I Want To Iterate Through An Xlsx, Using Pandas, Containing Timestamps And Get Downtime

So I have an excel file with date in the first column and a regular interval timestamps in the consecutive rows and a column in the end containing the average. If the average is be

Solution 1:

moved calculation into dictionaries, as i could not find a suitable solution via Pandas.

  #convert to dictionary
  A = df.set_index('Date').to_dict('index')

  #remove values where 'Average' is less than 100
  B = {key:value for key,value in A.items() if value['Average'] < 100}

  #get rid of the 'Average' key
  #it is not relevant to the solution
  for value in B.values():
     del value['Average']

  from collections import Counter,defaultdict
  d=defaultdict(list)

 #count the number of 0s
 #if it is greater than one, keep
 #and append to the defaultdict d
 for key,value in B.items():
    m = Counter(value.values())
    M = list(value.values())
    #check for consecutive 0s in list
    test_for_consecutive_0 = any(i==j==0 for i,j in zip(M,M[1:]))
    if test_for_consecutive_0  and (m[0]>1):
        d[key].extend([key for key,val in value.items() if val==0])


 #join the values into a string
 result = {key:'-'.join(value) for key,value in d.items()}
 print(result)

 {'2-10-18': 'Timestamp2-TImestamps3',
  '3-10-18': 'Timestamp2-TImestamps3-Timestamp4'}