"Fossies" - the Fresh Open Source Software Archive  

Source code changes of the file "docs/_docs/non-daily_data.md" between
prophet-1.0.tar.gz and prophet-1.1.tar.gz

About: Prophet is a tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

non-daily_data.md  (prophet-1.0):non-daily_data.md  (prophet-1.1)
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- title: Monthly data - title: Monthly data
id: monthly-data id: monthly-data
- title: Holidays with aggregated data - title: Holidays with aggregated data
id: holidays-with-aggregated-data id: holidays-with-aggregated-data
--- ---
<a id="sub-daily-data"> </a> <a id="sub-daily-data"> </a>
## Sub-daily data ## Sub-daily data
Prophet can make forecasts for time series with sub-daily observations by passin g in a dataframe with timestamps in the `ds` column. The format of the timestamp s should be YYYY-MM-DD HH:MM:SS - see the example csv [here](https://github.com/ facebook/prophet/blob/master/examples/example_yosemite_temps.csv). When sub-dail y data are used, daily seasonality will automatically be fit. Here we fit Prophe t to data with 5-minute resolution (daily temperatures at Yosemite): Prophet can make forecasts for time series with sub-daily observations by passin g in a dataframe with timestamps in the `ds` column. The format of the timestamp s should be YYYY-MM-DD HH:MM:SS - see the example csv [here](https://github.com/ facebook/prophet/blob/main/examples/example_yosemite_temps.csv). When sub-daily data are used, daily seasonality will automatically be fit. Here we fit Prophet to data with 5-minute resolution (daily temperatures at Yosemite):
```R ```R
# R # R
df <- read.csv('../examples/example_yosemite_temps.csv') df <- read.csv('../examples/example_yosemite_temps.csv')
m <- prophet(df, changepoint.prior.scale=0.01) m <- prophet(df, changepoint.prior.scale=0.01)
future <- make_future_dataframe(m, periods = 300, freq = 60 * 60) future <- make_future_dataframe(m, periods = 300, freq = 60 * 60)
fcst <- predict(m, future) fcst <- predict(m, future)
plot(m, fcst) plot(m, fcst)
``` ```
```python ```python
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