I\'m looking to turn a pandas cell containing a list into rows for each of those values.
So, take this:
If I\'d like to unpack and stack the value
Extending Oleg's .iloc answer to automatically flatten all list-columns:
def extend_iloc(df):
cols_to_flatten = [colname for colname in df.columns if
isinstance(df.iloc[0][colname], list)]
# Row numbers to repeat
lens = df[cols_to_flatten[0]].apply(len)
vals = range(df.shape[0])
ilocations = np.repeat(vals, lens)
# Replicate rows and add flattened column of lists
with_idxs = [(i, c) for (i, c) in enumerate(df.columns) if c not in cols_to_flatten]
col_idxs = list(zip(*with_idxs)[0])
new_df = df.iloc[ilocations, col_idxs].copy()
# Flatten columns of lists
for col_target in cols_to_flatten:
col_flat = [item for sublist in df[col_target] for item in sublist]
new_df[col_target] = col_flat
return new_df
This assumes that each list-column has equal list length.