Python Pandas——查找列的最大值并返回其对应的行值
在 Pandas中寻找列的最大值并返回其对应的行值,我们可以使用df.loc[df[col].idxmax()]。让我们举个例子来加深理解。
步骤
- 创建一个二维、尺寸可变、具有异构表格数据的 df。
- 打印输入 DataFrame(数据框),df。
- 初始化一个变量,col,以找到该列的最大值。
- 使用 df.loc[df[col].idxmax()] 找到最大值及其对应的行。
- 打印步骤 4 的输出。
示例
import pandas as pd df = pd.DataFrame( { "x": [5, 2, 7, 0], "y": [4, 7, 5, 1], "z": [9, 3, 5, 1] } ) print "Input DataFrame is:\n", df col = "x" max_x = df.loc[df[col].idxmax()] print "Maximum value of column ", col, " and its corresponding row values:\n", max_x col = "y" max_x = df.loc[df[col].idxmax()] print "Maximum value of column ", col, " and its corresponding row values:\n", max_x col = "z" max_x = df.loc[df[col].idxmax()] print "Maximum value of column ", col, " and its corresponding row values:\n", max_x
输出
Input DataFrame is: x y z 0 5 4 9 1 2 7 3 2 7 5 5 3 0 1 1 Maximum value of column x and its corresponding row values: x 7 y 5 z 5 Name: 2, dtype: int64 Maximum value of column y and its corresponding row values: x 2 y 7 z 3 Name: 1, dtype: int64 Maximum value of column z and its corresponding row values: x 5 y 4 z 9 Name: 0, dtype: int64
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