python - pandas read_csv() 输入本地日期时间字符串，tz_convert to UTC

Question

我正在使用 pandas-0.8rc2 读取包含两列本地化的输入 CSV缺少 UTC 偏移信息的日期时间字符串，需要数据帧系列正确转换为 UTC。

我一直在尝试解决方法来缓解时间戳列都没有的事实代表索引，它们是数据。 tz_localize 和 tz_convert 显然有效仅在系列/数据框的索引上，而不是列。我非常愿意学习更好的方法来做到这一点，而不是以下代码:

# test.py
import pandas

# input.csv:
# starting,ending,measure
# 2012-06-21 00:00,2012-06-23 07:00,77
# 2012-06-23 07:00,2012-06-23 16:30,65
# 2012-06-23 16:30,2012-06-25 08:00,77
# 2012-06-25 08:00,2012-06-26 12:00,0
# 2012-06-26 12:00,2012-06-27 08:00,77

df = pandas.read_csv('input.csv', parse_dates=[0,1])
print df

ser_starting = df.starting
ser_starting.index = ser_starting.values
ser_starting = ser_starting.tz_localize('US/Eastern')
ser_starting = ser_starting.tz_convert('UTC')

ser_ending = df.ending
ser_ending.index = ser_ending.values
ser_ending = ser_ending.tz_localize('US/Eastern')
ser_ending = ser_ending.tz_convert('UTC')

df.starting = ser_starting.index
print df
df.ending = ser_ending.index
print df

其次，代码遇到了一些奇怪的行为。它改变了时间戳第二次赋值回数据框的数据，顺序是否为df.starting 或 df.ending:

$ python test.py 
              starting               ending  measure
0  2012-06-21 00:00:00  2012-06-23 07:00:00       77
1  2012-06-23 07:00:00  2012-06-23 16:30:00       65
2  2012-06-23 16:30:00  2012-06-25 08:00:00       77
3  2012-06-25 08:00:00  2012-06-26 12:00:00        0
4  2012-06-26 12:00:00  2012-06-27 08:00:00       77
             starting               ending  measure
0 2012-06-21 04:00:00  2012-06-23 07:00:00       77
1 2012-06-23 11:00:00  2012-06-23 16:30:00       65
2 2012-06-23 20:30:00  2012-06-25 08:00:00       77
3 2012-06-25 12:00:00  2012-06-26 12:00:00        0
4 2012-06-26 16:00:00  2012-06-27 08:00:00       77
Traceback (most recent call last):
  File "test.py", line 28, in <module>
    print df
  File "/path/to/lib/python2.7/site-packages/pandas/core/frame.py", line 572, in __repr__
    if self._need_info_repr_():
  File "/path/to/lib/python2.7/site-packages/pandas/core/frame.py", line 560, in _need_info_repr_
    self.to_string(buf=buf)
  File "/path/to/lib/python2.7/site-packages/pandas/core/frame.py", line 1207, in to_string
    formatter.to_string(force_unicode=force_unicode)
  File "/path/to/lib/python2.7/site-packages/pandas/core/format.py", line 200, in to_string
    fmt_values = self._format_col(i)
  File "/path/to/lib/python2.7/site-packages/pandas/core/format.py", line 242, in _format_col
    space=self.col_space)
  File "/path/to/lib/python2.7/site-packages/pandas/core/format.py", line 462, in format_array
    return fmt_obj.get_result()
  File "/path/to/lib/python2.7/site-packages/pandas/core/format.py", line 589, in get_result
    fmt_values = [formatter(x) for x in self.values]
  File "/path/to/lib/python2.7/site-packages/pandas/core/format.py", line 597, in _format_datetime64
    base = stamp.strftime('%Y-%m-%d %H:%M:%S')
ValueError: year=1768 is before 1900; the datetime strftime() methods require year >= 1900

打印语句只是为了演示问题。不正确的值如果我避免 repr 和其他调用的方法，将无一异常(exception)地执行strftime.

奇怪的是，如果我一直调用 df.{starting,ending} 赋值在 repl 中，我通常会得到一个带有时间戳的正确数据帧:

In [151]: df
Out[151]: 
             starting              ending  measure
0 2012-06-21 04:00:00 2012-06-23 11:00:00  77
1 2012-06-23 11:00:00 2012-06-23 20:30:00  65
2 2012-06-23 20:30:00 2012-06-25 12:00:00  77
3 2012-06-25 12:00:00 2012-06-26 16:00:00   0
4 2012-06-26 16:00:00 2012-06-27 12:00:00  77

这是不可重复的，AFAICT，我无法描述调用的确切顺序它超越了上面的 ValueError，但确实如此

如果我遇到错误，我将不胜感激，或者这是不受支持的 API 用法。

如上所述，我宁愿学习更好地使用 pandas API避免这样做。

Answer 1

看来这里可能潜伏着一个错误，所以我在这里创建了一个问题，很快就会看一下并让你知道:

https://github.com/pydata/pandas/issues/1518

编辑:您遇到的错误已修复。我现在也要解决 1900 年前的显示问题。