Groupby remainder of day to show True if identical consecutive values-CodePudding

Given the following DataFrame. How do I add a new column showing True for the rest of the day when two consecutive "y" are seen in a single day in the val column (else False).

Each day resets the logic.

This is close but the True should be for each row in this day after condition is seen.

Code

df_so = pd.DataFrame(
    {
        "val": list("yynnnyyynn")
    },
    index=pd.date_range(start="1/1/2018", periods=10, freq="6h"),
)

                   val
2018-01-01 00:00:00 y
2018-01-01 06:00:00 y
2018-01-01 12:00:00 n
2018-01-01 18:00:00 n
2018-01-02 00:00:00 n
2018-01-02 06:00:00 y
2018-01-02 12:00:00 y
2018-01-02 18:00:00 y
2018-01-03 00:00:00 n
2018-01-03 06:00:00 n

Desired output

                    val  out
2018-01-01 00:00:00  y   False
2018-01-01 06:00:00  y   False
2018-01-01 12:00:00  n   True
2018-01-01 18:00:00  n   True
2018-01-02 00:00:00  n   False
2018-01-02 06:00:00  y   False
2018-01-02 12:00:00  y   False
2018-01-02 18:00:00  y   True
2018-01-03 00:00:00  n   False
2018-01-03 06:00:00  n   False

CodePudding user response：

You can use cummax to check if the condition holds at some point in the past:

target = 2
df_so['out'] = (df_so['val'].eq('y')
                    .groupby(df_so.index.normalize())
                    .transform(lambda x: x.rolling(target).sum().shift().eq(target).cummax())
               )

Output:

                    val    out
2018-01-01 00:00:00   y  False
2018-01-01 06:00:00   y  False
2018-01-01 12:00:00   n   True
2018-01-01 18:00:00   n   True
2018-01-02 00:00:00   n  False
2018-01-02 06:00:00   y  False
2018-01-02 12:00:00   y  False
2018-01-02 18:00:00   y   True
2018-01-03 00:00:00   n  False
2018-01-03 06:00:00   n  False