Merge to dataset according to matching dates

Question

I have 2 datasets with time series.

In the dataset 1, the are 3 columns: Date , price changes , volume . And 1056 rows sorting by dates that start from 01-01-2005 to 31-12-2015 .

In the dataset 2, the are 3 columns: Date , price changes , volume . And 1028 rows sorting by dates that start from 01-01-2005 to 31-12-2015 . But only 1028 rows because there is missing data (ie missing rows).

I would like to erase in dataset 1 the rows with the dates that do not appear in dataset 2.

I have tried this but it does not work:

dataset1[!rownames(dataset1) %in% dataset2$Date, ]

The output has 1056 rows, so it does not erase anything.

Answer 1

You just need to do dataset1[dataset1$Date %in% dataset2$Date, ] :

set.seed(1)
d1 <- as.Date('2015-01-01') + 0:10
x <- sample(1:10, 11, replace = TRUE)
df1 <- data.frame(d1, x)
           d1  x
1  2015-01-01  3
2  2015-01-02  4
3  2015-01-03  6
4  2015-01-04 10
5  2015-01-05  3
6  2015-01-06  9
7  2015-01-07 10
8  2015-01-08  7
9  2015-01-09  7
10 2015-01-10  1
11 2015-01-11  3
d2 <- as.Date('2015-01-01') + seq(0, 10, 3)
y <- sample(1:10, 4)
df2 <- data.frame(d2, y)
df1[df1$d1 %in% df2$d2, ]
           d1  x
1  2015-01-01  3
4  2015-01-04 10
7  2015-01-07 10
10 2015-01-10  1