pct_change().dropna()
时间: 2023-05-01 07:03:48 浏览: 95
b'pct_change().dropna()' 是一个 Pandas 库函数的调用,用于计算数据的百分比变化并且去除 NaN 值。具体来说,pct_change() 函数将每个数值与其前一个数值的比率计算出来,然后 dropna() 函数将在计算出来的结果中去除掉 NaN 值。这个函数通常用于对金融数据和时间序列数据进行分析和处理。
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data.pct_change().dropna()
This code calculates the percentage change between each element in a pandas DataFrame or Series with the previous element, and then drops the first row (which will be NaN as there is no previous element to compare it to). The result is a DataFrame or Series with the same shape as the original, but with each value replaced by the percentage change from the previous value.
For example, if we have a DataFrame 'data' with the following values:
| | A | B | C |
|---|---|---|---|
| 0 | 1 | 5 | 9 |
| 1 | 2 | 6 | 10 |
| 2 | 3 | 7 | 11 |
Then running `data.pct_change().dropna()` will give us:
| | A | B | C |
|---|----|---|----|
| 1 | 1.0 | 0.2 | 0.111111 |
| 2 | 0.5 | 0.166667 | 0.1 |
This shows the percentage change between each row and the previous row, with the first row dropped as there is no previous row to compare it to. For example, in column A the percentage change between row 1 and row 0 is 100% (as the value has doubled), and the percentage change between row 2 and row 1 is 50% (as the value has increased by half).
rets = close_px.pct_change().dropna()
这段代码的作用是计算DataFrame对象close_px每一列的百分比变化(即变化率),并将其中含有缺失数据的行(即NaN值所在的行)删除,最终返回一个新的DataFrame对象rets。
具体来说,pct_change()函数用于计算每个元素与其前一个元素之间的变化率,计算公式为:(当前元素 - 前一个元素) / 前一个元素。这里的前一个元素指的是该列中当前元素的前一行元素。dropna()函数则用于删除含有缺失数据的行,即删除含有NaN值的行。
因此,通过这段代码,我们可以获得close_px每一列的变化率,并将其中的缺失数据删除,以便后续的分析和处理。