Convert Unix epoch time to datetime in Pandas

Question

I have been searching for a long time to find a solution to my problem.

I get the data from the column I want using the below 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)

I get the output

10    1.513753e+09
11    1.513753e+09
12    1.513753e+09
Name: Time, dtype: float64

I want to convert this time into readable time so I can input it into the x axis of a matplotlib graph.

real_x1 = datetime.datetime.strptime(str(unix_x1), '%Y-%m-%d %H:%M:%S')

I get the error

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'

how do I get this unix time to output into a readable format for a user?

I am a little new to code so if you answer, could you please explain the reasoning if you can?

Answer 1

Pandas can read unix epoch time, use unit parameter

pd.to_datetime('1.513753e+09', unit = 's')

Timestamp('2017-12-20 06:56:40')

You can pass your column using

pd.to_datetime(df[<your_datetime_column>], unit = 's')