_india) - timedelta(days=5))
symbol = "ZINC20MAYFUT"
instype = "MCX"
Timeinterval = "5minute"
tradeDir = 0 #neutral
while (True):
histdata1 = zerodha.get_history(symbol, fromdate, todate, Timeinterval, instype)
df = pd.DataFrame(histdata1)
df = heikinashi(df)
df = bollinger_bands(df,field='h_close',period=20, numsd=2)
df1 =pd.DataFrame(df, columns=['date','volume','close','h_close','middle_band', 'upper_band'])
pp = pd.DataFrame(df1.tail(3))
print(pp)
dfCToList = pp['h_close'].tolist()
dfCList = list(pp['h_close'])
dfHValues = pp['h_close'].values
dfBMValues = pp['middle_band'].values
H_last = dfHValues[2] # tail 1
BM_last = dfBMValues[2] # tail 1
if (H_last > BM_last and (tradeDir == 0 or tradeDir == -1)):
print("buy")
tradeDir = 1 # up
if (H_last < BM_last and (tradeDir == 0 or tradeDir == 1)):
print("SELL")
tradeDir = -1 # down
# pdb.set_trace()
Question: When conditions meet its Printing "BUY/SELL" again and again. I want to just print a single time when condition meet the first time
todate = zerodha.get_trade_day(datetime.now().astimezone(to_india) - timedelta(days=0))
fromdate = zerodha.get_trade_day(datetime.now().astimezone(to_india) - timedelta(days=5))
tradeDir = 0 #neutral
def script():
global tradeDir
##For historical Data##
symbol = ["ZINC20MAYFUT" ,"CRUDEOIL20MAYFUT","GOLD20JUNFUT"]
instype = "MCX"
Timeinterval = "5minute"
for symbol in symbol:
global tradeDir
histdata1 = zerodha.get_history(symbol, fromdate, todate, Timeinterval, instype)
df = pd.DataFrame(histdata1)
df = heikinashi(df)
df = bollinger_bands(df,field='h_close',period=20, numsd=2)
df1 =pd.DataFrame(df, columns=['date','volume','close','h_close','middle_band', 'upper_band'])
pp = pd.DataFrame(df1.tail(3))
print(pp)
dfCToList = pp['h_close'].tolist()
dfCList = list(pp['h_close'])
dfHValues = pp['h_close'].values
dfBMValues = pp['middle_band'].values
H_last = dfHValues[2] # tail 1
BM_last = dfBMValues[2] # tail 1
if (H_last > BM_last and (tradeDir == 0 or tradeDir == -1)):
print("buy")
tradeDir = 1 # up
if (H_last < BM_last and (tradeDir == 0 or tradeDir == 1)):
print("SELL")
tradeDir = -1 # down
# pdb.set_trace()
while True:
try:
script()
except Exception as e:
sleep(2)
continue
When conditions meet its Printing "BUY/SELL" again and again. I want to just print a single time when condition meet the first time full Script and should run continuously
If you want the code to stop looping after the first time it prints "buy" or "SELL", you just need to add a break statement after each of the prints (inside the scope of the containing if blocks).
I am using my arduino to analyze analog inputs and I am accessing the arduino using the pyfirmata library and I ambasically measuring voltages using the 6 analog inputs on my arduino Uno. I need to find a way to live time feed this data into a CSV efficiently... I am not sure on the best way to do that
Any suggestion would help but please write out the code you suggest. I would prefer to use Pandas if possible because it's easier
voltage0 through voltage5 are my variables and I am trying to report those in a nice format that will later have to be analyzed
import time
from datetime import datetime
import pyfirmata
import pandas as pd
board = pyfirmata.Arduino('/dev/ttyACM1')
analog_pin0 = board.get_pin('a:0:i')
analog_pin1 = board.get_pin('a:1:i')
analog_pin2 = board.get_pin('a:2:i')
analog_pin3 = board.get_pin('a:3:i')
analog_pin4 = board.get_pin('a:4:i')
analog_pin5 = board.get_pin('a:5:i')
it = pyfirmata.util.Iterator(board)
it.start()
analog_pin0.enable_reporting()
analog_pin1.enable_reporting()
analog_pin2.enable_reporting()
analog_pin3.enable_reporting()
analog_pin4.enable_reporting()
analog_pin5.enable_reporting()
data = []
count = 0
x = 0
start = 0
while x <= 1000:
reading0 = analog_pin0.read()
if reading0 != None:
voltage0 = reading0 * 5
voltage0 = round(voltage0,2)
else:
voltage0 = float('nan')
reading1 = analog_pin1.read()
if reading1 != None:
voltage1 = reading1 * 5
voltage1 = round(voltage1,2)
else:
voltage1 = float('nan')
reading2 = analog_pin2.read()
if reading2 != None:
voltage2 = reading2 * 5
voltage2 = round(voltage2,2)
else:
voltage2 = float('nan')
reading3 = analog_pin3.read()
if reading3 != None:
voltage3 = reading3 * 5
voltage3 = round(voltage3,2)
else:
voltage3 = float('nan')
reading4 = analog_pin4.read()
if reading4 != None:
voltage4 = reading4 * 5
voltage4 = round(voltage4,2)
else:
voltage4 = float('nan')
reading5 = analog_pin5.read()
if reading5 != None:
voltage5 = reading5 * 5
voltage5 = round(voltage5,2)
else:
voltage5 = float('nan')
datarow = {'Voltage0': voltage0, 'Voltage1': voltage1, 'Voltage2' : voltage2, 'Voltage3': voltage3, 'Voltage4' : voltage4, 'Voltage5' : voltage5, 'Time' : time.strftime("%Y-%m-%d_%H:%M:%S")}
data.append(datarow)
if count%500 == 0:
dataframe = pd.DataFrame(data)
dataframe.to_csv('data.csv')
x += 1
count += 1
#time.sleep(1)enter code here
Your code seems to work, but it's not very efficient. Every 500 iterations, you rewrite all your data instead of updating your file with the new data in the end. You might consider saving it this way instead:
if count%500 == 0:
dataframe = pd.DataFrame(data)
dataframe.to_csv('data.csv',mode='a',header=False)
data = []
If it's still not fast enough, you might consider saving your data to a binary format such as .npy (numpy format), and convert it later to csv.
Sorry for the unsophisticated question title but I need help desperately:
My objective at work is to create a script that pulls all the records from exacttarget salesforce marketing cloud API. I have successfully setup the API calls, and successfully imported the data into DataFrames.
The problem I am running into is two-fold that I need to keep pulling records till "Results_Message" in my code stops reading "MoreDataAvailable" and I need to setup logic which allows me to control the date from either within the API call or from parsing the DataFrame.
My code is getting stuck at line 44 where "print Results_Message" is looping around the string "MoreDataAvailable"
Here is my code so far, on lines 94 and 95 you will see my attempt at parsing the date directly from the dataframe but no luck and no luck on line 32 where I have specified the date:
import ET_Client
import pandas as pd
AggreateDF = pd.DataFrame()
Data_Aggregator = pd.DataFrame()
#Start_Date = "2016-02-20"
#End_Date = "2016-02-25"
#retrieveDate = '2016-07-25T13:00:00.000'
Export_Dir = 'C:/temp/'
try:
debug = False
stubObj = ET_Client.ET_Client(False, debug)
print '>>>BounceEvents'
getBounceEvent = ET_Client.ET_BounceEvent()
getBounceEvent.auth_stub = stubObj
getBounceEvent.search_filter = {'Property' : 'EventDate','SimpleOperator' : 'greaterThan','Value' : '2016-02-22T13:00:00.000'}
getResponse1 = getBounceEvent.get()
ResponseResultsBounces = getResponse1.results
Results_Message = getResponse1.message
print(Results_Message)
#EventDate = "2016-05-09"
print "This is orginial " + str(Results_Message)
#print ResponseResultsBounces
i = 1
while (Results_Message == 'MoreDataAvailable'):
#if i > 5: break
print Results_Message
results1 = getResponse1.results
#print(results1)
i = i + 1
ClientIDBounces = []
partner_keys1 = []
created_dates1 = []
modified_date1 = []
ID1 = []
ObjectID1 = []
SendID1 = []
SubscriberKey1 = []
EventDate1 = []
EventType1 = []
TriggeredSendDefinitionObjectID1 = []
BatchID1 = []
SMTPCode = []
BounceCategory = []
SMTPReason = []
BounceType = []
for BounceEvent in ResponseResultsBounces:
ClientIDBounces.append(str(BounceEvent['Client']['ID']))
partner_keys1.append(BounceEvent['PartnerKey'])
created_dates1.append(BounceEvent['CreatedDate'])
modified_date1.append(BounceEvent['ModifiedDate'])
ID1.append(BounceEvent['ID'])
ObjectID1.append(BounceEvent['ObjectID'])
SendID1.append(BounceEvent['SendID'])
SubscriberKey1.append(BounceEvent['SubscriberKey'])
EventDate1.append(BounceEvent['EventDate'])
EventType1.append(BounceEvent['EventType'])
TriggeredSendDefinitionObjectID1.append(BounceEvent['TriggeredSendDefinitionObjectID'])
BatchID1.append(BounceEvent['BatchID'])
SMTPCode.append(BounceEvent['SMTPCode'])
BounceCategory.append(BounceEvent['BounceCategory'])
SMTPReason.append(BounceEvent['SMTPReason'])
BounceType.append(BounceEvent['BounceType'])
df1 = pd.DataFrame({'ClientID': ClientIDBounces, 'PartnerKey': partner_keys1,
'CreatedDate' : created_dates1, 'ModifiedDate': modified_date1,
'ID':ID1, 'ObjectID': ObjectID1,'SendID':SendID1,'SubscriberKey':SubscriberKey1,
'EventDate':EventDate1,'EventType':EventType1,'TriggeredSendDefinitionObjectID':TriggeredSendDefinitionObjectID1,
'BatchID':BatchID1,'SMTPCode':SMTPCode,'BounceCategory':BounceCategory,'SMTPReason':SMTPReason,'BounceType':BounceType})
#print df1
#df1 = df1[(df1.EventDate > "2016-02-20") & (df1.EventDate < "2016-02-25")]
#AggreateDF = AggreateDF[(AggreateDF.EventDate > Start_Date) and (AggreateDF.EventDate < End_Date)]
print(df1['ID'].max())
AggreateDF = AggreateDF.append(df1)
print(AggreateDF.shape)
#df1 = df1[(df1.EventDate > "2016-02-20") and (df1.EventDate < "2016-03-25")]
#AggreateDF = AggreateDF[(AggreateDF.EventDate > Start_Date) and (AggreateDF.EventDate < End_Date)]
print("Final Aggregate DF is: " + str(AggreateDF.shape))
#EXPORT TO CSV
AggreateDF.to_csv(Export_Dir +'DataTest1.csv')
#with pd.option_context('display.max_rows',10000):
#print (df_masked1.shape)
#print df_masked1
except Exception as e:
print 'Caught exception: ' + str(e.message)
print e
Before my code parses the data, the orginal format I get of the data is a SOAP response, this is what it look like(below). Is it possible to directly parse records based on EventDate from the SOAP response?
}, (BounceEvent){
Client =
(ClientID){
ID = 1111111
}
PartnerKey = None
CreatedDate = 2016-05-12 07:32:20.000937
ModifiedDate = 2016-05-12 07:32:20.000937
ID = 1111111
ObjectID = "1111111"
SendID = 1111111
SubscriberKey = "aaa#aaaa.com"
EventDate = 2016-05-12 07:32:20.000937
EventType = "HardBounce"
TriggeredSendDefinitionObjectID = "aa111aaa"
BatchID = 1111111
SMTPCode = "1111111"
BounceCategory = "Hard bounce - User Unknown"
SMTPReason = "aaaa"
BounceType = "immediate"
Hope this makes sense, this is my desperately plea for help.
Thank you in advance!
You don't seem to be updating Results_Message in your loop, so it's always going to have the value it gets in line 29: Results_Message = getResponse1.message. Unless there's code involved that you didn't share, that is.