09.11.2018 · In my case with more than one column to explode, and with variables lengths for the arrays that needs to be unnested. I ended up applying the new pandas 0.25 explode function two times, then removing generated duplicates and it does the job ! df = df.explode('A') df = df.explode('B') df = df.drop_duplicates()
01.09.2020 · pandas.apply expand column ValueError: If using all scalar values, you must pass an index. Ask Question Asked 1 year, 1 month ago. Active 1 year, 1 month ago. ... If using all scalar values, you must pass an index. I've tried to set the name of the output dataframe, ...
Jul 04, 2017 · So I would be willing to reverse this if we then allow scalars in the constructor w/o an Index. I think that it would be better than nothing (also because, all else equal, for backward compatibility we prefer to allow than to disallow something new).
Explode a DataFrame from list-like columns to long format. This routine will explode list-likes including lists, tuples, sets, Series, and np.ndarray. The result dtype of the subset rows will be object. Scalars will be returned unchanged, and empty list-likes will result in a np.nan for that row.
Raises: ValueError : if columns of As per pandas documentation explode(): ... Scalars will be returned This routine will explode list-likes including lists, ...
Exploded lists to rows of the subset columns; index will be duplicated for these rows. Raises. ValueError : If columns of the frame are not unique. If specified ...
My goal is to list each element on it's own row. I can use the df.explode() . but it only accepts one column. However, I want the pair of the two columns to ...
Pandas explode error – column must be scalar. 134 views July 21, 2021 pythonexplode pandas python Attribution: ... ValueError: column must be a scalar.
Apr 20, 2020 · This answer is not useful. Show activity on this post. For those of you working with Pandas < 1.3, the following logic executes a multi-column explode and is reasonably efficient. Just need to replace the name of cols you want to explode. def explode (df): df ['tmp']=df.apply (lambda row: list (zip (row [col1],row [col2])), axis=1) df=df ...