熊貓-選擇多列

Question

注意：曾經有人問過類似的問題，但它並不能完全回答我的問題。

如何基於滿足某些布爾條件的大量列，對具有許多列的pandas數據框進行子集設置。

現在，我必須執行以下操作：

df[(df.column4 > a1) | (df.column23 < a2) | (df.column27 == a3) | ... 
    (df.column56 > a21) | (df.column72 < a22)]

謝謝

Answer 1

您必須以一種或另一種方式指定您的條件。 您可以為每種情況創建單獨的蒙版，最終將其減少為單個蒙版：

import seaborn.apionly as sns
import operator
import numpy as np

# Load a sample dataframe to play with
df = sns.load_dataset('iris')

# Define individual conditions as tuples
# ([column], [compare_function], [compare_value])
cond1 = ('sepal_length', operator.gt, 5)
cond2 = ('sepal_width', operator.lt, 2)
cond3 = ('species', operator.eq, 'virginica')
conditions = [cond1, cond2, cond3]

# Apply those conditions on the df, creating a list of 3 masks
masks = [fn(df[var], val) for var, fn, val in conditions]
# Reduce those 3 masks to one using logical OR
mask = np.logical_or.reduce(masks)

result = df.ix[mask]

當我們將其與“手工制作”選項進行比較時，我們發現它們是相同的：

result_manual = df[(df.sepal_length>5) | (df.sepal_width<2) | (df.species == 'virginica')]
result_manual.equals(result) # == True