if you are using linux, unix, os x:
pip install -U setuptools
pip install -U pip
pip install numpy
pip install scipy
pip install matplotlib
#pip install PySide
| #!/usr/bin/env bash | |
| # Author: Sasha Nikiforov | |
| # source of inspiration | |
| # https://stackoverflow.com/questions/41293077/how-to-compile-tensorflow-with-sse4-2-and-avx-instructions | |
| # Detect platform | |
| if [ "$(uname)" == "Darwin" ]; then | |
| # MacOS |
| ''' | |
| Non-parametric computation of entropy and mutual-information | |
| Adapted by G Varoquaux for code created by R Brette, itself | |
| from several papers (see in the code). | |
| This code is maintained at https://github.com/mutualinfo/mutual_info | |
| Please download the latest code there, to have improvements and | |
| bug fixes. |
| import pymssql | |
| import pandas as pd | |
| ## instance a python db connection object- same form as psycopg2/python-mysql drivers also | |
| conn = pymssql.connect(server="172.0.0.1", user="howens",password="some_fake_password", port=63642) # You can lookup the port number inside SQL server. | |
| ## Hey Look, college data | |
| stmt = "SELECT * FROM AlumniMirror..someTable" | |
| # Excute Query here | |
| df = pd.read_sql(stmt,conn) |
| # Test of Significance, takes the same arguments as t.test() . | |
| signif.test <- function(x, ...) { | |
| p <- t.test(x, ...)$p.value | |
| # List of p excuses retrieved from http://mchankins.wordpress.com/2013/04/21/still-not-significant-2/ | |
| p_excuses <- c( | |
| "(barely) not statistically significant <p>", | |
| "a barely detectable statistically significant difference <p>", | |
| "a borderline significant trend <p>", | |
| "a certain trend toward significance <p>", |
if you are using linux, unix, os x:
pip install -U setuptools
pip install -U pip
pip install numpy
pip install scipy
pip install matplotlib
#pip install PySide