Convert unix time to readable date in pandas dataframe

Question

I have a dataframe with unix times and prices in it  I want to convert the index column so that it shows in human readable dates    So for instance I have date as 1349633705 in the index column but I d want it to show as 10 07 2012  or at least 10 07 2012 18 15     For some context  here is the code I m working with and what I ve tried already   import json import urllib2 from datetime import datetime response   urllib2 urlopen  http   blockchain info charts market-price  amp format json   data   json load response     df   DataFrame data  values    df columns     date   price    convert dates  df date   df date apply lambda d  datetime strptime d    Y- m- d    df index   df date      As you can see I m using df date   df date apply lambda d  datetime strptime d    Y- m- d    here which doesn t work since I m working with integers  not strings  I think I need to use datetime date fromtimestamp but I m not quite sure how to apply this to the whole of df date    Thanks

User · Answer

Alternatively  by changing a line of the above code     df date   df date apply lambda d  datetime strptime d    Y- m- d    df date   df date apply lambda d  datetime datetime fromtimestamp int d   strftime   Y- m- d      It should also work

User · Answer

If you try using    df DATE FIELD   pd to datetime df DATE FIELD     unit  s         and receive an error         pandas tslib OutOfBoundsDatetime  cannot convert input with unit  s     This means the DATE FIELD is not specified in seconds    In my case  it was milli seconds - EPOCH time    The conversion worked using below   df DATE FIELD   pd to datetime df DATE FIELD  unit  ms

User · Answer

These appear to be seconds since epoch   In  20   df   DataFrame data  values     In  21   df columns     date   price    In  22   df Out 22     lt class  pandas core frame DataFrame  gt  Int64Index  358 entries  0 to 357 Data columns  total 2 columns   date     358  non-null values price    358  non-null values dtypes  float64 1   int64 1   In  23   df head   Out 23             date  price 0  1349720105  12 08 1  1349806505  12 35 2  1349892905  12 15 3  1349979305  12 19 4  1350065705  12 15 In  25   df  date     pd to datetime df  date   unit  s    In  26   df head   Out 26                     date  price 0 2012-10-08 18 15 05  12 08 1 2012-10-09 18 15 05  12 35 2 2012-10-10 18 15 05  12 15 3 2012-10-11 18 15 05  12 19 4 2012-10-12 18 15 05  12 15  In  27   df dtypes Out 27    date     datetime64 ns  price           float64 dtype  object

User · Answer

Assuming we imported pandas as pd and df is our dataframe  pd to datetime df  date    unit  s     works for me

[python] Convert unix time to readable date in pandas dataframe

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