我正在努力做到以下几点:
df['SR1'] = df['Open'].pct_change(1)
df['SR2'] = df['Open'].pct_change(2)
df['SR3'] = df['Open'].pct_change(3)
df['SR4'] = df['Open'].pct_change(4)
df['SR5'] = df['Open'].pct_change(5)
df['SR6'] = df['Open'].pct_change(6)
df['SR7'] = df['Open'].pct_change(7)
df['SR8'] = df['Open'].pct_change(8)
df['SR9'] = df['Open'].pct_change(9)
df['SR10'] = df['Open'].pct_change(10)
df['SR11'] = df['Open'].pct_change(11)
df['SR12'] = df['Open'].pct_change(12)
df['SR13'] = df['Open'].pct_change(13)
df['SR14'] = df['Open'].pct_change(14)
df['SR15'] = df['Open'].pct_change(15)
df['SR16'] = df['Open'].pct_change(16)
df['SR17'] = df['Open'].pct_change(17)
df['SR18'] = df['Open'].pct_change(18)
df['SR19'] = df['Open'].pct_change(19)
df['SR20'] = df['Open'].pct_change(20)
df['SR30'] = df['Open'].pct_change(30)
df['SR50'] = df['Open'].pct_change(50)
df['SR70'] = df['Open'].pct_change(70)
df['SR90'] = df['Open'].pct_change(90)
df['SR110'] = df['Open'].pct_change(110)
df['SR130'] = df['Open'].pct_change(130)
df['SR150'] = df['Open'].pct_change(150)
df['SR170'] = df['Open'].pct_change(170)
df['SR190'] = df['Open'].pct_change(190)
df['SR210'] = df['Open'].pct_change(210)
df['SR230'] = df['Open'].pct_change(230)
df['SR250'] = df['Open'].pct_change(250)
它看起来既愚蠢又低效。有没有什么很酷的方法来创建一个函数来循环这个过程?我就是没办法把数字放在pct\u change()的括号里。你知道吗
也许吧
包含所有要处理的索引的
numbers
。你知道吗如果你想提高效率,不要使用循环。你可以将
assign
与词典理解一起使用。你知道吗或不使用f字符串:
计时
稍微快一点使用字典理解。你知道吗
为什么不是一个简单的
for
循环?你知道吗注意:f-string表示法仅适用于Python>;=3.6,相当于
'SR{}'.format(n)
。你知道吗相关问题 更多 >
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