Import data
## # A tibble: 45,088 × 8
## stock_symbol date open high low close adj_close volume
## <chr> <dttm> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 AAPL 2010-01-04 00:00:00 7.62 7.66 7.58 7.64 6.52 493729600
## 2 AAPL 2010-01-05 00:00:00 7.66 7.70 7.62 7.66 6.53 601904800
## 3 AAPL 2010-01-06 00:00:00 7.66 7.69 7.53 7.53 6.42 552160000
## 4 AAPL 2010-01-07 00:00:00 7.56 7.57 7.47 7.52 6.41 477131200
## 5 AAPL 2010-01-08 00:00:00 7.51 7.57 7.47 7.57 6.45 447610800
## 6 AAPL 2010-01-11 00:00:00 7.6 7.61 7.44 7.50 6.40 462229600
## 7 AAPL 2010-01-12 00:00:00 7.47 7.49 7.37 7.42 6.32 594459600
## 8 AAPL 2010-01-13 00:00:00 7.42 7.53 7.29 7.52 6.41 605892000
## 9 AAPL 2010-01-14 00:00:00 7.50 7.52 7.46 7.48 6.38 432894000
## 10 AAPL 2010-01-15 00:00:00 7.53 7.56 7.35 7.35 6.27 594067600
## # ℹ 45,078 more rows
Apply the following dplyr verbs to your data
Filter rows
## # A tibble: 0 × 8
## # ℹ 8 variables: stock_symbol <chr>, date <dttm>, open <dbl>, high <dbl>,
## # low <dbl>, close <dbl>, adj_close <dbl>, volume <dbl>
Arrange rows
## # A tibble: 45,088 × 8
## stock_symbol date open high low close adj_close volume
## <chr> <dttm> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 TSLA 2010-07-07 00:00:00 1.09 1.11 0.999 1.05 1.05 103825500
## 2 TSLA 2010-07-06 00:00:00 1.33 1.33 1.06 1.07 1.07 103003500
## 3 TSLA 2010-07-12 00:00:00 1.20 1.20 1.13 1.14 1.14 33037500
## 4 TSLA 2010-07-09 00:00:00 1.17 1.19 1.10 1.16 1.16 60759000
## 5 TSLA 2010-07-08 00:00:00 1.08 1.17 1.04 1.16 1.16 115671000
## 6 TSLA 2010-08-12 00:00:00 1.19 1.19 1.16 1.17 1.17 10365000
## 7 TSLA 2010-08-11 00:00:00 1.25 1.26 1.19 1.19 1.19 11964000
## 8 TSLA 2010-07-13 00:00:00 1.16 1.24 1.13 1.21 1.21 40201500
## 9 TSLA 2010-08-13 00:00:00 1.21 1.23 1.18 1.22 1.22 9510000
## 10 TSLA 2010-08-18 00:00:00 1.31 1.31 1.24 1.25 1.25 9019500
## # ℹ 45,078 more rows
## # A tibble: 45,088 × 8
## stock_symbol date open high low close adj_close volume
## <chr> <dttm> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 NFLX 2021-11-17 00:00:00 690 701. 686. 692. 692. 2732800
## 2 NFLX 2021-10-29 00:00:00 673. 691. 671. 690. 690. 3825300
## 3 ADBE 2021-11-19 00:00:00 681. 700. 679. 688. 688. 3090900
## 4 NFLX 2021-11-03 00:00:00 677. 689. 677. 688. 688. 2334900
## 5 ADBE 2021-11-29 00:00:00 668 691. 666. 687. 687. 2728800
## 6 NFLX 2021-11-16 00:00:00 678. 688. 677. 687. 687. 2077400
## 7 NFLX 2021-11-12 00:00:00 660. 683. 654. 683. 683. 4198400
## 8 NFLX 2021-11-18 00:00:00 692. 692. 680. 682. 682. 2012900
## 9 NFLX 2021-11-01 00:00:00 689. 690. 677. 681. 681. 3110900
## 10 NFLX 2021-11-15 00:00:00 681. 685. 671. 679. 679. 2872200
## # ℹ 45,078 more rows
Select columns
Add columns
Summarize by groups