See the website for this project here: https://ckalitin.github.io/space/2025/06/08/space-industry-charts.html

Example Charts

Installation

Install from PyPI

The easiest way to install the package is via PyPI:

pip install mcdowell-dataset-analysis

Local Installation (Optional)

For modifying the code locally, without having to deal with PyPI every time you make a change:

1. Clone the repository:

   git clone https://github.com/CKalitin/mcdowell-dataset-analysis.git
   cd mcdowell-dataset-analysis

2. Install in editable mode (remember the dot at the end!!):

   pip install -e .

   If using Github desktop, run only this command in the base directory of this repo in the VS Code terminal.

Dependencies

The package requires:

• pandas>=2.0.0
• matplotlib>=3.5.0
• plotly>=5.0.0
• kaleido>=0.2.1

These are automatically installed when you use pip.

Note that plotly requires a chromium-based browser to be installed to render charts. Firefox users beware!

Updating Datasets

The datasets currently have data up until December 1 2025.

To update the datasets, you can use the update_datasets.py script. This script fetches the latest data from Jonathan McDowell's website and updates the local TSV files.

If the script fails, manually download the datasets as instructed in How-To-Update-Datasets.md.

Block Diagram

Drawio Google Drive Link

TODO

1. Documentation of all the columns in my dataframes + mcdowell documentation
2. Line charts (eg. launches per country or pad)
3. Pie charts
4. Launch Types
   • Small sat payload type
   • Small sat operator type
   • General operator type?
   • F9 payload type
5. F9 Booster Launches Line Chart
6. ULA charts (really haven't launched more than once a month for a decade?)
7. Error message for nothing in dataframe after filters

Types of charts:

• Launch Provider charts
• Country payload & launches charts
• Launches by launch pad (for all existing types of charts)