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法律研究Python - 使用 NumPy 筛选 Pandas DataFrame
NumPy where() 方法可用于筛选 Pandas DataFrame。在 where() 方法中指定条件。首先，让我们使用各个别名导入所需的库
import pandas as pd import numpy as np
现在，我们将使用产品记录创建 Pandas DataFrame
dataFrame = pd.DataFrame({"Product": ["SmartTV", "ChromeCast", "Speaker", "Earphone"],"Opening_Stock": [300, 700, 1200, 1500],"Closing_Stock": [200, 500, 1000, 900]})
使用 NumPy where() 根据 2 个条件筛选 DataFrame
resValues1 = np.where((dataFrame['Opening_Stock']>=700) & (dataFrame['Closing_Stock']< 1000)) print"\nFiltered DataFrame Value = \n",dataFrame.loc[resValues1]
让我们再次使用 NumPy where() 根据 3 个条件筛选 DataFrame
resValues2 = np.where((dataFrame['Opening_Stock']>=500) & (dataFrame['Closing_Stock']< 1000) & (dataFrame['Product'].str.startswith('C')))
示例
以下是完整的代码
import pandas as pd import numpy as np dataFrame = pd.DataFrame({"Product": ["SmartTV", "ChromeCast", "Speaker", "Earphone"],"Opening_Stock": [300, 700, 1200, 1500],"Closing_Stock": [200, 500, 1000, 900]}) print"DataFrame...\n",dataFrame # using numpy where() to filter DataFrame with 2 Conditions resValues1 = np.where((dataFrame['Opening_Stock']>=700) & (dataFrame['Closing_Stock']< 1000)) print"\nFiltered DataFrame Value = \n",dataFrame.loc[resValues1] # using numpy where() to filter DataFrame with 3 conditions resValues2 = np.where((dataFrame['Opening_Stock']>=500) & (dataFrame['Closing_Stock']< 1000) & (dataFrame['Product'].str.startswith('C'))) print"\nFiltered DataFrame Value = \n",dataFrame.loc[resValues2]
输出
将输出以下内容
DataFrame... Closing_Stock Opening_Stock Product 0 200 300 SmartTV 1 500 700 ChromeCast 2 1000 1200 Speaker 3 900 1500 Earphone Filtered DataFrame Value = Closing_Stock Opening_Stock Product 1 500 700 ChromeCast 3 900 1500 Earphone Filtered DataFrame Value = Closing_Stock Opening_Stock Product 1 500 700 ChromeCast
更新于: 14-Sep-2021
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