timeline_brands | R Documentation |
Scoring Param Description 3-Point Measure (Pos/Neg/Neu) 2-Point (yes/no) total all respondents unaware == neu unaware == no aware no unaware no unaware no unaware opinion no unaware or neu no unaware + neu no unaware + neu Timeline Brands
timeline_brands(brand, start_date, end_date, scoring, moving_average = 1,
endpoint = "timeline/brands")
brand |
A string in the format |
start_date |
A string in the format |
end_date |
A string in the format |
scoring |
A string containing the scoring option to use (default: "total", "aware", "opinion"). |
moving_average |
A number of the moving_average, in days, to be applied. |
endpoint |
A string containing the appropriate endpoint. |
This endpoint contains the URLs from where timeline series files can be retrieved.
Where indicated, these URLs accept optional parts with demographic and metric
filters (referenced as :demo_filters
and :metric_filters
here in the documentation) for the reponses used to calculate the datapoints.
:demo_filters
has the following format:
:demo_filter_nickname.filter_value[/another_demo.another_value]
(starting
with a colon), each slash representing the start of a demo filter. :metric_filters
has the following format:
:/brand.brand_id.metric_nick.filter_value[/brand.another_brand_id.another_metric.nick.another_value]
(starting with a colon), each slash representing the start of a demo filter. Notice
that each metric filter has to start exactly with the characters brand
(this pattern is used to differentiate between the two types of filters). You
can also provide multiple values for each filter; to do so, just put the numeric
fitler values as the filter_value
part separated by a comma (",").
For example: :/brand.1234.buzz.1,2/brand.2345.quality.9
.
A tibble with timeline data.
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