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:
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')
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