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materials's Introduction

Join the chat at https://gitter.im/Analyticsdojo/Analyticsdojo

AnalyticsDojo is a data science community where you learn to data science and work on real projects. This repository contains a number of different sources of materials to use for analytics.

In order to get started with the Jupyter data science container, try the following command.

Note: You need to (a) download this directory and (b) change to the materials directory.

docker run -d -p 8888:8888  -e GRANT_SUDO=yes  --name analyticsdojo  -v {enter path to materials directory}/materials/analyticsdojo:/home/jovyan/work jupyter/datascience-notebook start-notebook.sh

In the above command, you need to customize the location of the directory. For example, on my machine it is the following:

docker run -d -p 8888:8888  -e GRANT_SUDO=yes  --name analyticsdojo  -v /Users/jasonkuruzovich/githubdesktop/materials/analyticsdojo:/home/jovyan/work jupyter/datascience-notebook start-notebook.sh

On a Windows machine, it might be the following:

docker run -d -p 8888:8888  -e GRANT_SUDO=yes  --name analyticsdojo  -v /C//Users/jkuruzovich/materials/analyticsdojo:/home/jovyan/work jupyter/datascience-notebook start-notebook.sh

If you reboot and later find that the container is not running, you can start it from the command line with docker start analyticsdojo

If you enter the wrong file path:

docker stop analyticsdojo
docker rm analyticsdojo 

Then rerun the command.

This will launch a container (called analyticsdojo) and share the appropriate directory with the container. This will allow the container to easily share files and notebooks with the operating system.

If everything is working correctly then http://localhost:8888/ will show the root directory of this repository in the Jupyter console.

Console

To launch the Spark notebook, follow a similar command:

docker run -d -p 8888:8888  -e GRANT_SUDO=yes  --name analyticsdojo_pyspark  -v /Users/jasonkuruzovich/githubdesktop/materials/analyticsdojo:/home/jovyan/work jupyter/pyspark-notebook  start-notebook.sh

License

Please check the individual directories regarding the licensing. Because this project incorporates materials from different project, the subdirectories had different required attribuiton and licensing.

materials's People

Contributors

parente avatar jkuruzovich avatar jakirkham avatar minrk avatar rgbkrk avatar poplav avatar willingc avatar costerwi avatar tylere avatar abtrout avatar jtyberg avatar alewitt avatar fperez avatar mkolovic avatar apurvann avatar jcfr avatar depend avatar carreau avatar rissem avatar okoethibm avatar leosartaj avatar eigengrau avatar gitter-badger avatar wernight avatar

Stargazers

Reynaldo Méndez Robles avatar Mallikarjuna Gandhamsetty avatar Shrey Shrivastava avatar Adithya  avatar Yosin030 avatar  avatar  avatar Craig DeBono avatar  avatar Leah_RPI avatar Chien-Wei Ho avatar  avatar

Watchers

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materials's Issues

Salesforce Pipeline to Redshift

The goal of this work is to develop a pipeline from Salesforce to Redshift. We have had a number of different Capstone projects involving Salesforce, and this is a powerful technology.

The idea solution would be able to:
-navigate salesforce object metadata
-create structures in Redshift
-Extract and load to redshift all data, recording time.
-Update only new records.

Twitter Data Extraction

Twitter is an interesting data source for scientific inquiry and analysis. We would like to develop a way to extract data out of Twitter for further analysis via Spark/etc.

Salesforce Visualization Via Plotly

A proof of concept dashboard via plotly.

Extract data out of Redshift.

Perform necessary aggregations.

Visualize:

New Leads
Leads over time
Leads/Opportunities Pipeline.

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