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- numpy.mean
...NumPy reference Routines and objects by topic Statistics numpy.mean...
- numpy.char.chararray.mean (Python method, in numpy.char.chararray.mean)
- numpy.ma.masked_array.mean (Python method, in numpy.ma.masked_array.mean)
- numpy.ma.MaskedArray.mean (Python method, in numpy.ma.MaskedArray.mean)
- numpy.ma.MaskType.mean (Python method, in numpy.ma.MaskType.mean)
- numpy.ma.mean (Python data, in numpy.ma.mean)
- numpy.matrix.mean (Python method, in numpy.matrix.mean)
- numpy.mean (Python function, in numpy.mean)
- numpy.memmap.mean (Python method, in numpy.memmap.mean)
- numpy.ndarray.mean (Python method, in numpy.ndarray.mean)
- numpy.recarray.mean (Python method, in numpy.recarray.mean)
- numpy.record.mean (Python method, in numpy.record.mean)
numpy.distutilsuser guide...onfig.add_subpackage(subpackage_name,subpackage_path=None) — add SciPy subpackage configuration to the current one. The meaning and usage of arguments is explained above, see config.get_subpackage() method. config.add_data_files(*files) — p...
- Array iterator API
...then set every value to the reduction unit before doing the iteration loop. In the case of a buffered reduction, this means you must also specify the flag NPY_ITER_DELAY_BUFALLOC, then reset the iterator after initializing the allocated o...
- Building from source
...build & packaging documentation that is relevant. System-level dependencies NumPy uses compiled code for speed, which means you need compilers and some other system-level (i.e, non-Python / non-PyPI) dependencies to build it on your syste...
- Contributing to NumPy
...st your work locally before committing. A PR must be approved by at least one core team member before merging. Approval means the core team member has carefully reviewed the changes, and the PR is ready for merging. Document changes Beyon...
- Data type promotion in NumPy
...general promotion rules In NumPy promotion refers to what specific functions do with the result and in some cases, this means that NumPy may deviate from what the np.result_type would give. Behavior of sum and prod np.sum and np.prod will...
- Data types
...have used the Python float object as a dtype instead of numpy.float64. NumPy knows that int refers to numpy.int_, bool means numpy.bool, that float is numpy.float64 and complex is numpy.complex128. The other data-types do not have Python...
- Discrete Fourier Transform (
numpy.fft)...mitian, i.e., the component at frequency \(f_k\) is the complex conjugate of the component at frequency \(-f_k\), which means that for real inputs there is no information in the negative frequency components that is not already available fr...
- For downstream package authors
...application binary interface) stability of NumPy is important. NumPy’s ABI is forward but not backward compatible. This means: binaries compiled against a given target version of NumPy’s C API will still run correctly with newer NumPy versi...
- How to contribute to the NumPy documentation
...are our best guide to what needs fixing. If you write a missing doc you join the front line of open source, but it’s a meaningful contribution just to let us know what’s missing. If you want to compose a doc, run your thoughts by the maili...
- Internal organization of NumPy arrays
...use of the copy method if one really wants to make a new and independent copy of the data buffer. New views into arrays mean the object reference counts for the data buffer increase. Simply doing away with the original array object will not...
- Interoperability with NumPy
...method returns an array or any nested sequence) that implements it can be used as a NumPy array. If possible, this will mean using __array__() to create a NumPy ndarray view of the array-like object. Otherwise, this copies the data into a n...
- Legacy random generation
...aplace([loc, scale, size]) Draw samples from the Laplace or double exponential distribution with specified location (or mean) and scale (decay). logistic([loc, scale, size]) Draw samples from a logistic distribution. lognormal([mean, sigm...
- Linear algebra (
numpy.linalg)...ray. This is indicated in the documentation via input parameter specifications such as a : (..., M, M) array_like. This means that if for instance given an input array a.shape == (N, M, M), it is interpreted as a “stack” of N matrices, each...
- NumPy 1.10.0 Release Notes
..., but a fully masked version of the item. Median warns and returns nan when invalid values are encountered Similar to mean, median and percentile now emits a Runtime warning and returns NaN in slices where a NaN is present. To compute the...
- NumPy 1.12.0 Release Notes
...ve like NaN In 1.13 np.average will preserve subclasses, to match the behavior of most other numpy functions such as np.mean. In particular, this means calls which returned a scalar may return a 0-d subclass object instead. Multiple-field...
- NumPy 1.12.1 Release Notes
...T: Work around isfinite inconsistency on i386 BUG: Guard against replacing constants without ‘_’ spec in f2py. BUG: Fix mean for float 16 non-array inputs for 1.12 BUG: Fix calling python api with error set and minor leaks for… BUG: Make is...
- NumPy 1.13.0 Release Notes
...GUfuncs on empty arrays and NpyIter axis removal It is now allowed to remove a zero-sized axis from NpyIter. Which may mean that code removing axes from NpyIter has to add an additional check when accessing the removed dimensions later on....
- NumPy 1.14.0 Release Notes
...type-like arguments. It might be expected that issubdtype(np.float32, 'float64') and issubdtype(np.float32, np.float64) mean the same thing - however, there was an undocumented special case that translated the former into issubdtype(np.floa...
- NumPy 1.15.0 Release Notes
...failed on python 3 when called with a string. Multidimensional indexing with anything but a tuple is deprecated. This means that the index list in ind = [slice(None), 0]; arr[ind] should be changed to a tuple, e.g., ind = [slice(None), 0]...
- NumPy 1.16.0 Release Notes
...ing point values, while before it was equal to the size of the type. For many users (for instance on x64/unix/gcc) this means that complex64 is now 4-byte aligned instead of 8-byte aligned. An important consequence is that aligned structure...
- NumPy 1.17.0 Release Notes
...rounding Casting from a different floating point precision to float16 used incorrect rounding in some edge cases. This means in rare cases, subnormal results will now be rounded up instead of down, changing the last bit (ULP) of the result...
- NumPy 1.19.0 Release Notes
...ixed scalars and arrays in PyArray_ConvertToCommonType has been changed to adhere to those used by np.result_type. This means that input such as (1000, np.array([1], dtype=np.uint8))) will now return uint16 dtypes. In most cases the behavio...
- NumPy 1.20.0 Release Notes
...or moving window access to the array. This allows for the simple implementation of certain algorithms, such as running means. (gh-17394) numpy.broadcast_shapes is a new user-facing function broadcast_shapes gets the resulting shape from...
- NumPy 1.20.2 Release Notes
...item__, __mul__ and… #18611: BUG: NameError in numpy.distutils.fcompiler.compaq #18612: BUG: Fixed where keyword for np.mean & np.var methods #18617: CI: Update apt package list before Python install #18636: MAINT: Ensure that re-exported s...
- NumPy 1.21.0 Release Notes
- NumPy 1.22.0 Release Notes
- NumPy 1.23.0 Release Notes
- NumPy 1.24 Release Notes
- NumPy 1.7.0 Release Notes
- NumPy 1.8.0 Release Notes
- NumPy 1.8.1 Release Notes
- NumPy 1.9.0 Release Notes
- NumPy 2.0 migration guide
- NumPy 2.0.0 Release Notes
- NumPy 2.1.0 Release Notes
- NumPy 2.2.0 Release Notes
- NumPy C code explanations
- NumPy for MATLAB users
- NumPy project governance and decision-making
- NumPy quickstart
- NumPy security
- numpy.allclose
- numpy.array_equiv
- numpy.asanyarray
- numpy.asarray
- numpy.asarray_chkfinite
- numpy.average
- numpy.bartlett
- numpy.blackman
- numpy.block
- numpy.busday_offset