When I do
df.dtypes
, appears this
utc_time int64
one example of utc_time is: 1536444323321
I found a code here to change utc_time (epoch) to day of week
df['Week_Day'] =
datetime.fromtimestamp(df['utc_time']/1000).strftime("%A")
But i receive this error:
TypeError Traceback (most recent call
last)
<ipython-input-124-b3277c232078> in <module>()
2 # df['intage'] = df['utc_time'].astype(int)
3 # df['intage'] = df['utc_time'].dt.days
----> 4 df['Week_Day'] =
datetime.fromtimestamp(df['utc_time']/1000).strftime("%A")
/anaconda3/lib/python3.6/site-packages/pandas/core/series.py in
wrapper(self)
115 return converter(self.iloc[0])
116 raise TypeError("cannot convert the series to "
--> 117 "{0}".format(str(converter)))
118
119 return wrapper
TypeError: cannot convert the series to <class 'int'>
First, convert your column/Series to a datetime object. df['column'] = pd.to_datetime(df['column'])
Then, you have two options:
Option 1 - use the .dt
accessor: df['column'].dt.weekday
gives you the weekdays as integers
Option 2 - use the pandas Timestamp
object: df['column'].apply(pd.Timestamp.weekday)
But I really recommend option 1.
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