WebNov 30, 2024 · 0. Let's say we apply to each row of a Pandas.DataFrame a function returning a `List: def predict (row: Dict) -> List [float]: pass input.apply (predict, axis=1, result_type='expand') We do it with result_type='expand' to flatten the internal list to columns. So, if for example predict returns [1, 2, 3] for first row and [4, 5, 6] for second ... Web2 days ago · The to_datetime() function is great if you want to convert an entire column of strings. The astype() function helps you change the data type of a single column as well. The strptime() function is better with individual strings instead of dataframe columns. There are multiple ways you can achieve this result.
Python pandas dataframe apply result of function to multiple columns ...
WebThe moment you're forced to iterate over a DataFrame, you've lost all the reasons to use one. You may as well store a list and then use a for loop. Of course, the answer to this question is pd.DataFrame((f(v) for v in s.tolist()), columns=['len', 'slice']) and it works perfectly, but I don't think it is going to solve your actual problem. The ... WebFor Dask, applying the function to the data and collating the results is virtually identical: import dask.dataframe as dd ddf = dd.from_pandas (df, npartitions=2) # here 0 and 1 refer to the default column names of the resulting dataframe res = ddf.apply (pandas_wrapper, axis=1, result_type='expand', meta= {0: int, 1: int}) # which are renamed ... flooding zones in houston
Pandas groupby apply vs transform with specific functions
WebMar 5, 2024 · Value. Description "expand" Values of list-like results (e.g. [1,2,3]) will be placed in separate columns. "reduce" Values of list-like results will be reduced to a single Series. "broadcast" Values of list-like results will be separated out into columns, but unlike "expand", the column names will be retained. None WebOct 17, 2024 · Answer. This code works in pandas version 0.23.3, properly you just need to run pip install --upgrade pandas in your terminal. Or. You can accomplish it without the result_type as follows: 14. 1. def get_list(row): 2. return pd.Series( [i for i in range(5)]) WebApr 4, 2024 · If func returns a Series object the result will be a DataFrame. Key Points. Applicable to Pandas Series; Accepts a function; ... We can explode the list into multiple columns, one element per column, by defining the result_type parameter as expand. df.apply(lambda x: x['name'].split(' '), axis = 1, result_type = 'expand') flood in hindi