I have a list of tweet sentiment values and the timestamps of the tweets. I want to get the daily mean values, but I cannot get rid of the timestamp values so my groupby is not working.
2 Answers
You could do this:
initial df:
Date Sentiment
0 2020-01-31 00:00:00+00:00 0.6369
1 2020-01-31 01:00:00+00:00 0.3612
Code:
df['Date']=pd.to_datetime(df['Date'], utc=False)
df['Date']=df['Date'].dt.date
df.groupby('Date')['Sentiment'].mean()
Output:
Date
2020-01-31 0.49905
Name: Sentiment, dtype: float64
final df:
Date Sentiment
0 2020-01-31 0.6369
1 2020-01-31 0.3612
Comments
Found it: https://stackoverflow.com/a/39400136/5822871
df = df.groupby([df['Date_Time'].dt.date]).mean()
Datestored as string or as datetime ? If it's a string, convert it into datetime. You will be able to filter the df then. You can check this question if you want to know more about coneverting string to datetime.