按日期时间列将Pandas Dataframe的所有元素分组

Question

Imagine a Dataframe with 3 columns:

index
A: datetime
B: value 1 or 2

There could be more rows for a specific day. I want to make a new dataframe which summarize the value for each day. So:

index
A: datetime (1 day)
B: amount of rows which contained value 1 in first dataframe
C: amount of rows which contained value 2 in first dataframe

Sample data:

Answer 1

You could use groupby with something like:

df['count_sentiment'] = df['Sentiment'] == 'positive' # equal to 1 iff the row is positive
df[['Date', 'Likes', 'Rts', 'count_sentiment']].groupby(by='Date').sum()

where df is your dataframe. This will group by Date. If you want to group by day, create another column Day with the day you want to group with and replace groupby(by='Date') by groupby(by='Day')