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Update pkgdown docs and generate README.md
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README.md

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@@ -12,19 +12,19 @@ Built on top of the `tidyverse`, `tibbletime` is an extension that allows for th
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Some immediate advantages of this include:
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1. The ability to perform compact time-based subsetting on tibbles.
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1. Performing compact time-based subsetting on tibbles.
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2. Partitioning an index column by time (like yearly, monthly, every 2 weeks, etc.) so that you can use `dplyr`'s grouped functionality to summarise and aggregate by time period.
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3. Changing the periodicity of a time-based tibble. This allows easily changing from a daily dataset to a monthly or yearly dataset.
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4. All functions were designed to support the pipe and to work with packages like `dplyr` and `tidyr`. Each function has also been designed to work with `dplyr::group_by()` allowing for powerful data manipulation.
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4. Easily working with the pipe and packages like `dplyr` and `tidyr` to make for a seamless experience with time series and the tidyverse. Each function has also been designed to work with `dplyr::group_by()` allowing for powerful data manipulation.
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5. Modifying functions for rolling analysis.
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6. Quickly creating `tbl_time` time series objects.
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6. Creating `tbl_time` time series objects quickly.
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7. Full support for `Date` and `POSIXct` index columns, and experimental support for `yearmon`, `yearqtr` and `hms` which should become more stable as some issues in `dplyr` are worked out.
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7. Using fully supported `Date` and `POSIXct` index columns, along with experimental support for `yearmon`, `yearqtr` and `hms` which should become more stable as some issues in `dplyr` are worked out.
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Installation
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------------
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5. `rollify()` - Modify a function so that it calculates a value (or a set of values) at specific time intervals. This can be used for rolling averages and other rolling calculations inside the `tidyverse` framework.
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6. `create_series()` - Use shorthand notation to quickly initialize a `tbl_time` object containing a `date` column with a regularly spaced time series.
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6. `create_series()` - Use shorthand notation to quickly initialize a `tbl_time` object containing a regularly spaced index column of class `Date`, `POSIXct`, `yearmon`, `yearqtr` or `hms`.
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To look at just a few:
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Grouping
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--------
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Groups created through `dplyr::group_by()` are supported throughout the package. Because `collapse_index()` is just adding a column you can group on, all dplyr functions are supported.
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Groups created through `dplyr::group_by()` are supported throughout the package. Because `collapse_index()` is just adding a column you can group on, all `dplyr` functions are supported.
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``` r
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# Facebook, Amazon, Netflix and Google stocks

docs/articles/TT-01-time-based-filtering.html

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docs/articles/index.html

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