statistics

Mathematical statistics functions, similar to Python's statistics module.

import statistics

Functions

statistics.mean(data: Iterable[float]) -> float

Return the arithmetic mean (average) of data.

Parameters:

• data (Iterable[float]) -- A sequence of numeric values.

Returns: The arithmetic mean.

statistics.mean([1, 2, 3, 4, 5])    # 3.0

Raises:

• StatisticsError -- Thrown if data is empty.

statistics.mean(data: Iterable[int]) -> float

Return the arithmetic mean of data (integer overload).

statistics.mean(data: Iterable[long]) -> float

Return the arithmetic mean of data (long overload).

statistics.fmean(data: Iterable[float]) -> float

Return the arithmetic mean of data as a float. For this implementation, equivalent to Mean(IEnumerable{double}).

Parameters:

• data (Iterable[float]) -- A sequence of numeric values.

Returns: The arithmetic mean.

Raises:

• StatisticsError -- Thrown if data is empty.

statistics.fmean(data: Iterable[int]) -> float

Return the arithmetic mean of data as a float (integer overload).

statistics.fmean(data: Iterable[long]) -> float

Return the arithmetic mean of data as a float (long overload).

statistics.median(data: Iterable[float]) -> float

Return the median (middle value) of data. When the number of data points is even, the median is the average of the two middle values.

Parameters:

• data (Iterable[float]) -- A sequence of numeric values.

Returns: The median value.

statistics.median([1, 2, 3, 4])    # 2.5
statistics.median([1, 2, 3])       # 2.0

Raises:

• StatisticsError -- Thrown if data is empty.

statistics.median(data: Iterable[int]) -> float

Return the median of data (integer overload).

statistics.median(data: Iterable[long]) -> float

Return the median of data (long overload).

statistics.median_low(data: Iterable[float]) -> float

Return the low median of data. When the number of data points is even, the low median is the smaller of the two middle values.

Parameters:

• data (Iterable[float]) -- A sequence of numeric values.

Returns: The low median value.

Raises:

• StatisticsError -- Thrown if data is empty.

statistics.median_low(data: Iterable[int]) -> float

Return the low median of data (integer overload).

statistics.median_low(data: Iterable[long]) -> float

Return the low median of data (long overload).

statistics.median_high(data: Iterable[float]) -> float

Return the high median of data. When the number of data points is even, the high median is the larger of the two middle values.

Parameters:

• data (Iterable[float]) -- A sequence of numeric values.

Returns: The high median value.

Raises:

• StatisticsError -- Thrown if data is empty.

statistics.median_high(data: Iterable[int]) -> float

Return the high median of data (integer overload).

statistics.median_high(data: Iterable[long]) -> float

Return the high median of data (long overload).

statistics.mode(data: Iterable[T]) -> T

Return the single most common data point from data. If there are multiple modes (tied), the first encountered value wins.

Parameters:

• data (Iterable[T]) -- A sequence of values.

Returns: The most common value.

statistics.mode([1, 1, 2, 3])    # 1

Raises:

• StatisticsError -- Thrown if data is empty.

statistics.stdev(data: Iterable[float]) -> float

Return the sample standard deviation (the square root of the sample variance) of data. Uses n-1 in the denominator.

Parameters:

• data (Iterable[float]) -- A sequence of at least two numeric values.

Returns: The sample standard deviation.

statistics.stdev([2, 4, 4, 4, 5, 5, 7, 9])    # ~2.138

Raises:

• StatisticsError -- Thrown if data has fewer than 2 elements.

statistics.stdev(data: Iterable[int]) -> float

Return the sample standard deviation (integer overload).

statistics.stdev(data: Iterable[long]) -> float

Return the sample standard deviation (long overload).

statistics.pstdev(data: Iterable[float]) -> float

Return the population standard deviation (the square root of the population variance) of data. Uses n in the denominator.

Parameters:

• data (Iterable[float]) -- A sequence of numeric values.

Returns: The population standard deviation.

Raises:

• StatisticsError -- Thrown if data is empty.

statistics.pstdev(data: Iterable[int]) -> float

Return the population standard deviation (integer overload).

statistics.pstdev(data: Iterable[long]) -> float

Return the population standard deviation (long overload).

statistics.variance(data: Iterable[float]) -> float

Return the sample variance of data. Uses n-1 in the denominator (Bessel's correction).

Parameters:

• data (Iterable[float]) -- A sequence of at least two numeric values.

Returns: The sample variance.

Raises:

• StatisticsError -- Thrown if data has fewer than 2 elements.

statistics.variance(data: Iterable[int]) -> float

Return the sample variance (integer overload).

statistics.variance(data: Iterable[long]) -> float

Return the sample variance (long overload).

statistics.pvariance(data: Iterable[float]) -> float

Return the population variance of data. Uses n in the denominator.

Parameters:

• data (Iterable[float]) -- A sequence of numeric values.

Returns: The population variance.

Raises:

• StatisticsError -- Thrown if data is empty.

statistics.pvariance(data: Iterable[int]) -> float

Return the population variance (integer overload).

statistics.pvariance(data: Iterable[long]) -> float

Return the population variance (long overload).