Question

我想基于其他列（X，Y）中的值设置熊猫数据框中的列（Z）的值：

以下是示例代码：

for i, row in df.iterrows():
    #print(i, row['Z'])
    if row['X'] == 1 and row['Y'] == 0:
        row['Z'] = 1
    if row['X'] == 0 and row['Y'] == 1:
        row['Z'] = 0
    if row['X'] == 0 and row['Y'] == 0:
        row['Z'] = 2
    if row['X'] == 1 and row['Y'] == 1:
        row['Z'] = 3

这样做的方式是什么？

Answer 1

将numpy.select与&一起用于按位AND：

m1 = df['X'] == 0
m2 = df['X'] == 1
m3 = df['Y'] == 0
m4 = df['Y'] == 1

df['Z'] = np.select([m2 & m3, m1 & m4, m1 & m3, m2 & m4], [1,0,2,3])

Answer 2

如果只想编码Z值，则可以解决

df['Z'] = df['X'] + 2 * df['Y']

如果不是这种情况，请在之后使用pandas.Series.map

df['Z'] = df['Z'].map({1:0, 2:1, 0:2, 3:3})

根据其他列中的值设置pandas数据框中的列值

2 个答案: