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import numpy as np
import pandas as pd
from tqdm.auto import tqdm
df = pd.DataFrame(np.random.randint(0, 100, (100000, 6)))
# Register `pandas.progress_apply` and `pandas.Series.map_apply` with `tqdm`
# (can use `tqdm.gui.tqdm`, `tqdm.notebook.tqdm`, optional kwargs, etc.)
tqdm.pandas(desc="my bar!")
# Now you can use `progress_apply` instead of `apply`
# and `progress_map` instead of `map`
df.progress_apply(lambda x: x**2)
# can also groupby:
# df.groupby(0).progress_apply(lambda x: x**2)
# -- Source code for `tqdm_pandas` (really simple!)
# def tqdm_pandas(t):
# from pandas.core.frame import DataFrame
# def inner(df, func, *args, **kwargs):
# t.total = groups.size // len(groups)
# def wrapper(*args, **kwargs):
# t.update(1)
# return func(*args, **kwargs)
# result = df.apply(wrapper, *args, **kwargs)
# t.close()
# return result
# DataFrame.progress_apply = inner
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