How to Select Data from a pandas DataFrame Based on Multiple Complex Criteria?

Selecting with Complex Criteria from pandas.DataFrame

Consider the following DataFrame:

import pandas as pd
from random import randint

df = pd.DataFrame({'A': [randint(1, 9) for x in range(10)],
                   'B': [randint(1, 9)*10 for x in range(10)],
                   'C': [randint(1, 9)*100 for x in range(10)]})

To select values from 'A' for which corresponding values for 'B' are greater than 50 and 'C' is not equal to 900, we can utilize Pandas' methods and idioms.

We begin by applying column operations to obtain Boolean Series objects:

df["B"] > 50
(df["B"] > 50) & (df["C"] != 900)

These Series represent the conditions we are interested in. We can then index into the DataFrame using these conditions to filter the data:

df["A"][(df["B"] > 50) & (df["C"] != 900)]

Alternatively, we can use .loc to achieve the same result:

df.loc[(df["B"] > 50) & (df["C"] != 900), "A"]

This method provides more control and allows for a more customizable indexing experience.

The resulting DataFrame will contain only the values of 'A' that satisfy the specified criteria.

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