title: Convert Unix epoch time to datetime in Pandas
body: <p>I have been searching for a long time to find a solution to my problem.</p>
  
  <p>I get the data from the column I want using the below code</p>
  
  <pre><code>import pandas as pd
  df = pd.read_excel("Live_data_test.xlsx","Sheet1")
  
  number_of_entries = len(df.loc[:, 'Time'])
  number_of_entries_last_3 = number_of_entries - 3
  unix_x1 = df.loc[number_of_entries_last_:number_of_entries, 'Time']
  print(unix_x1)
  </code></pre>
  
  <p>I get the output</p>
  
  <pre><code>10    1.513753e+09
  11    1.513753e+09
  12    1.513753e+09
  Name: Time, dtype: float64
  </code></pre>
  
  <p>I want to convert this time into readable time so I can input it into the x axis of a matplotlib graph.</p>
  
  <pre><code>real_x1 = datetime.datetime.strptime(str(unix_x1), '%Y-%m-%d %H:%M:%S')
  </code></pre>
  
  <p>I get the error</p>
  
  <pre><code>ValueError: time data '10    1.513753e+09\n11    1.513753e+09\n12    1.513753e+09\nName: Time, dtype: float64' does not match format '%Y-%m-%d %H:%M:%S'
  </code></pre>
  
  <p>how do I get this unix time to output into a readable format for a user?</p>
  
  <p>I am a little new to code so if you answer, could you please explain the reasoning if you can?</p>