Merge rows which have the same date within a data frame

Question

I have a data.frame as follows:

         timestamp     index   negative  positive sentiment

            <dttm>      <dbl>    <dbl>    <dbl>     <dbl>

1 2015-10-29 15:00:10     0       11       10        -1

2 2015-10-29 17:26:48     0        1        5         4

3 2015-10-29 17:30:07     0       10       22        12

4 2015-10-29 20:13:22     0        5        6         1

5 2015-10-30 14:25:26     0        3        2        -1

6 2015-10-30 18:22:30     0       14       15         1

7 2015-10-31 14:16:00     0       10       23        13

8 2015-11-02 20:30:18     0       14        7        -7

9 2015-11-03 14:15:00     0        8       26        18

10 2015-11-03 16:52:30    0       12       34        22

I would like to know if there is a possibility to merge rows with equal days such that i have a scoring for each day, since I have absolutely no clue how to approach this problem because I dont even know how to unlist each date and write a function which merges only equal dates, because the time differs in each day . I would like to obtain a data.frame which has the following form:

           timestamp     index   negative  positive sentiment                

            <dttm>      <dbl>    <dbl>    <dbl>     <dbl>

         1 2015-10-29     0       27       43        16

         2 2015-10-30     0        3        2        -1

         3 2015-10-31     0       17       17         0

         4 2015-11-02     0       14        7        -7

         5 2015-11-03     0       20       60        40

Is there any possibility to get around to this result? I would be thankful for any hint.

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Answer 1

You can use aggregate() to do this. Before doing that, you'll need to show that it should sort according to the day, ignoring the exact time-point.

I will assume you have your data stored as df:

aggregate(df[ ,2:5], FUN="sum", by=list(as.Date(df$timestamp, "%Y-%m-%d")))

Merge rows which have the same date within a data frame

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