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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

  1. Navigate to the Skynet query interface: https://skynet.coypu.org/#/dataset/coypu-internal/query
  2. In the query window, enter the SPARQL query to retrieve the data you want to export
  3. Click on the "Results" tab, then select "CSV" as the format
  4. Click on the "Apply" button to execute the query
  5. Download the resulting CSV file by clicking the "Download" button

Visualize with Tableau

  1. Open Tableau and connect to your data by clicking on "Connect to Data" and then selecting "Text File"
  2. Browse to your CSV file and select it
  3. Tableau will automatically detect the file structure and create a data source
  4. Drag and drop the fields you want to use in your visualization onto the Rows and Columns shelves
  5. Use the visualization types in the top right corner to create your desired visualization
  6. Use the options in the top right corner to customize the visualization as needed

Visualize with Looker

  1. 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
  2. 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"
  3. 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

  1. 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
  2. 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.
  3. 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.