springcoil

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springcoil

csvsql --db postgresql:///test1 --insert Problem_Set_Operations_Research.csv
# I was having some trouble getting a csv file inserted into a Postgres Database. The above line worked.
\dt
#Shows the tables in a particular database
\connect test1
#Connects to a database with a particular name in the case above "test1"

springcoil

# -*- coding: utf-8 -*-
"""
LICENSE: BSD (same as pandas)
example use of pandas with oracle mysql postgresql sqlite
    - updated 9/18/2012 with better column name handling; couple of bug fixes.
    - used ~20 times for various ETL jobs.  Mostly MySQL, but some Oracle. 

    to do:  
            save/restore index (how to check table existence? just do select count(*)?), 
            finish odbc, 

springcoil

install.packages("caret")
install.packages("rpart")
install.packages("tree")
install.packages("randomForest")
install.packages("e1071")
install.packages("ggplot2")
table <- read.csv("DataSciIntro/assignment5//seaflow_21min.csv")

library("caret")
library("rpart")

springcoil

install.packages("caret")
install.packages("rpart")
install.packages("tree")
install.packages("randomForest")
install.packages("e1071")
install.packages("ggplot2")
table <- read.csv("DataSciIntro/assignment5//seaflow_21min.csv")

library("caret")
library("rpart")

springcoil

#!/bin/bash
virtualenv .env &&
source .env/bin/activate &&
sudo apt-get install -y libevent-dev &&
sudo apt-get install -y libyaml-0-2 &&
sudo apt-get install --yes --force-yes automake autoconf libtool* gfortran &&
sudo apt-get install --yes --force-yes liblapack-dev &&
sudo apt-get install --yes --force-yes binutils &&
sudo apt-get install -y libatlas-dev &&
sudo apt-get install -y build-essential --upgrade &&

springcoil

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springcoil

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springcoil

# -*- coding: utf-8 -*-
"""
Sample report generation script from pbpython.com

This program takes an input Excel file, reads it and turns it into a
pivot table.

The output is saved in multiple tabs in a new Excel file.
"""

springcoil

g = simuls.groupby('Team')
season_hdis = pd.DataFrame({'points_lower': g.points.quantile(.05),
                            'points_upper': g.points.quantile(.95),
                            'goals_for_lower': g.gf.quantile(.05),
                            'goals_for_median': g.gf.median(),
                            'goals_for_upper': g.gf.quantile(.95),
                            'goals_against_lower': g.ga.quantile(.05),
                            'goals_against_upper': g.ga.quantile(.95),
                            })
season_hdis = pd.merge(season_hdis, df_observed, left_index=True, right_on='Team')