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use super::*;
impl Expr {
/// Standard deviation of the values of the Series.
pub fn std(self, ddof: u8) -> Self {
AggExpr::Std(Arc::new(self), ddof).into()
}
/// Variance of the values of the Series.
pub fn var(self, ddof: u8) -> Self {
AggExpr::Var(Arc::new(self), ddof).into()
}
/// Reduce groups to minimal value.
pub fn min(self) -> Self {
AggExpr::Min {
input: Arc::new(self),
propagate_nans: false,
}
.into()
}
/// Reduce groups to maximum value.
pub fn max(self) -> Self {
AggExpr::Max {
input: Arc::new(self),
propagate_nans: false,
}
.into()
}
/// Get minimum value, ordered by another expression.
pub fn min_by(self, by: Self) -> Self {
Expr::n_ary(FunctionExpr::MinBy, vec![self, by])
}
/// Get maximum value, ordered by another expression.
pub fn max_by(self, by: Self) -> Self {
Expr::n_ary(FunctionExpr::MaxBy, vec![self, by])
}
/// Reduce groups to minimal value.
pub fn nan_min(self) -> Self {
AggExpr::Min {
input: Arc::new(self),
propagate_nans: true,
}
.into()
}
/// Reduce groups to maximum value.
pub fn nan_max(self) -> Self {
AggExpr::Max {
input: Arc::new(self),
propagate_nans: true,
}
.into()
}
/// Reduce groups to the mean value.
pub fn mean(self) -> Self {
AggExpr::Mean(Arc::new(self)).into()
}
/// Reduce groups to the median value.
pub fn median(self) -> Self {
AggExpr::Median(Arc::new(self)).into()
}
/// Reduce groups to the sum of all the values.
pub fn sum(self) -> Self {
AggExpr::Sum(Arc::new(self)).into()
}
/// Compute the histogram of a dataset.
#[cfg(feature = "hist")]
pub fn hist(
self,
bins: Option<Expr>,
bin_count: Option<usize>,
include_category: bool,
include_breakpoint: bool,
) -> Self {
let mut input = vec![self];
input.extend(bins);
Expr::n_ary(
FunctionExpr::Hist {
bin_count,
include_category,
include_breakpoint,
},
input,
)
}
}