python - Pandas: Using Unix epoch timestamp as Datetime index -


my application involves dealing data (contained in csv) of following form:

epoch (number of seconds since jan 1, 1970), value 1368431149,20.3 1368431150,21.4 ..

currently read csv using numpy loadtxt method (can use read_csv pandas). series converting timestamps field follows:

timestamp_date=[datetime.datetime.fromtimestamp(timestamp_column[i]) in range(len(timestamp_column))]

i follow setting timestamp_date datetime index dataframe. tried searching @ several places see if there quicker (inbuilt) way of using these unix epoch timestamps, not find any. lot of applications make use of such timestamp terminology.

  1. is there inbuilt method handling such timestamp formats?
  2. if not, recommended way of handling these formats?

convert them datetime64[s]:

np.array([1368431149, 1368431150]).astype('datetime64[s]') # array([2013-05-13 07:45:49, 2013-05-13 07:45:50], dtype=datetime64[s])

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