Python - 使用 filter() 创建列的子集
要创建列的子集，我们可以使用filter().通过这个，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，让我们创建一个具有多列的子集-
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
以下是完整的代码-
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')输出结果这将产生以下输出-
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