数据框降序过滤

问题描述

我有一个数据框，例如

Index   Results  Price
0       Buy      10
1       Sell     11
2       Buy      12
3       Neutral  13
4       Buy      14
5       Sell     15

我想最终以降序返回买入"和卖出"结果的第一个连续组合的价格差.这样第一个输出的差为1，第二个输出的差为3.

I would like to ultimately return the price difference for the first continuous combination of Buy and then Sell Results in a descending manner. Such that the first output is a difference of 1, second output 3.

for buy in df:
        if buy:
              df['Buy Price'] = df['Price']
           for sell in df:
                  if sell:
                      df['Sell Price'] = df['Price']
                      df['Difference'] = df['Sell Price'] - df['Buy Price']

所需的输出

Index Results Price Difference
0     Buy     10
1     Sell    11    1
2     Buy     12
3     Neutral 13
4     Buy     14
5     Sell    15    3

我试图实现一个计数器，但是没有运气.预先感谢.

I have attempted to implement a counter but with no such luck. Thanks in advance.

推荐答案

您可以使用带有两个布尔标志的手动循环.在这里，我使用numba添加一些优化元素:

You can use a manual loop with a couple of Boolean flags. Here I use numba to add some element of optimisation:

from numba import njit

@njit
def get_diffs(results, prices):
    res = np.full(prices.shape, np.nan)
    prev_one, prev_zero = True, False
    for i in range(len(results)):
        if prev_one and (results[i] == 0):
            price_start = prices[i]
            prev_zero, prev_one = True, False
        elif prev_zero and (results[i] == 1):
            res[i] = prices[i] - price_start
            prev_zero, prev_one = False, True
    return res

results = df['Results'].map({'Buy': 0, 'Sell': 1})

df['Difference'] = get_diffs(results.values, df['Price'].values)

print(df)

   Index  Results  Price  Difference
0      0      Buy     10         NaN
1      1     Sell     11         1.0
2      2      Buy     12         NaN
3      3  Neutral     13         NaN
4      4      Buy     14         NaN
5      5     Sell     15         3.0

这篇关于数据框降序过滤的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！