Question

我有一个函数返回一个由Series值数组组成的熊猫pd.Timestamp实例的索引值作为ISO周值。

import numpy as np
import pandas as pd

timestamps = [pd.Timestamp('2014-01-01'), pd.Timestamp('2014-02-01'), pd.Timestamp('2014-02-01')]
quantities = [1.0, 1.0, 1.0]
series = pd.Series(quantities, index=timestamps)

def timestamps_iso() -> np.array:
    timestamps_iso = []
    for timestamp in series.index:
        timestamp_iso = timestamp.isocalendar()[1]
        if timestamp_iso == 53: # fix ISO week number 53.
            timestamp_iso = np.random.choice([52, 1])
        timestamps_iso.append(timestamp_iso)
    return np.array(timestamps_iso)

请问这可以做得更快，还是可以采用更熊猫的风格？当索引很大时，要花很多时间。

感谢您的帮助。

Answer 1

您的问题表示月份值，但代码表示星期值。我认为您正在寻找星期值。您可以使用.week访问日期时间序列中的星期数：

In [1]: timestamps = [pd.Timestamp('2014-01-01'), pd.Timestamp('2014-02-01'), pd.Timestamp('2014-02-01')] 
   ...: quantities = [1.0, 1.0, 1.0] 
   ...: series = pd.Series(quantities, index=timestamps)                                                                                                                                                                                             

In [2]: series.index.week                                                                                                                                                                                                                            
Out[2]: Int64Index([1, 5, 5], dtype='int64')

大熊猫：快速将时间戳索引转换为ISO周

1 个答案: