pandas.Series.asfreq

http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.asfreq.html#pandas.Series.asfreq

Series.asfreq(freq, method=None, how=None, normalize=False, fill_value=None)

参数

参数 描述 freq : DateOffset object, or string method : {‘backfill’/’bfill’, ‘pad’/’ffill’}, default None 设置如何填充，前填充或者后填充 how : {‘start’, ‘end’}, default end normalize : bool, default False fill_value: scalar, optional 设置填充值

返回

converted : type of caller

例子

>>> index = pd.date_range('1/1/2000', periods=4, freq='T')#生成4个1分钟间隔的序列作为索引>>> series = pd.Series([0.0, None, 2.0, 3.0], index=index)# 以刚才的时间序列为索引生成新的序列>>> df = pd.DataFrame({'s':series})# 转换成数据框>>> df                       s2000-01-01 00:00:00    0.02000-01-01 00:01:00    NaN 2000-01-01 00:02:00    2.02000-01-01 00:03:00    3.0

>>> df.asfreq(freq='30S', fill_value=9.0)//空值使用9来填充                       s2000-01-01 00:00:00    0.02000-01-01 00:00:30    9.02000-01-01 00:01:00    NaN 2000-01-01 00:01:30    9.02000-01-01 00:02:00    2.02000-01-01 00:02:30    9.02000-01-01 00:03:00    3.0

>>> df.asfreq(freq='30S', method='bfill')# 空值使用后一位填充                       s2000-01-01 00:00:00    0.02000-01-01 00:00:30    NaN2000-01-01 00:01:00    NaN2000-01-01 00:01:30    2.02000-01-01 00:02:00    2.02000-01-01 00:02:30    3.02000-01-01 00:03:00    3.0