# Time Series

A number of string aliases are given to useful common time series frequencies. We will refer to these aliases as *offset aliases*.

| Alias    | Description                                      |
| -------- | ------------------------------------------------ |
| B        | business day frequency                           |
| C        | custom business day frequency                    |
| D        | calendar day frequency                           |
| W        | weekly frequency                                 |
| M        | month end frequency                              |
| SM       | semi-month end frequency (15th and end of month) |
| BM       | business month end frequency                     |
| CBM      | custom business month end frequency              |
| MS       | month start frequency                            |
| SMS      | semi-month start frequency (1st and 15th)        |
| BMS      | business month start frequency                   |
| CBMS     | custom business month start frequency            |
| Q        | quarter end frequency                            |
| BQ       | business quarter end frequency                   |
| QS       | quarter start frequency                          |
| BQS      | business quarter start frequency                 |
| A, Y     | year end frequency                               |
| BA, BY   | business year end frequency                      |
| AS, YS   | year start frequency                             |
| BAS, BYS | business year start frequency                    |
| BH       | business hour frequency                          |
| H        | hourly frequency                                 |
| T, min   | minutely frequency                               |
| S        | secondly frequency                               |
| L, ms    | milliseconds                                     |
| U, us    | microseconds                                     |
| N        | nanoseconds                                      |

```
# Use pandas grouper to group values using annual frequency
year_groups = nyse.groupby(pd.Grouper(freq ='A'))
```


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