progress_apply

progress_apply(data, func, show_progress=True, desc='Processing...', **kwargs)

Adds a progress bar to pandas apply().

Parameters

Name	Type	Description	Default
data	pd.core.groupby.generic.DataFrameGroupBy	The data parameter is a pandas DataFrameGroupBy object. It represents a grouped DataFrame, where the data is grouped based on one or more columns.	required
func	Callable	The func parameter is a callable function that will be applied to each group in the data DataFrameGroupBy object. This function will be applied to each group separately.	required
show_progress	bool	A boolean value indicating whether to show the progress bar or not. If set to True, a progress bar will be displayed while the function is being applied. If set to False, no progress bar will be displayed.	True
desc	str	The desc parameter is used to provide a description for the progress bar. It is displayed as a prefix to the progress bar.	'Processing...'
**kwargs		The **kwargs parameter is a dictionary of keyword arguments that are passed to the func function.	{}

Returns

Type	Description
pd.DataFrame	The result of applying the given function to the grouped data.

Examples:

import pytimetk as tk
import pandas as pd   

df = pd.DataFrame({
    'A': ['foo', 'bar', 'foo', 'bar', 'foo', 'bar'],
    'B': [1, 2, 3, 4, 5, 6]
})

grouped = df.groupby('A')

result = grouped.progress_apply(lambda df: df['B'].sum())
result

A
bar    12
foo     9
dtype: int64