Python – 使用 filter() 创建列子集
pythonserver side programmingprogramming更新于 2025/10/27 14:04:17
要创建列子集，我们可以使用 filter()。通过此方法，我们可以使用 like 运算符过滤具有相似模式的列值。首先，让我们创建一个包含 3 列的 DataFrame −
dataFrame = pd.DataFrame({"Product": ["SmartTV", "ChromeCast", "Speaker", "Earphone"],"Opening_Stock": [300, 700, 1200, 1500],"Closing_Stock": [200, 500, 1000, 900]})
现在，让我们创建一个包含多列的子集 −
dataFrame[['Opening_Stock','Closing_Stock']]
创建一个具有类似模式名称的子集 −
dataFrame.filter(like='Open')
示例
以下是完整代码 −
import pandas as pd
dataFrame = pd.DataFrame({"Product": ["SmartTV", "ChromeCast", "Speaker", "Earphone"],"Opening_Stock": [300, 700, 1200, 1500],"Closing_Stock": [200, 500, 1000, 900]})
print"DataFrame...\n",dataFrame
print"\nDisplaying a subset using indexing operator:\n",dataFrame[['Product']]
print"\nDisplaying a subset with multiple columns:\n",dataFrame[['Opening_Stock','Closing_Stock']]
print"\nDisplaying a subset with similarly patterned names:\n",dataFrame.filter(like='Open')
输出
这将产生以下输出 −
DataFrame... Closing_Stock Opening_Stock Product 0 200 300 SmartTV 1 500 700 ChromeCast 2 1000 1200 Speaker 3 900 1500 Earphone Displaying a subset using indexing operator: Product 0 SmartTV 1 ChromeCast 2 Speaker 3 Earphone Displaying a subset with multiple columns: Opening_Stock Closing_Stock 0 300 200 1 700 500 2 1200 1000 3 1500 900 Displaying a subset with similarly patterned names: Opening_Stock 0 300 1 700 2 1200 3 1500
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有用资源
python 参考教程 - 该教程包含有关 python 的更多信息:https://www.cainiaomax.com/python/
