I don't think df.copy() does what we want in the @copy_td decorator because it doesn't make an actual copy of array fields.
We will probably have to make recursive deep copy with something like pd.DataFrame(data=copy.deepcopy(df.values), index=df.index, columns=df.columns).
Unfortunately, it will be definitely slower and memory intensive, so we might have to think about those consequences later.
import copy
dfa = df.copy(deep=True)
dfb = deepcopy(df)
dfc = pd.DataFrame(data=copy.deepcopy(df.values), index=df.index, columns=df.columns)
dfa.PMd_spikes[0][0, 0] = -1 # changes the value in df
dfb.PMd_spikes[1][0, 0] = -1 # changes the value in df
dfc.PMd_spikes[2][0, 0] = -1 # leaves the value in df intact
I don't think
df.copy()does what we want in the@copy_tddecorator because it doesn't make an actual copy of array fields.We will probably have to make recursive deep copy with something like
pd.DataFrame(data=copy.deepcopy(df.values), index=df.index, columns=df.columns).Unfortunately, it will be definitely slower and memory intensive, so we might have to think about those consequences later.