Can Operator Chaining Be Used to Filter DataFrame Rows in Pandas?

Pandas: Filter DataFrame Rows with Operator Chaining

Many Pandas operations can be performed through operator chaining, including groupby, aggregate, and apply. However, filtering rows has typically been done using traditional bracket indexing.

df_filtered = df[df['column'] == value]

This approach requires assigning df to a variable before filtering, which can be cumbersome. Is there a more convenient way to chain filter operations?

Answer:

While the last line of code provided in the question is unclear, "chained" filtering can be achieved by chaining criteria in the boolean index.

df[(df.A == 1) & (df.D == 6)]

Additionally, users can define their own mask method and use it for filtering:

def mask(df, key, value):
    return df[df[key] == value]

pandas.DataFrame.mask = mask

df = pandas.DataFrame(np.random.randint(0, 10, (4,4)), index=list('abcd'), columns=list('ABCD'))

df.mask('A', 1)
df.mask('A', 1).mask('D', 6)

This allows for convenient chaining of filter operations.

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