python - pandas 将字符串评估为数字

Question

假设 df 为；

data = {'duration':['1week 3day 2hour 4min 23', '2hour 4min 23sec', '2hour 4min', np.nan, '', '23sec']}
df = pd.DataFrame(data)

我正在尝试将持续时间计算为秒数总和。将值替换为:

df['duration'] = df['duration'].str.replace('week', '*604800+') \
                                                                 .str.replace('day', '*604800+') \
                                                                 .str.replace('hour', '*3600+') \
                                                                 .str.replace('min', '*60+') \
                                                                 .str.replace('sec', '')  \
                                                                 .str.replace(' ', '')

但无法运行 eval 函数，例如(pd.eval、apply.eval、eval 等)。某些单元格以“+”号结尾或其他字符串/不存在问题..有帮助吗？

Ps:这不是一个重复的问题。

Answer 1

您可以使用正则表达式与自定义函数相结合，将周替换为 7 天，并在单独的数字上添加秒(您可以添加其他单位)。然后转换to_timedelta :

def change_units(m):
    d = {'week': (7, 'days'), '': (1, 's')}
    _, i, period = m.groups()
    factor, txt = d[period]
    return f'{factor*int(i)}{txt}'
    
df['delta'] = pd.to_timedelta(df['duration'].str.replace(r'((\d)\s*(week|)\b)',
                                                         replace, regex=True))

输出:

                   duration            delta
0  1week 3day 2hour 4min 23 10 days 02:04:23
1          2hour 4min 23sec  0 days 02:04:23
2                2hour 4min  0 days 02:04:00
3                       NaN              NaT
4                                        NaT
5                     23sec  0 days 00:00:23

然后您可以从 TimeDelta 对象中受益，例如转换为 total_seconds :

pd.to_timedelta(df['duration'].str.replace(r'((\d)\s*(week|)\b)',
                                           change_units, regex=True)
               ).dt.total_seconds()

输出:

0    871463.0
1      7463.0
2      7440.0
3         NaN
4         NaN
5        23.0
Name: duration, dtype: float64