pandas.DataFrame.apply¶
- DataFrame.apply(func, axis=0, broadcast=False, raw=False, args=(), **kwds)¶
Applies function along input axis of DataFrame. Objects passed to functions are Series objects having index either the DataFrame’s index (axis=0) or the columns (axis=1). Return type depends on whether passed function aggregates
- func : function
- Function to apply to each column
- axis : {0, 1}
- 0 : apply function to each column 1 : apply function to each row
- broadcast : bool, default False
- For aggregation functions, return object of same size with values propagated
- raw : boolean, default False
- If False, convert each row or column into a Series. If raw=True the passed function will receive ndarray objects instead. If you are just applying a NumPy reduction function this will achieve much better performance
- args : tuple
- Positional arguments to pass to function in addition to the array/series
Additional keyword arguments will be passed as keywords to the function
>>> df.apply(numpy.sqrt) # returns DataFrame >>> df.apply(numpy.sum, axis=0) # equiv to df.sum(0) >>> df.apply(numpy.sum, axis=1) # equiv to df.sum(1)
DataFrame.applymap: For elementwise operations
applied : Series or DataFrame