Mapo AI is a virtual exploration assistant that manages your mineral exploration efforts. To learn more, check out the Mapo Blog Post and Mapo White Paper.
The data
folder contains mineral occurence datasets for:
- Canada > British Columbia
- Canada > Alberta
ariasdata.csv
and arismetadata.csv
- Number of data records: 35,898
- Date of last update: Unknown
MINFILE.csv
- Number of records: 14,817
- Record last modified: 2018-11-27
To re-create MINFILE.csv
, perform the following:
- Go here: http://apps.gov.bc.ca/pub/dwds/addProducts.do
- Search "MINFILE Mineral Occurrence Database"
- Click
+
button to add database to order - Click "View Your Order" button
- Slect "Geographic Long/Lat (dd)" under projection drop-down menu and "CSV" under format drop-down menu
- Type your email address
- Press "I accept the Terms and Conditions"
- Press "Submit Order"
- Receive email from [email protected] with the subject: "Your order XXXXXXX has been assembled"
- Copy URL in the email body (i.e. https://apps.gov.bc.ca/pub/dwds/initiateDownload.do?orderId=XXXXXXX)
- Paste URL into browser to download a ZIP file
- Open ZIP file to extract contents
- Open extracted folder
- Open "MINFIL_MINERAL_FILE" folder
- Use "MINFILE.csv" for data analysis
mrds.csv
- Number of records: 244
- Record last modified: Unknown
To re-create mrds.csv
, perform the following:
- Go here: https://mrdata.usgs.gov/mrds/geo-inventory.php
- Click the "North America" link
- Click the "Canada" link
- Select "CSV" under Format menu
- Click "Download" button
- Look for "British Columbia" rows under the "state" column
Metallic_Mineral_Occurrence.csv
- Website
- Number of records: 385
- Record last modified: 2016-09-23
mrds.csv
- Number of records: 24
- Record last modified: Unknown
To re-create mrds.csv
, perform the following:
- Go here: https://mrdata.usgs.gov/mrds/geo-inventory.php
- Click the "North America" link
- Click the "Canada" link
- Select "CSV" under Format menu
- Click "Download" button
- Look for "Alberta" rows under the "state" column
-
Create environment using pipenv with python 3.6.*
pipenv --python python3.6
-
Enter pipenv environment
pipenv shell
-
Install packages (for development)
pipenv install -d
- To explore the existing datasets, review the
eda
folder - To visualize mineral occurrence data on a map, look for: Latitude, Longitude, Depth, or Elevation values. Use the guide below to get started.
MINFILE.csv
- Relevant columns:
DECIMAL_LATITUDE
,DECIMAL_LONGITUDE
,ELEVATION
,COMMODITY_DESCRIPTION1
,COMMODITY_DESCRIPTION2
,COMMODITY_DESCRIPTION3
,COMMODITY_DESCRIPTION4
,COMMODITY_DESCRIPTION5
,COMMODITY_DESCRIPTION6
,COMMODITY_DESCRIPTION7
,COMMODITY_DESCRIPTION8
- Missing columns: year of discovery
mrds.csv
- Relevant columns:
latitude
,longitude
,commod1
,commod2
,commod3
,disc_yr
- Missing columns: depth or elevation of discovery
Metallic_Mineral_Occurrence.csv
- Relevant columns:
Long_NAD83
,Lat_NAD83
,Depth_m
,Comm_1
,Comm_2
,Location
,Ref_AGS
mrds.csv
- Relevant columns:
latitude
,longitude
,commod1
,commod2
,commod3
,disc_yr
- Missing columns: depth or elevation of discovery