clean_trim_data: Clean and trim raw dataset
In yForecasting/leadingindicators: Find relevant leading indicators for time series forecasting
Description
Usage
Arguments
Examples
View source: R/clean_trim_data.R
Description
Cleans the raw dataset by removing the first column, renaming the variables in the column headers. The dataset is trimmed from start to end date, the rest is omitted. Series that have NA values between these dates are omitted.
Usage
1
Arguments
data
Data frame containing raw data export from statistical agency. The first column is index, second column is the date and the following columns are indicator variables.
start
Start date to trim from.
end
End date to trim to.
Examples
1
# clean_trim_data(data=indicatordata, start="2004-01-01", end="2014-12-01")
yForecasting/leadingindicators documentation built on Dec. 12, 2021, 3:09 p.m.
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Description Usage Arguments Examples
View source: R/clean_trim_data.R
Description
Cleans the raw dataset by removing the first column, renaming the variables in the column headers. The dataset is trimmed from start to end date, the rest is omitted. Series that have NA values between these dates are omitted.
Usage
1 |
Arguments
data |
Data frame containing raw data export from statistical agency. The first column is index, second column is the date and the following columns are indicator variables. |
start |
Start date to trim from. |
end |
End date to trim to. |
Examples
1 | # clean_trim_data(data=indicatordata, start="2004-01-01", end="2014-12-01")
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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