Create New Dataframe Once Time-delta Is Higher Than Xy

I have a dataframe with the following scheme: Is it possible to create new dataframes according TimeDelta? So if TimeDelta is greater than e.g. 1.5, create new dataframe? So that

Solution 1:

You can use a custom group and split with groupby.

First ensure that your "TimeDelta" values are numeric with pd.to_numeric, then asses whether they are geater than 1.5, and apply a cumsum() to flag all the following rows up to the next value above threshold. Finally groupby the custom group and convert to dict.

group = pd.to_numeric(df.TimeDelta, errors='coerce').gt(1.5).cumsum()
my_dfs = dict(list(df.groupby(group)))

output:

>>> my_dfs
{0:    time  parameter TimeDelta
 01800         -,
 1:    time  parameter TimeDelta
 137882245441,
 2:    time  parameter TimeDelta
 373443482441}

accessing a particular group:

>>> my_dfs[1] # secondgrouptimeparameter TimeDelta
137882245441

looping over the dataframes:

for group, dfin dict(list(df.groupby(group))).items():
    print(f'group {group}')
    print(df)