Climate Change Impacts on Terrestrial and Aquatic Ecosystems.pptx
Python crash course for geologists in the mining industry
1. Python crash course
for geologists in the mining industry
Sponsored by
Dates: 5-6 September 2018
Place: Core, 191 St Georges Tce, Perth
Lecturers: Laurent Wagner & Johann Dangin
Max participants: 14
Price: 450euro (about 700AUD) for the 2 days
Pre-requisites: no background in coding is required. You do need to have some sense of
geology to understand the examples and applications given in this course.
Whom for: geologists, mining engineers or managers who want to understand how open
source and scripting can easily be used for day to day tasks in manipulating geological data.
Objectives:
At the end of the 2 days sessions you will be able to :
1. Setup a python environment from scratch
2. Understand basic coding in Python
3. Import geochem and grid data
4. Put your data into custom graphics using Pandas and Seaborn
5. Write procedures to automate tasks such as reporting
6. Understand where to look next
2. Agenda
Day 1 - Introduction to Python
● 9am - 9.30am: Introduction to Python coding
○ How open source is going to change the mining industry
○ Why use Python when you are a geologist
○ Python vs R
● 9.30am - 10.30am: Before you start coding
○ Overview of useful libraries
○ How to set up your computer environment to start coding
● 10.45m - 12pm: Programming in Python
○ Loop, if else
○ Dictionary
○ Pandas dataframe
● 1pm - 2pm: Getting data in
○ Load a file and read it
○ Example on XYZ csv file
○ Use basic plots using Pandas to QC
● 2pm - 3pm: Your first program - Transforming data
○ Basic data manipulation
○ Merging files
○ Data cleaning
Day 2 - Data exploration and plotting using Python
● 9am - 10.30am: Explore a Drillhole file
○ Clean and select the relevant information
○ Merge data
● 10.30am - 12.30pm: Interrogate your data
○ Understand data through general statistics
○ Going further with graphics using Seaborn
● 1.30pm - 3pm: Applications to Model Validation
○ Writing procedure for automatic reporting
○ understanding['more'] = understanding['bits'] + practice['more']
![Agenda
Day 1 - Introduction to Python
● 9am - 9.30am: Introduction to Python coding
○ How open source is going to change the mining industry
○ Why use Python when you are a geologist
○ Python vs R
● 9.30am - 10.30am: Before you start coding
○ Overview of useful libraries
○ How to set up your computer environment to start coding
● 10.45m - 12pm: Programming in Python
○ Loop, if else
○ Dictionary
○ Pandas dataframe
● 1pm - 2pm: Getting data in
○ Load a file and read it
○ Example on XYZ csv file
○ Use basic plots using Pandas to QC
● 2pm - 3pm: Your first program - Transforming data
○ Basic data manipulation
○ Merging files
○ Data cleaning
Day 2 - Data exploration and plotting using Python
● 9am - 10.30am: Explore a Drillhole file
○ Clean and select the relevant information
○ Merge data
● 10.30am - 12.30pm: Interrogate your data
○ Understand data through general statistics
○ Going further with graphics using Seaborn
● 1.30pm - 3pm: Applications to Model Validation
○ Writing procedure for automatic reporting
○ understanding['more'] = understanding['bits'] + practice['more']](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)