ndarray의 통계값을 구할 때는 전체에서 구할 수도 있지만 행/열 등 축을 기준으로 구할 수도 있다.
- NumPY amin - 최소값 구하기
https://docs.scipy.org/doc/numpy/reference/generated/numpy.amin.html?highlight=amin
numpy.amin — NumPy v1.16 Manual
Parameters: a : array_like Input data. axis : None or int or tuple of ints, optional Axis or axes along which to operate. By default, flattened input is used. If this is a tuple of ints, the minimum is selected over multiple axes, instead of a single axis
docs.scipy.org
- NumPY amax - 최대값 구하기
https://docs.scipy.org/doc/numpy/reference/generated/numpy.amax.html?highlight=amax
numpy.amax — NumPy v1.16 Manual
Parameters: a : array_like Input data. axis : None or int or tuple of ints, optional Axis or axes along which to operate. By default, flattened input is used. If this is a tuple of ints, the maximum is selected over multiple axes, instead of a single axis
docs.scipy.org
- NumPY ptp - 최대, 최소의 범위 값을 구한다.
ndarray의 크기가 커서 전체를 다 볼 수 없을 때 해당 다차원 배열의 최대, 최소의 범위를 보는 함수이다.
https://docs.scipy.org/doc/numpy/reference/generated/numpy.ptp.html?highlight=ptp#numpy.ptp
numpy.ptp — NumPy v1.16 Manual
Parameters: a : array_like Input values. axis : None or int or tuple of ints, optional Axis along which to find the peaks. By default, flatten the array. axis may be negative, in which case it counts from the last to the first axis. If this is a tuple of i
docs.scipy.org
- NumPY median
https://docs.scipy.org/doc/numpy/reference/generated/numpy.median.html?highlight=median
numpy.median — NumPy v1.16 Manual
Parameters: a : array_like Input array or object that can be converted to an array. axis : {int, sequence of int, None}, optional Axis or axes along which the medians are computed. The default is to compute the median along a flattened version of the array
docs.scipy.org
- NumPY mean
산술평균을 구할 때 쓴다. 가중평균을 구할 때는 average 메서드를 사용한다.
https://docs.scipy.org/doc/numpy/reference/generated/numpy.mean.html#numpy.mean
numpy.mean — NumPy v1.16 Manual
Parameters: a : array_like Array containing numbers whose mean is desired. If a is not an array, a conversion is attempted. axis : None or int or tuple of ints, optional Axis or axes along which the means are computed. The default is to compute the mean of
docs.scipy.org
- NumPY var - 분산
https://docs.scipy.org/doc/numpy/reference/generated/numpy.var.html?highlight=var
numpy.var — NumPy v1.16 Manual
Parameters: a : array_like Array containing numbers whose variance is desired. If a is not an array, a conversion is attempted. axis : None or int or tuple of ints, optional Axis or axes along which the variance is computed. The default is to compute the v
docs.scipy.org
- NumPY std - 표준편차
https://docs.scipy.org/doc/numpy/reference/generated/numpy.std.html?highlight=std
numpy.std — NumPy v1.16 Manual
Parameters: a : array_like Calculate the standard deviation of these values. axis : None or int or tuple of ints, optional Axis or axes along which the standard deviation is computed. The default is to compute the standard deviation of the flattened array.
docs.scipy.org
'karma( 업 ) > Python' 카테고리의 다른 글
| 5. 브로드 캐스팅, 벡터화 연산 NumPY 고급기능 (0) | 2019.05.06 |
|---|---|
| 4. 인덱싱, 슬라이싱, 전치, 형태변경, 연결, 연산을 이용한 다차원 배열 현태 변경하기 (0) | 2019.05.06 |
| 2. 다차원 배열 생성하기 (0) | 2019.05.06 |
| 1. NumPY ? (1) | 2019.05.05 |
| Python, Virtualenv, OpenCV, PyCharm 설치( 3 ) (0) | 2019.05.01 |