Command-line data analytics made easy with SPyQL

• spyql

  23 902 0.0 Jupyter Notebook

  Query data on the command line with SQL-like SELECTs powered by Python expressions

These motivated me to write a command-line tool that focus on readability, easiness to learn and modern data formats, while leveraging the command-line ecosystem. On top of that, it also leverages the Python ecosystem! Meet SPyQL - SQL with Python in the middle:

• matplotcli

  2 50 0.0 Python

  Create matplotlib visualizations from the command-line

Notice the pretty printing output. We can plot the above results by setting the output format to JSON and piping results into MatplotCLI:

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• h3-py

  1 758 6.6 Python

  Python bindings for H3, a hierarchical hexagonal geospatial indexing system

  

Another advantage of SPyQL is that we can leverage the Python ecosystem. Let's try to do some more geographical statistics. Let's count towers by H3 cell (resolution 5) for Europe. First, we need to install the H3 lib:

• cheatsheets

  126 7,245 7.0 Python

  Official Matplotlib cheat sheets (by matplotlib)

  

Let's also install MatplotCLI, a utility for creating plots from the command-line that leverages Matplotlib:

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