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Merge pull request #19 from manumerous/prepare-to-publish
Prepare to publish on Pypi
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.gitignore

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__pycache__/
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/*.csv
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build/
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*.egg-info/
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*.egg-info/
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dist/

README.md

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The Visual Pandas Selector is a tool to visually select portions of numeric time-series data from a pandas dataframe. The tool is intended to provide an fast interactive way for manual data selection, as can be very useful in for example machine learning, regression or system identification.
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The tool is configurable in order to plot a range of dataframe columns in vertically stacked subplots.
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Hereby the user can specify which columns are plotted in which subplot. Furthermore, a histogram is included to get a rough idea on the distribution of the data.
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Easily configure the tool to plot dataframe columns in vertically stacked subplots and view data distributions with the included histogram feature. With a simple click and drag, you can then select horizontal data windows, and let the tool automatically combine them into a new dataframe.
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The user can subsequentially select different horizontal data windows via click and drag and he tool then automatically combines the visually selected sections into a new dataframe.
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## Install
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I am still working on publishing the project on PyPi (any help is apprechiated here). For now you can install the package locally from the top-level project folder using:
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Install the package using:
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```bash
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pip install .
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pip install vpselector
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```
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## Use in your project
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Then simply import it using `import vpselector`. Then simply use:
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- If your project does not contain a pyqt application: `select_visual_data(data : pd.DataFrame, plot_config : dict)`
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- If your project does not contain a pyqt application: `vpselector.select_visual_data(data : pd.DataFrame, plot_config : dict)`
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- To add the vpselector to an existing pyqt application: `select_visual_data_in_pyqt_app(data : pd.DataFrame, plot_config : dict, pyqt_app)`
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- To add the vpselector to an existing pyqt application: `vpselector.select_visual_data_in_pyqt_app(data : pd.DataFrame, plot_config : dict, pyqt_app)`
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## Run the Example

pyproject.toml

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[project]
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name = "vpselector"
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version = "0.1.0"
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version = "1.0.0"
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description = "Visualize and interactively select time-series data from a pandas DataFrame."
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readme = "README.md"
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requires-python = ">=3.8"
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license = {file = "LICENSE.txt"}
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keywords = ["python", "dataframe", "pandas", "visualization", "data selection", "time-series data", "data tools", "data science", "data-driven engineering", "machine learning", "system identification"]
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license = { file = "LICENSE.txt" }
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keywords = [
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"python",
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"dataframe",
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"pandas",
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"visualization",
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"data selection",
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"time-series data",
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"data tools",
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"data science",
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"data-driven engineering",
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"machine learning",
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"system identification",
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]
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authors = [
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{email = "manuel.galliker@gmx.ch"},
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{name = "Manuel Yves Galliker"}
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{ email = "manuel@galliker.tech" },
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{ name = "Manuel Yves Galliker" },
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]
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maintainers = [
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{name = "Manuel Yves Galliker", email = "manuel.galliker@gmx.ch"}
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{ name = "Manuel Yves Galliker", email = "manuel@galliker.tech" },
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]
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classifiers = [
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"Development Status :: 4 - Beta",
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"Programming Language :: Python"
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"Programming Language :: Python",
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]
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dependencies = [
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"matplotlib>=3.7.1",
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"seaborn>=0.11.1",
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"overrides>=7.3.1",
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"twine>=4.0.2",
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]
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[project.optional-dependencies]
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format = [
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"black >= 23.3.0"
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]
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format = ["black >= 23.3.0"]
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[project.urls]
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repository = "https://github.com/manumerous/vpselector"
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repository = "https://github.com/manumerous/vpselector"

src/vpselector/windows/main_window.py

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class MainWindow(QtWidgets.QMainWindow):
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def __init__(self, data : pd.DataFrame , plot_config : dict, *args, **kwargs):
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super(MainWindow, self).__init__(*args, **kwargs)
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self.setWindowTitle("Visual Dataframe Selector")
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self.setWindowTitle("Visual Pandas Selector")
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self.data = data
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self.cropped_data = pd.DataFrame()

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