How to count the number of times a continuous condition is true?-CodePudding

Each row of the A column is compared with the A value when the COND column was True last time, if it is less than it, the condition is satisfied, and the count is accumulated. Stop counting until greater than or equal to.

Input:

import pandas as pd
A=[28,30,15,25,24,13,31,19,20,11,19,21]
COND=[False,True,False,False,False,False,False,False,True,False,False,False]
df=pd.DataFrame({'A':A,'COND':COND})

Expected Output

    A   COND    expected
0   28  FALSE   0
1   30  TRUE    0
2   15  FALSE   1
3   25  FALSE   2
4   24  FALSE   3
5   13  FALSE   4
6   31  FALSE   0
7   19  FALSE   0
8   20  TRUE    0
9   11  FALSE   1
10  19  FALSE   2
11  21  FALSE   0

CodePudding user response：

In order to achieve this result, you need to iterate over the lists to determine the outputted values.

Start by assigning some base variables:

expected = []
lastTrue = None
count = 0

These will be modified throughout the loop. Next, loop through and test for each condition.

Loop through the numbers:

for i in range(len(A)):
    num = A[i]

Test for if the condition is True; if it is, save the number and reset the count:

if COND[i]:  # If True, save the number and reset count
    lastTrue = num
    count = 0

Check for if a True value has been found yet:

elif lastTrue is None:  # If haven't found a True value yet, pass
    pass

Test the number against the last true number to determine the output:

elif num < lastTrue:  # If less than the last True value, increment count
    count  = 1
else:  # If larger than or equal to, reset count
    count = 0
    lastTrue = None

Add the current count to the list:

expected.append(count)

Now all you need to do is add the column and print the output.

Final code:

import pandas as pd
A=[28,30,15,25,24,13,31,19,20,11,19,21]
COND=[False,True,False,False,False,False,False,False,True,False,False,False]

expected = []
lastTrue = None
count = 0
for i in range(len(A)):
    num = A[i]
    if COND[i]:  # If True, save the number and reset count
        lastTrue = num
        count = 0
    elif lastTrue is None:  # If haven't found a True value yet, pass
        pass
    elif num < lastTrue:  # If less than the last True value, increment count
        count  = 1
    else:  # If larger than or equal to, reset count
        count = 0
        lastTrue = None
    expected.append(count)

df=pd.DataFrame({'A':A,'COND':COND,'EXPECTED':expected})
print(df)

Output:

      A   COND  EXPECTED
 0   28  False         0
 1   30   True         0
 2   15  False         1
 3   25  False         2
 4   24  False         3
 5   13  False         4
 6   31  False         0
 7   19  False         0
 8   20   True         0
 9   11  False         1
 10  19  False         2
 11  21  False         0