Question

Using Python3,

How can I aggregate the output from each iteration to one single list? Because from the program I have right now, it gives me the result of every iteration and gives me something like this as individual results and not one large list:

None

None

...

None

130.0

None

...

1764

1765

None

To clarify, I have this program where it calculates the sum of bytes sent within each incrementation of every 1 second, but there are instances where I want to record the specific times when the sum of the bytes in the given second are above the threshold value.

The main part of code is below:
max_time = round(max_time,0) #rounding the number so that it should have only integer value

chunk = 1 #defines length of constant interval which is 1sec

def event_occurence(time, threshold):
load,res=[],[]
for i,j in zip(data_timestamp,data_load):
if(i<chunk and i>=time-chunk): #limit calculation for timestamps between restrictions, for example (3.14<4 and 3.14>=3)
load.append(j) #add bytes to list
if sum(load) >= threshold: #check to see if total bytes sent in that second pass threshold
res.append(i) #the timestamp of the very first instance it passed the threshold is added to res list
fin = np.ceil(res[0]) #round timestamp of first instance since its orignally a decimal
return int(fin)

for k in range(chunk, max_time+chunk, chunk):
print(event_occurence(k,3500))

How can I make just one big list that also does not include "None"

S.Py iied.py amttie import pandas as pd import openpyxl as xl import math import numpy as np 1 4 "/Users/myname/Des ktop/Book1. xlsx'" 6 filepath_out ######*****########### ######### pd.read_excel (filepath_out, sheet_name='SPLT') 10 data 11 #list of timestamp data 12 data_timestamp #list of length dat data_load #finding the max time in the timestamp list max_time = max ( data_timestamp ) #ceilng the max time to nearest largest number ex 3.14 to 4.00 max_time=math.ceil (max_time) #rounding the number so that it should have only integer value no floating values max_time = round(max_time,0) #function to caluculate the mean time data ["Timestamp") 13 14 data["Packet Length"] 15 16 17 18 19 20 21 22 23 24 ###********###### #####*****### [] 25 timefinal 26 def event_occurence(time, threshold) : load, res=[],[] for i,j in zip(data_timestamp, data_load): if(i<time and i>-time chunk) : load.append(j) if sum(load) >= threshold : res.append(i) 27 28 29 30 31 32 33 fin np.ceil(res[0]) return int(fin) 34 35 36 37 # def event_time ( num, th reshold ): 38 res,tim, fin=[], [],[]. for i,j in zip ( data_timestamp, data_load ) : if (i<num and i>=num-chunk_b): res.append(j) if sum(res) >= threshold: tim.append(i) fin = np.ceil (tim [0] ) return fin 39 # # 40 41 # 42 # 43 # 44 45 # 46 # 55 56 ##**### #########*########### chunk =1 for k in range(chunk, max_time+chunk, chunk): print (event_occurence(k,3500 ) ) 57 58 59 60

ignore xl import

Answer 1

# I couldn't add an execution screenshot because I don't have the excel file used in the question but the code will run fine

max_time = round(max_time,0) #rounding the number so that it should have only integer value

chunk = 1 #defines length of constant interval which is 1sec

def event_occurence(time, threshold):
load,res=[],[]
for i,j in zip(data_timestamp,data_load):
if(i<chunk and i>=time-chunk): #limit calculation for timestamps between restrictions, for example (3.14<4 and 3.14>=3)
load.append(j) #add bytes to list
if sum(load) >= threshold: #check to see if total bytes sent in that second pass threshold
res.append(i) #the timestamp of the very first instance it passed the threshold is added to res list
fin = np.ceil(res[0]) #round timestamp of first instance since its orignally a decimal
return int(fin)

# Code is same upto this point

event_list = [] # starting an empty list
for k in range(chunk, max_time+chunk, chunk):
e = event_occurence(k,3500)
if e != None: # check that the returned value is not None
event_list.append(e) # appending the value to the list

print(event_list) # printing the list