想了解功能强大的python包的新动态吗?本文将为您提供详细的信息,我们还将为您解答关于一:Numpy的相关问题,此外,我们还将为您介绍关于"importnumpyasnp"ImportError:N
想了解功能强大的python包的新动态吗?本文将为您提供详细的信息,我们还将为您解答关于一:Numpy的相关问题,此外,我们还将为您介绍关于"import numpy as np" ImportError: No module named numpy、3.7Python 数据处理篇之 Numpy 系列 (七)---Numpy 的统计函数、Anaconda Numpy 错误“Importing the Numpy C Extension Failed”是否有另一种解决方案、Difference between import numpy and import numpy as np的新知识。
本文目录一览:- 功能强大的python包(一):Numpy(功能强大的python包(一)知乎)
- "import numpy as np" ImportError: No module named numpy
- 3.7Python 数据处理篇之 Numpy 系列 (七)---Numpy 的统计函数
- Anaconda Numpy 错误“Importing the Numpy C Extension Failed”是否有另一种解决方案
- Difference between import numpy and import numpy as np
功能强大的python包(一):Numpy(功能强大的python包(一)知乎)
1.Numpy简介
Numpy是python的一种开源的数值计算扩展;Numpy可用来存储和处理大型矩阵;Numpy支持大量的维度数组与矩阵运算。
2.数据类型
Numpy最基本最常用的数据类型是ndarray(n维数组),其中的很多方法也是针对ndarray对象而开发的;其与python自带数据类型list(列表)基本无差别;因此对于list对象的操作都可以运用到ndarray对象上。
3.Numpy总览
数据生成
生成ndarray对象的方法汇总
函数 | 实例 |
---|---|
np.array | np.array([1,2,3,4,5]) |
np.arange | np.arange(1,10) |
np.linspace | np.linspace(1,10,10) |
np.ones | np.ones((2,2)) |
np.ones_like | np.ones_like([[1,2,3],[3,2,1]]) |
np.zeros | np.zeros((3,2)) |
np.zeros_like | np.zeros_like([[3,2,1],[1,2,3]]) |
np.empty | np.empty((3,4)) |
np.empty_like | np.empty_like([[1,2,3],[3,2,1]]) |
import numpy as np
np.array([1,2,3,4,5])
np.arange(1,10)
np.linspace(1,10,10)
np.ones((2,2))
np.ones_like([[1,2,3],[3,2,1]])
np.zeros((3,2))
np.zeros_like([[3,2,1],[1,2,3]])
np.empty((3,4))
np.empty_like([[1,2,3],[3,2,1]])
##### 数据结构
函数 | 实例 |
---|---|
np.size | np.size(np.ones((3,4))) |
np.shape | np.shape(np.ones((3,4))) |
np.split | np.split(np.ones((3,4)),1) |
np.reshape | np.ones((3,4)).reshape(2,6) |
np.concatenate | np.concatenate(ones((3,4))) |
np.transpose | np.ones((3,4)).transpose( ) |
import numpy as np
np.size(np.ones((3,4)))
np.shape(np.ones((3,4)))
np.split(np.ones((3,4)),1)
np.ones((3,4)).reshape(2,6)
np.concatenate(ones((3,4)))
np.ones((3,4)).transpose( )
##### np.random
np.random模块可以用于生成呈各种分布的数据
函数 | 实例 |
---|---|
np.random.rand | np.random.rand(2,3) |
np.random.randn | np.random.randn(3,4) |
np.random.gamma | np.random.gamma(3,10) |
np.random.normal | np.random.normal(0,1) |
np.random.randint | np.random.randint(0,10,10) |
import numpy as np
np.random.rand(2,3)
np.random.randn(3,4)
np.random.gamma(3,10)
np.random.normal(0,1)
np.random.randint(0,10,10)
##### 数值计算
函数 | 实例 |
---|---|
np.sin | np.sin(10) |
np.cos | np.cos(60) |
np.exp | np.exp(4) |
np.power | np.power(2,3) |
import numpy as np
np.sin(10)
np.cos(60)
np.exp(4)
np.power(2,3)
##### 数据分析
函数 | 实例 |
---|---|
np.abs | np.abs(np.arange(-5,4)) |
np.sum | np.sum([1,2,3]) |
np.var | np.var([1,2,3]) |
np.std | np.std([1,2,3]) |
np.mean | np.mean([1,2,3]) |
np.sqrt | np.sqrt([4,9,16]) |
np.floor | np.floor([2.1,3.7,4.3]) |
np.ceil | np.ceil([2,1,3.7,4.3]) |
np.median | np.median([3,2,4]) |
np.cumsum | np.cumsum([[1,2,3],[3,2,1]]) |
np.cumprod | np.cumprod([[1,2,3],[3,2,1]]) |
import numpy as np
np.abs(np.arange(-5,4))
np.sum([1,2,3])
np.var([1,2,3])
np.std([1,2,3])
np.mean([1,2,3])
np.sqrt([4,9,16])
np.floor([2.1,3.7,4.3])
np.ceil([2,1,3.7,4.3])
np.cumsum([[1,2,3],[3,2,1]])
np.cumprod([[1,2,3],[3,2,1]])
##### 索引
函数 | 实例 |
---|---|
np.argmin | np.argmin([4,2,1,6,8]) |
np.argmax | np.argmax([4,2,1,6,8]) |
import numpy as np
np.argmin([4,2,1,6,8])
np.argmax([4,2,1,6,8])
Ending
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"import numpy as np" ImportError: No module named numpy
问题:没有安装 numpy
解决方法:
下载文件,安装
numpy-1.8.2-win32-superpack-python2.7
安装运行 import numpy,出现
Traceback (most recent call last):
File "<pyshell#2>", line 1, in <module>
import numpy
File "C:\Python27\lib\site-packages\numpy\__init__.py", line 153, in <module>
from . import add_newdocs
File "C:\Python27\lib\site-packages\numpy\add_newdocs.py", line 13, in <module>
from numpy.lib import add_newdoc
File "C:\Python27\lib\site-packages\numpy\lib\__init__.py", line 8, in <module>
from .type_check import *
File "C:\Python27\lib\site-packages\numpy\lib\type_check.py", line 11, in <module>
import numpy.core.numeric as _nx
File "C:\Python27\lib\site-packages\numpy\core\__init__.py", line 6, in <module>
from . import multiarray
ImportError: DLL load failed: %1 不是有效的 Win32 应用程序。
原因是:python 装的是 64 位的,numpy 装的是 32 位的
重新安装 numpy 为:numpy-1.8.0-win64-py2.7
3.7Python 数据处理篇之 Numpy 系列 (七)---Numpy 的统计函数
目录
[TOC]
前言
具体我们来学 Numpy 的统计函数
(一)函数一览表
调用方式:np.*
.sum(a) | 对数组 a 求和 |
---|---|
.mean(a) | 求数学期望 |
.average(a) | 求平均值 |
.std(a) | 求标准差 |
.var(a) | 求方差 |
.ptp(a) | 求极差 |
.median(a) | 求中值,即中位数 |
.min(a) | 求最大值 |
.max(a) | 求最小值 |
.argmin(a) | 求最小值的下标,都处里为一维的下标 |
.argmax(a) | 求最大值的下标,都处里为一维的下标 |
.unravel_index(index, shape) | g 根据 shape, 由一维的下标生成多维的下标 |
(二)统计函数 1
(1)说明
(2)输出
.sum(a)
.mean(a)
.average(a)
.std(a)
.var(a)
(三)统计函数 2
(1)说明
(2)输出
.max(a) .min(a)
.ptp(a)
.median(a)
.argmin(a)
.argmax(a)
.unravel_index(index,shape)
作者:Mark
日期:2019/02/11 周一
Anaconda Numpy 错误“Importing the Numpy C Extension Failed”是否有另一种解决方案
如何解决Anaconda Numpy 错误“Importing the Numpy C Extension Failed”是否有另一种解决方案?
希望有人能在这里提供帮助。我一直在绕圈子一段时间。我只是想设置一个 python 脚本,它将一些 json 数据从 REST API 加载到云数据库中。我在 Anaconda 上设置了一个虚拟环境(因为 GCP 库推荐这样做),安装了依赖项,现在我只是尝试导入库并向端点发送请求。 我使用 Conda(和 conda-forge)来设置环境并安装依赖项,所以希望一切都干净。我正在使用带有 Python 扩展的 VS 编辑器作为编辑器。 每当我尝试运行脚本时,我都会收到以下消息。我已经尝试了其他人在 Google/StackOverflow 上找到的所有解决方案,但没有一个有效。我通常使用 IDLE 或 Jupyter 进行脚本编写,没有任何问题,但我对 Anaconda、VS 或环境变量(似乎是相关的)没有太多经验。 在此先感谢您的帮助!
\Traceback (most recent call last):
File "C:\Conda\envs\gcp\lib\site-packages\numpy\core\__init__.py",line 22,in <module>
from . import multiarray
File "C:\Conda\envs\gcp\lib\site-packages\numpy\core\multiarray.py",line 12,in <module>
from . import overrides
File "C:\Conda\envs\gcp\lib\site-packages\numpy\core\overrides.py",line 7,in <module>
from numpy.core._multiarray_umath import (
ImportError: DLL load Failed while importing _multiarray_umath: The specified module Could not be found.
During handling of the above exception,another exception occurred:
Traceback (most recent call last):
File "c:\API\citi-bike.py",line 4,in <module>
import numpy as np
File "C:\Conda\envs\gcp\lib\site-packages\numpy\__init__.py",line 150,in <module>
from . import core
File "C:\Conda\envs\gcp\lib\site-packages\numpy\core\__init__.py",line 48,in <module>
raise ImportError(msg)
ImportError:
IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!
Importing the numpy C-extensions Failed. This error can happen for
many reasons,often due to issues with your setup or how NumPy was
installed.
We have compiled some common reasons and troubleshooting tips at:
https://numpy.org/devdocs/user/troubleshooting-importerror.html
Please note and check the following:
* The Python version is: python3.9 from "C:\Conda\envs\gcp\python.exe"
* The NumPy version is: "1.21.1"
and make sure that they are the versions you expect.
Please carefully study the documentation linked above for further help.
Original error was: DLL load Failed while importing _multiarray_umath: The specified module Could not be found.
解决方法
暂无找到可以解决该程序问题的有效方法,小编努力寻找整理中!
如果你已经找到好的解决方法,欢迎将解决方案带上本链接一起发送给小编。
小编邮箱:dio#foxmail.com (将#修改为@)
Difference between import numpy and import numpy as np
Difference between import numpy and import numpy as np
up vote 18 down vote favorite 5 |
I understand that when possible one should use This helps keep away any conflict due to namespaces. But I have noticed that while the command below works the following does not Can someone please explain this? python numpy
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4 Answers
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up vote 13 down vote |
numpy is the top package name, and doing When you do In your above code: Here is the difference between
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up vote 7 down vote |
The When you import a module via the numpy package is bound to the local variable Thus, is equivalent to, When trying to understand this mechanism, it''s worth remembering that When importing a submodule, you must refer to the full parent module name, since the importing mechanics happen at a higher level than the local variable scope. i.e. I also take issue with your assertion that "where possible one should [import numpy as np]". This is done for historical reasons, mostly because people get tired very quickly of prefixing every operation with Finally, to round out my exposé, here are 2 interesting uses of the 1. long subimports 2. compatible APIs
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up vote 1 down vote |
when you call the statement
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up vote 1 down vote |
This is a language feature. This feature allows:
Notice however that Said that, when you run You receive an
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今天关于功能强大的python包和一:Numpy的分享就到这里,希望大家有所收获,若想了解更多关于"import numpy as np" ImportError: No module named numpy、3.7Python 数据处理篇之 Numpy 系列 (七)---Numpy 的统计函数、Anaconda Numpy 错误“Importing the Numpy C Extension Failed”是否有另一种解决方案、Difference between import numpy and import numpy as np等相关知识,可以在本站进行查询。
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