masking
apply_cond
apply_cond
Description
Takes a pandas DataFrame and a condition, which can be a string, dictionary,
or callable, and applies the condition to the DataFrame using eval
or apply
accordingly.
Usage
apply_cond(df, cond)
Arguments
Argument | Description |
---|---|
df |
DataFrame. A pandas DataFrame containing the data on which the condition will be applied. |
cond |
MaskCondition. The condition to be applied on the dataframe. Can be either a string, a dictionary, or a callable function. |
Return Value
DataFrame. Dataframe evaluated at the mask condition.
Mask
Description
Class to define masks with conditions and weights to apply to DataFiles
Methods
Public Methods
Method new()
Create a new mask object
Usage
Mask$new(where = NULL, use = NULL, weight = NULL, other = NaN, comment = "")
Arguments:
where
MaskCondition | listMaskCondition, optional. Where the mask should be applied.use
MaskCondition | listMaskCondition, optional. Condition on where to use the masks.weight
Numeric | Character | listNumeric | Character, optional. Weights to apply.other
Numeric, optional.comment
Character, optional. Comment.
Method matches()
Check if a mask matches a dataframe by verifying if all 'where' conditions match across all rows.
Usage
Mask$matches(df)
Arguments:
df
DataFrame. Dataframe to check for matches.
Returns:
Logical. If the mask matches the dataframe.
Method get_weights()
Apply weights to the dataframe
Usage
Mask$get_weights(df)
Arguments:
df
(Dataframe
): Dataframe to apply weights on
Returns:
Dataframe. Dataframe with applied weights
Method clone()
The objects of this class are cloneable with this method.
Usage
Mask$clone(deep = FALSE)
Arguments:
deep
Whether to make a deep clone.
read_masks
read_masks
Description
Reads YAML files containing mask specifications from multiple databases and returns a list of Mask objects.
Usage
read_masks(variable)
Arguments
Argument | Description |
---|---|
variable |
Character. Variable to be read. |
Return Value
List. List with masks for the variable.