PyBerries
PyBerries is a Python package that can be used to import, manipulate and plot data from Bacmman measurement tables.
It relies mainly on Pandas for data handling and Seaborn/Matplotlib for plotting.
Installation
Optional: install Jupyter-lab (to run Jupyter Notebooks)
Anaconda (recommended)
Anaconda will install both Python and Jupyter-lab (used to run Python notebooks) easily. Note however that it requires ~5 Gb free disk space. For a lighter installation procedure, see the next section "Command line install".
- Download Anaconda from the official website
- Run the installer (leave all options as default)
- Start "Anaconda Navigator"
- In Anaconda, launch the "Jupyter Lab" module (you might need to click on "Install" first)
Command line install
- Open a terminal (macOS/Linux) or Powershell (Windows)
- Install Python
- Enter the command
python --version - If an error or a version < 3.9 is shown, download and install Python from the official website
- Enter the command
- After installing, restart your terminal/powershell; the
python --versioncommand should display a version number > 3.9 - Install Jupyter Lab
- In a terminal/powershell, run the command
python -m pip install jupyterlab - After the installation completes, Jupyter Lab can be started using the command
jupyter-lab
- In a terminal/powershell, run the command
Installing the package
To install the package, use the following command in a terminal:
python -m pip install PyBerries
You can also install a specific version number (useful e.g. to make sure you code won't be broken by a future update):
python -m pip install PyBerries==0.2.8
In a jupyter notebook, use the command:
%pip install PyBerries, or %pip install PyBerries==0.2.8 for a specific version.
Getting started
Try downloading and running the tutorial notebook to get acquainted with data import and plotting in PyBerries.
For further details, see the main functionalities documentation, as well as the DatasetPool documentation.
For more info and examples on plots, see the plot_preset documentation and the Seaborn documentation
Contact
For questions and feedback related to this package please send an email to daniel.thedie@ed.ac.uk
Metadata
Release files for PyBerries 0.2.26
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| pyberries-0.2.26.tar.gz | 26.6 kB | Without provenance | Details for pyberries-0.2.26.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| PyBerries-0.2.26-py3-none-any.whl | Python 3 | none | any | Details for PyBerries-0.2.26-py3-none-any.whl |
Total release size: 54.8 kB
Release files / pyberries-0.2.26.tar.gz
| Download URL | pyberries-0.2.26.tar.gz |
|---|---|
| Size | 26.6 kB |
| Tags | Source |
|
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No |
| Uploaded via |
twine/4.0.2 CPython/3.11.3
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Release files / PyBerries-0.2.26-py3-none-any.whl
| Download URL | PyBerries-0.2.26-py3-none-any.whl |
|---|---|
| Size | 28.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.3
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Security for PyBerries 0.2.26
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