Visualization Tools
This document is a simple how-to for exporting data from the CoyPu graph and loading it into various external tools. Other helpful tools are collected here.
Get data as CSV
- Navigate to the Skynet query interface: https://skynet.coypu.org/#/dataset/coypu-internal/query
- In the query window, enter the SPARQL query to retrieve the data you want to export
- Click on the "Results" tab, then select "CSV" as the format
- Click on the "Apply" button to execute the query
- Download the resulting CSV file by clicking the "Download" button
Visualize with Tableau
- Open Tableau and connect to your data by clicking on "Connect to Data" and then selecting "Text File"
- Browse to your CSV file and select it
- Tableau will automatically detect the file structure and create a data source
- Drag and drop the fields you want to use in your visualization onto the Rows and Columns shelves
- Use the visualization types in the top right corner to create your desired visualization
- Use the options in the top right corner to customize the visualization as needed
Visualize with Looker
- Import your CSV file into Looker:
- Go to the "Develop" tab in the Looker web interface
- Click on the "Add Data" button
- Select "Upload a file" and browse to your CSV file
- Looker will automatically create a new model for your data
- Create a new LookML Project:
- Go to the "Develop" tab
- Click on the "+" button next to "Projects"
- Enter a name for your project and click on "Create"
- Create a new Look:
- Go to the "Looks" tab
- Click on the "+" button
- Select the model that Looker created for your data
- Choose the fields you want to include in the visualization
- Select a visualization type (such as a bar chart, line chart, or table)
- Customize the visualization as needed
Visualize with Power BI
- Import your CSV file:
- Open Power BI Desktop
- Click on "Home" and then "Get Data"
- Select "File" and then "Browse"
- Browse to your CSV file and select it
- In the "Import" dialog box, select "Load" to load the data into Power BI
- Create a new report:
- Once the data is loaded, you can create a new report by clicking on "Home" and then "New Report"
- Drag the fields you want to use in your visualization from the "Fields" pane on the right to the "Values" or "Axis" sections of the "Visualizations" pane on the left.
- Select visualization type:
- Select visualization type (such as a bar chart, line chart, or table) in the "Visualizations" pane.
- You can also use the "Visualizations" pane to customize the visualization as needed.
Visualize with Plotly Express in Python
import plotly.express as px
import pandas as pd
# Read the CSV file into a pandas DataFrame
df = pd.read_csv('file.csv')
# Create the scattermapbox plot
fig = px.scatter_mapbox(df, lat='latitude', lon='longitude',
mapbox_style='open-street-map', zoom=5)
# Show the plot
fig.show()
Note: make sure the CSV file contains the referenced columns.