SPSS+AMOS数据分析案例教程-关于中介模
SPSS视频教程内容目录和跳转链接
Meta分析辅导+代找数据
SPSS+AMOS数据分析案例教程-关于中介模
SPSS视频教程内容目录和跳转链接
R语言快速入门视频教程
Python智联招聘数据分析
LCA潜在类别分析和Mplus应用
Amos结构方程模型数据分析入门教程
倒U关系回归分析中介效应和调节效应分析SPSS视频教程
统计咨询(图文问答)

安装stata并在jupyter notebook中调用

在B站@mlln-cn, 我就能回答你的问题奥!

文章目录
  1. 1. 安装stata
    1. 1.0.1. 下载
    2. 1.0.2. 安装
  2. 1.1. 命令行注册
  • 2. 方案一: 使用stata魔法函数
    1. 2.1. 安装python模块
    2. 2.2. 使用
      1. 2.2.1. 参数
    3. 2.3. 参考
  • 3. 方案二: 使用stata kernel
    1. 3.1. 安装方法
    2. 3.2. 使用方法
  • Stata是做生物统计/计量经济学的重要统计工具, 而python是做数据科学的利器, ipystata将stata和python结合在一起, 并能够在jupyter notebook中使用, 使得我们的工作效率大大提升。下面我们介绍一下, 如何安装stata, 如何在python中使用stata, 并进行stata的一些自动化操作。

    目前来看, 在jupyternotebook中使用stata有两种方案:

    • 方案一: 使用ipystata模块, 这个模块提供了%%stata魔法函数, 可以把notebook的cell可以执行stata语句
    • 方案二: 使用stata_kernel, 它实际上是一个notebook kernel, 使用stata kernel创建的notebook, 只能执行stata语句

    下面我们分别介绍两种方案。

    安装stata

    安装stata非常简单, 基本上都是一路next, 不过我把一些需要注意的步骤贴在下面, 便于你选择:

    下载

    链接:https://pan.baidu.com/s/15cWE_4mxKmOiT08yhG8GXQ
    提取码:zuaz

    安装

    双击安装:

    注意选择stata/SE:

    这里不用改, 只需要记住stata的安装目录, 后面会用到:

    安装好了以后, 来到安装目录, 打开stata:

    注意, 不需要注册:

    最好不要让他自动更新:

    输入注册码:

    命令行注册

    这是windows的安装方法, 如果你是linux, 也是类似的道理, 需要运行stata命令来注册。

    使用管理员模式打开powershell:

    工作目录调整到stata的安装目录, 然后执行命令.\StataSE-64.exe /Register

    1
    2
    3
    4
    5
    6
    7
    PS C:\Users\syd> cd c:/
    PS C:\> cd '.\Program Files (x86)\'
    PS C:\Program Files (x86)> cd .\Starth\
    PS C:\Program Files (x86)\Starth> cd ..
    PS C:\Program Files (x86)> cd .\Stata15\
    PS C:\Program Files (x86)\Stata15> .\StataSE-64.exe /Register
    PS C:\Program Files (x86)\Stata15>

    方案一: 使用stata魔法函数

    安装python模块

    (假设你已经安装好了jupyter notebook)

    你需要使用pip安装两个模块:

    ‘’’
    pip install ipystata
    pip install psutil
    ‘’’

    使用

    自己随便新建一个notebook , 然后先设置stata的路径:

    1
    2
    3
    import ipystata  
    from ipystata.config import config_stata
    config_stata(r'C:\Program Files (x86)\Stata15\StataSE-64.exe')

    然后你可以使用魔法函数%%stata运行一个stata的输出命令:

    1
    display "hello world"

    参数

    把pandas.DataFrame发送给stata使用:

    在python中提前定义好一个df(DataFrame), 然后:

    1
    %%stata -d df  

    或者把数据从stata输出到python:

    1
    %%stata -o df

    为了调试, 运行stata的时候, 可以设置打开stata的操作界面:

    1
    %%stata -os

    输出图表:

    1
    %%stata -gr

    参考

    还有很多用法请参考github地址: https://github.com/TiesdeKok/ipystata/blob/master/ipystata/Example.ipynb

    方案二: 使用stata kernel

    安装方法

    powershell中执行下面两条命令即可:

    1
    2
    pip install stata_kernel
    python -m stata_kernel.install

    安装输出:

    1
    2
    3
    4
    5
    6
    7
    8
    9
    10
    11
    12
    13
    14
    15
    16
    17
    18
    19
    20
    21
    22
    23
    24
    25
    26
    27
    28
    29
    30
    31
    32
    33
    34
    35
    36
    37
    38
    39
    40
    41
    42
    43
    44
    45
    46
    47
    48
    49
    50
    51
    52
    53
    54
    55
    56
    57
    58
    59
    60
    61
    62
    63
    64
    65
    66
    67
    68
    69
    70
    71
    72
    73
    74
    75
    76
    77
    78
    79
    80
    81
    82
    83
    84
    85
    86
    87
    88
    89
    90
    91
    92
    93
    94
    95
    96
    97
    98
    99
    100
    101
    102
    103
    Looking in indexes: https://mirrors.ustc.edu.cn/pypi/web/simple
    Collecting stata_kernel
    Downloading https://mirrors.ustc.edu.cn/pypi/web/packages/10/5c/b0bebe1214f09d50439622ad812fb165b5a8caba1fd0f83d51b67ebc7e4f/stata_kernel-1.5.5-py3-none-any.whl (60kB)
    100% |████████████████████████████████| 61kB 2.2MB/s
    Collecting requests>=2.19.1 (from stata_kernel)
    Downloading https://mirrors.ustc.edu.cn/pypi/web/packages/65/47/7e02164a2a3db50ed6d8a6ab1d6d60b69c4c3fdf57a284257925dfc12bda/requests-2.19.1-py2.py3-none-any.whl (91kB)
    100% |████████████████████████████████| 92kB 1.6MB/s
    Collecting packaging>=17.1 (from stata_kernel)
    Downloading https://mirrors.ustc.edu.cn/pypi/web/packages/89/d1/92e6df2e503a69df9faab187c684585f0136662c12bb1f36901d426f3fab/packaging-18.0-py2.py3-none-any.whl
    Requirement already satisfied: jupyter>=1.0.0 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from stata_kernel) (1.0.0)
    Requirement already satisfied: pygments>=2.2.0 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from stata_kernel) (2.2.0)
    Requirement already satisfied: jupyter-client>=5.2.3 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from stata_kernel) (5.2.3)
    Requirement already satisfied: pywin32>=223; platform_system == "Windows" in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from stata_kernel) (224)
    Collecting pexpect>=4.6.0 (from stata_kernel)
    Downloading https://mirrors.ustc.edu.cn/pypi/web/packages/89/e6/b5a1de8b0cc4e07ca1b305a4fcc3f9806025c1b651ea302646341222f88b/pexpect-4.6.0-py2.py3-none-any.whl (57kB)
    100% |████████████████████████████████| 61kB 20.5MB/s
    Collecting pandas>=0.23.4 (from stata_kernel)
    Downloading https://mirrors.ustc.edu.cn/pypi/web/packages/0e/67/def5bfaf4d3324fdb89048889ec523c0903c5efab1a64c8dbe0ac8eec13c/pandas-0.23.4-cp36-cp36m-win_amd64.whl (7.7MB)
    100% |████████████████████████████████| 7.7MB 34.2MB/s
    Collecting regex>=2018.7.11 (from stata_kernel)
    Downloading https://mirrors.ustc.edu.cn/pypi/web/packages/15/a5/cdb73862c207dcbb2dec5a4c64f850314910c55097dfa12cdfc533892502/regex-2018.08.29-cp36-none-win_amd64.whl (255kB)
    100% |████████████████████████████████| 256kB 1.9MB/s
    Requirement already satisfied: ipykernel>=4.8.2 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from stata_kernel) (4.8.2)
    Collecting IPython>=6.5.0 (from stata_kernel)
    Downloading https://mirrors.ustc.edu.cn/pypi/web/packages/a0/27/29d66ed395a5c2c3a912332d446a54e2bc3277c36b0bbd22bc71623e0193/ipython-7.0.1-py3-none-any.whl (760kB)
    100% |████████████████████████████████| 768kB 3.5MB/s
    Collecting beautifulsoup4>=4.6.3 (from stata_kernel)
    Downloading https://mirrors.ustc.edu.cn/pypi/web/packages/21/0a/47fdf541c97fd9b6a610cb5fd518175308a7cc60569962e776ac52420387/beautifulsoup4-4.6.3-py3-none-any.whl (90kB)
    100% |████████████████████████████████| 92kB 452kB/s
    Collecting pillow>=5.2.0 (from stata_kernel)
    Downloading https://mirrors.ustc.edu.cn/pypi/web/packages/bd/39/c76eaf781343162bdb1cf4854cb3bd5947a87ee44363e5acd6c48d69c4a1/Pillow-5.3.0-cp36-cp36m-win_amd64.whl (1.6MB)
    100% |████████████████████████████████| 1.6MB 11.4MB/s
    Requirement already satisfied: certifi>=2017.4.17 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from requests>=2.19.1->stata_kernel) (2018.4.16)
    Requirement already satisfied: urllib3<1.24,>=1.21.1 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from requests>=2.19.1->stata_kernel) (1.22)
    Requirement already satisfied: chardet<3.1.0,>=3.0.2 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from requests>=2.19.1->stata_kernel) (3.0.4)
    Requirement already satisfied: idna<2.8,>=2.5 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from requests>=2.19.1->stata_kernel) (2.6)
    Requirement already satisfied: six in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from packaging>=17.1->stata_kernel) (1.11.0)
    Requirement already satisfied: pyparsing>=2.0.2 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from packaging>=17.1->stata_kernel) (2.2.0)
    Requirement already satisfied: notebook in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from jupyter>=1.0.0->stata_kernel) (5.5.0)
    Requirement already satisfied: ipywidgets in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from jupyter>=1.0.0->stata_kernel) (7.2.1)
    Requirement already satisfied: jupyter-console in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from jupyter>=1.0.0->stata_kernel) (5.2.0)
    Requirement already satisfied: nbconvert in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from jupyter>=1.0.0->stata_kernel) (5.3.1)
    Requirement already satisfied: qtconsole in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from jupyter>=1.0.0->stata_kernel) (4.3.1)
    Requirement already satisfied: python-dateutil>=2.1 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from jupyter-client>=5.2.3->stata_kernel) (2.7.3)
    Requirement already satisfied: pyzmq>=13 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from jupyter-client>=5.2.3->stata_kernel) (17.0.0)
    Requirement already satisfied: traitlets in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from jupyter-client>=5.2.3->stata_kernel) (4.3.2)
    Requirement already satisfied: jupyter-core in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from jupyter-client>=5.2.3->stata_kernel) (4.4.0)
    Requirement already satisfied: tornado>=4.1 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from jupyter-client>=5.2.3->stata_kernel) (5.0.2)
    Collecting ptyprocess>=0.5 (from pexpect>=4.6.0->stata_kernel)
    Downloading https://mirrors.ustc.edu.cn/pypi/web/packages/d1/29/605c2cc68a9992d18dada28206eeada56ea4bd07a239669da41674648b6f/ptyprocess-0.6.0-py2.py3-none-any.whl
    Requirement already satisfied: pytz>=2011k in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from pandas>=0.23.4->stata_kernel) (2018.4)
    Requirement already satisfied: numpy>=1.9.0 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from pandas>=0.23.4->stata_kernel) (1.14.1)
    Requirement already satisfied: colorama; sys_platform == "win32" in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from IPython>=6.5.0->stata_kernel) (0.3.9)
    Requirement already satisfied: decorator in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from IPython>=6.5.0->stata_kernel) (4.3.0)
    Requirement already satisfied: pickleshare in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from IPython>=6.5.0->stata_kernel) (0.7.4)
    Requirement already satisfied: simplegeneric>0.8 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from IPython>=6.5.0->stata_kernel) (0.8.1)
    Requirement already satisfied: setuptools>=18.5 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from IPython>=6.5.0->stata_kernel) (28.8.0)
    Requirement already satisfied: jedi>=0.10 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from IPython>=6.5.0->stata_kernel) (0.12.0)
    Collecting prompt-toolkit<2.1.0,>=2.0.0 (from IPython>=6.5.0->stata_kernel)
    Downloading https://mirrors.ustc.edu.cn/pypi/web/packages/e5/c5/f1ee6698bdcf615f171a77e81ca70293b16a6d82285f1760b388b4348263/prompt_toolkit-2.0.5-py3-none-any.whl (334kB)
    100% |████████████████████████████████| 337kB 12.8MB/s
    Requirement already satisfied: backcall in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from IPython>=6.5.0->stata_kernel) (0.1.0)
    Requirement already satisfied: Send2Trash in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from notebook->jupyter>=1.0.0->stata_kernel) (1.5.0)
    Requirement already satisfied: terminado>=0.8.1 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from notebook->jupyter>=1.0.0->stata_kernel) (0.8.1)
    Requirement already satisfied: jinja2 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from notebook->jupyter>=1.0.0->stata_kernel) (2.10)
    Requirement already satisfied: nbformat in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from notebook->jupyter>=1.0.0->stata_kernel) (4.4.0)
    Requirement already satisfied: ipython-genutils in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from notebook->jupyter>=1.0.0->stata_kernel) (0.2.0)
    Requirement already satisfied: widgetsnbextension~=3.2.0 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from ipywidgets->jupyter>=1.0.0->stata_kernel) (3.2.1)
    Requirement already satisfied: mistune>=0.7.4 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from nbconvert->jupyter>=1.0.0->stata_kernel) (0.8.3)
    Requirement already satisfied: bleach in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from nbconvert->jupyter>=1.0.0->stata_kernel) (1.5.0)
    Requirement already satisfied: entrypoints>=0.2.2 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from nbconvert->jupyter>=1.0.0->stata_kernel) (0.2.3)
    Requirement already satisfied: testpath in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from nbconvert->jupyter>=1.0.0->stata_kernel) (0.3.1)
    Requirement already satisfied: pandocfilters>=1.4.1 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from nbconvert->jupyter>=1.0.0->stata_kernel) (1.4.2)
    Requirement already satisfied: parso>=0.2.0 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from jedi>=0.10->IPython>=6.5.0->stata_kernel) (0.2.0)
    Requirement already satisfied: wcwidth in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from prompt-toolkit<2.1.0,>=2.0.0->IPython>=6.5.0->stata_kernel) (0.1.7)
    Requirement already satisfied: pywinpty>=0.5; os_name == "nt" in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from terminado>=0.8.1->notebook->jupyter>=1.0.0->stata_kernel) (0.5.1)
    Requirement already satisfied: MarkupSafe>=0.23 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from jinja2->notebook->jupyter>=1.0.0->stata_kernel) (1.0)
    Requirement already satisfied: jsonschema!=2.5.0,>=2.4 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from nbformat->notebook->jupyter>=1.0.0->stata_kernel) (2.6.0)
    Requirement already satisfied: html5lib!=0.9999,!=0.99999,<0.99999999,>=0.999 in d:\mysites\deeplearning.ai-master\.env\lib\site-packages (from bleach->nbconvert->jupyter>=1.0.0->stata_kernel) (0.9999999)
    spacy 2.0.11 has requirement regex==2017.4.5, but you'll have regex 2018.8.29 which is incompatible.
    jupyter-console 5.2.0 has requirement prompt-toolkit<2.0.0,>=1.0.0, but you'll have prompt-toolkit 2.0.5 which is incompatible.
    Installing collected packages: requests, packaging, ptyprocess, pexpect, pandas, regex, prompt-toolkit, IPython, beautifulsoup4, pillow, stata-kernel
    Found existing installation: requests 2.18.4
    Uninstalling requests-2.18.4:
    Successfully uninstalled requests-2.18.4
    Found existing installation: pandas 0.23.0
    Uninstalling pandas-0.23.0:
    Successfully uninstalled pandas-0.23.0
    Found existing installation: regex 2017.4.5
    Uninstalling regex-2017.4.5:
    Successfully uninstalled regex-2017.4.5
    Found existing installation: prompt-toolkit 1.0.15
    Uninstalling prompt-toolkit-1.0.15:
    Successfully uninstalled prompt-toolkit-1.0.15
    Found existing installation: ipython 6.4.0
    Uninstalling ipython-6.4.0:
    Successfully uninstalled ipython-6.4.0
    Found existing installation: Pillow 5.1.0
    Uninstalling Pillow-5.1.0:
    Successfully uninstalled Pillow-5.1.0
    Successfully installed IPython-7.0.1 beautifulsoup4-4.6.3 packaging-18.0 pandas-0.23.4 pexpect-4.6.0 pillow-5.3.0 prompt-toolkit-2.0.5 ptyprocess-0.6.0 regex-2018.8.29 requests-2.19.1 stata-kernel-1.5.5
    You are using pip version 18.0, however version 18.1 is available.
    You should consider upgrading via the 'python -m pip install --upgrade pip' command.

    使用方法

    打开你的notebook:

    1
    jupyter notebook

    然后, 创建一个statanotebook:

    最后, 你就可以在cell中写stata命令了:

    教程到这里就结束了, 希望大家关注mlln.cn, 以后还会有stata的教程。

    统计咨询

    统计咨询请加入我的星球,有问必回

    加入星球向我提问(必回),下载资料,数据,软件等

    赞助

    持续创造有价值的内容, 我需要你的帮助