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pd.cut in pandas

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Famous Flamingo answered on October 20, 2020 Popularity 10/10 Helpfulness 2/10

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>>> pd.qcut(range(5), 4, labels=False)
array([0, 0, 1, 2, 3])

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Source: pandas.pydata.org

Tags: pandas python

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Contributed on Oct 20 2020

Famous Flamingo

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# Bin edges that will be used to "cut" the data into groups
bin_edges = [ 2.720000,3.110000 , 3.210000, 3.320000, 4.010000]

# Labels for the four acidity level groups
# Notice Acidity level is higher for lower pH levels
bin_names = [ "HIGH", "Above_Average", "below_Average", "LOW"
             
# creating New column with the cuts
df['acidity_levels'] = pd.cut(df['pH'], bin_edges, labels=bin_names)

# acidity_levels is the new column
# pH is the column to be cut or used as reference
# bin_edges represents the limits of four intervals in pH column
# bin_names represents the label of acertain interval containing a certain pH value

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Contributed on Dec 31 2022

Mahmoud Amin

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pd.cut in pandas

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>>> pd.qcut(range(5), 3, labels=["good", "medium", "bad"])
... 
[good, good, medium, bad, bad]
Categories (3, object): [good < medium < bad]

Popularity 10/10 Helpfulness 2/10 Language python

Source: pandas.pydata.org

Tags: pandas pa

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Contributed on Oct 20 2020

Famous Flamingo

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