<img src="https://github.com/invia-flights/blitzly/raw/main/docs/assets/images/icon.png" alt="blitzly logo" width="200" height="200"/><br>
# blitzly ⚡️
***Lightning-fast way to get plots with Plotly***
[](https://github.com/invia-flights/blitzly/actions/workflows/deploy-package.yml)
[](https://github.com/invia-flights/blitzly/actions/workflows/testing.yml)
[](https://codecov.io/gh/invia-flights/blitzly)
[](https://pypi.org/project/blitzly/)
[](https://pypistats.org/packages/blitzly)
[](https://www.python.org/downloads/)
[](https://invia-flights.github.io/blitzly/)
[](https://github.com/pre-commit/pre-commit)
[](https://github.com/invia-flights/blitzly/blob/main/LICENSE)
[](https://github.com/PyCQA/isort)
[](https://github.com/psf/black)
[](https://github.com/python/mypy)
[](https://github.com/PyCQA/pylint)
## Introduction 🎉
Plotly is great and powerful. But with great power comes great responsibility 🕸. And sometimes you just want to get a plot up and running as fast as possible. That's where blitzly ⚡️ comes in. It provides a set of functions that allow you to create plots with Plotly in a lightning-fast way. It's not meant to replace Plotly, but rather to complement it.
Check out some examples in the [Jupyter notebook](https://github.com/invia-flights/blitzly/blob/main/examples/playground.ipynb).<br>
[](https://colab.research.google.com/github/invia-flights/blitzly/blob/main/examples/playground.ipynb)
## Install the package 📦
If you are using [pip](https://pip.pypa.io/en/stable/), you can install the package with the following command:
```bash
pip install blitzly
```
If you are using [Poetry](https://python-poetry.org/), you can install the package with the following command:
```bash
poetry add blitzly
```
## installing dependencies 🧑🔧
With [pip](https://pip.pypa.io/en/stable/):
```bash
pip install -r requirements.txt
```
With [Poetry](https://python-poetry.org/):
```bash
poetry install
```
## Available plots (so far 🚀)
| Module | Method | Description |
| ------ | ------ | ----------- |
| [`bar`](https://invia-flights.github.io/blitzly/plots/bar/) | [`model_feature_importances`](https://invia-flights.github.io/blitzly/plots/bar/#blitzly.plots.bar.model_feature_importances) | Creates a bar chart with the feature importance of a model. |
| [`bar`](https://invia-flights.github.io/blitzly/plots/bar/) | [`multi_chart`](https://invia-flights.github.io/blitzly/plots/bar/#blitzly.plots.bar.multi_chart) | Creates a bar chart with multiple groups. |
| [`dumbbell`](https://invia-flights.github.io/blitzly/plots/dumbbell/) | [`simple_dumbbell`](https://invia-flights.github.io/blitzly/plots/dumbbell/#blitzly.plots.dumbbell.simple_dumbbell) | Plots a dumbbell plot. This can be used to compare two columns of data to visualize changes. |
| [`histogram`](https://invia-flights.github.io/blitzly/plots/histogram/) | [`simple_histogram`](https://invia-flights.github.io/blitzly/plots/histogram/#blitzly.plots.histogram.simple_histogram) | Plots a histogram with one ore more distributions. |
| [`matrix`](https://invia-flights.github.io/blitzly/plots/matrix/) | [`binary_confusion_matrix`](https://invia-flights.github.io/blitzly/plots/matrix/#blitzly.plots.matrix.binary_confusion_matrix) | Plots a confusion matrix for binary classification data. |
| [`matrix`](https://invia-flights.github.io/blitzly/plots/matrix/) | [`cramers_v_corr_matrix`](https://invia-flights.github.io/blitzly/plots/matrix/#blitzly.plots.matrix.cramers_v_corr_matrix) | Cramer's V correlation for categorical features. |
| [`matrix`](https://invia-flights.github.io/blitzly/plots/matrix/) | [`pearson_corr_matrix`](https://invia-flights.github.io/blitzly/plots/matrix/#blitzly.plots.matrix.pearson_corr_matrix) | Plots a Pearson product-moment correlation coefficients matrix. |
| [`scatter`](https://invia-flights.github.io/blitzly/plots/scatter/) | [`scatter_matrix`](https://invia-flights.github.io/blitzly/plots/scatter/#blitzly.plots.scatter.scatter_matrix) | Plots a scatter matrix. |
| [`scatter`](https://invia-flights.github.io/blitzly/plots/scatter/) | [`multi_scatter`](https://invia-flights.github.io/blitzly/plots/scatter/#blitzly.plots.scatter.multi_scatter) | Create a multi scatter plot. It can be used to visualize the relationship between multiple variables from the same Pandas DataFrame. |
| [`scatter`](https://invia-flights.github.io/blitzly/plots/scatter/) | [`dimensionality_reduction`](https://invia-flights.github.io/blitzly/plots/scatter/#blitzly.plots.scatter.dimensionality_reduction) | Creates a plot to visualize higher dimensionality reduced data using matrix decomposition |
### Subplots 👩👩👧👦
| Module | Method | Description |
| ------ | ------ | ----------- |
| [`subplots`](https://invia-flights.github.io/blitzly/plots/subplots/) | [`make_subplots`](https://invia-flights.github.io/blitzly/plots/subplots/#blitzly.subplots.make_subplots) | Create subplots using figure objects created with any of the above available plots. |
## Usage 🤌
Here are some examples. You can also open the [playground notebook](https://github.com/invia-flights/blitzly/blob/main/examples/playground.ipynb) 📒.
**[`dimensionality_reduction`](https://invia-flights.github.io/blitzly/plots/scatter/#blitzly.plots.scatter.dimensionality_reduction):**
```python
from blitzly.plots.scatter import dimensionality_reduction
import plotly.express as px
df = px.data.iris()
dimensionality_reduction(
df,
n_components=2,
target_column="species",
reduction_funcs=["PCA", "TNSE"],
)
```
Gives you this:
<img src="https://github.com/invia-flights/blitzly/raw/main/docs/assets/images/example_plots/dimensionality_reduction.png" alt="dimensionality reduction plot" width="1000" height="555"/>
**[`multi_bar`](https://invia-flights.github.io/blitzly/plots/bar/#blitzly.plots.bar.multi_bar):**
```python
from blitzly.plots.bar import multi_bar
import numpy as np
data = np.array([[8, 3, 6], [9, 7, 5]])
error_array = np.array([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]])
multi_bar(
data,
x_labels=["Vienna", "Berlin", "Lisbon"],
group_labels=["Personal rating", "Global rating"],
errors=error_array,
title="City ratings 🏙",
mark_x_labels=["Lisbon"],
write_html_path="see_the_blitz.html",
)
```
Gives you this:
<img src="https://github.com/invia-flights/blitzly/raw/main/docs/assets/images/example_plots/multi_bars.png" alt="multi bars plot" width="1000" height="555"/>
**[`scatter matrix`](https://invia-flights.github.io/blitzly/plots/scatter/#blitzly.plots.scatter.scatter_matrix):**
```python
from blitzly.plots.scatter import scatter_matrix
import numpy as np
import pandas as pd
foo = np.random.randn(1000)
bar = np.random.randn(1000) + 1
blitz = np.random.randint(2, size=1000)
licht = np.random.randint(2, size=1000)
data = np.array([foo, bar, blitz, licht])
df = pd.DataFrame(data.T, columns=["foo", "bar", "blitz", "licht"])
scatter_matrix(
df,
dimensions=["foo", "bar", "blitz"],
color_dim=df["licht"],
title="My first scatter matrix 🙃",
show_upper_half=True,
diagonal_visible=False,
marker_color_scale="Rainbow",
marker_line_color="blue",
size=(500, 500),
)
```
Gives you this:
<img src="https://github.com/invia-flights/blitzly/raw/main/docs/assets/images/example_plots/scatter_matrix.png" alt="scatter-matrix plot" width="500" height="500"/>
## Contributing 👩💻
Please check out the [guide](https://invia-flights.github.io/blitzly/CONTRIBUTING/) on how to contribute to this project.
Raw data
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"description": "<img src=\"https://github.com/invia-flights/blitzly/raw/main/docs/assets/images/icon.png\" alt=\"blitzly logo\" width=\"200\" height=\"200\"/><br>\n# blitzly \u26a1\ufe0f\n***Lightning-fast way to get plots with Plotly***\n\n[](https://github.com/invia-flights/blitzly/actions/workflows/deploy-package.yml)\n[](https://github.com/invia-flights/blitzly/actions/workflows/testing.yml)\n[](https://codecov.io/gh/invia-flights/blitzly)\n[](https://pypi.org/project/blitzly/)\n[](https://pypistats.org/packages/blitzly)\n[](https://www.python.org/downloads/)\n[](https://invia-flights.github.io/blitzly/)\n[](https://github.com/pre-commit/pre-commit)\n[](https://github.com/invia-flights/blitzly/blob/main/LICENSE)\n[](https://github.com/PyCQA/isort)\n[](https://github.com/psf/black)\n[](https://github.com/python/mypy)\n[](https://github.com/PyCQA/pylint)\n## Introduction \ud83c\udf89\nPlotly is great and powerful. But with great power comes great responsibility \ud83d\udd78. And sometimes you just want to get a plot up and running as fast as possible. That's where blitzly \u26a1\ufe0f comes in. It provides a set of functions that allow you to create plots with Plotly in a lightning-fast way. It's not meant to replace Plotly, but rather to complement it.\n\nCheck out some examples in the [Jupyter notebook](https://github.com/invia-flights/blitzly/blob/main/examples/playground.ipynb).<br>\n[](https://colab.research.google.com/github/invia-flights/blitzly/blob/main/examples/playground.ipynb)\n\n## Install the package \ud83d\udce6\nIf you are using [pip](https://pip.pypa.io/en/stable/), you can install the package with the following command:\n```bash\npip install blitzly\n```\n\nIf you are using [Poetry](https://python-poetry.org/), you can install the package with the following command:\n```bash\npoetry add blitzly\n```\n## installing dependencies \ud83e\uddd1\u200d\ud83d\udd27\nWith [pip](https://pip.pypa.io/en/stable/):\n```bash\npip install -r requirements.txt\n```\n\nWith [Poetry](https://python-poetry.org/):\n```bash\npoetry install\n```\n## Available plots (so far \ud83d\ude80)\n| Module | Method | Description |\n| ------ | ------ | ----------- |\n| [`bar`](https://invia-flights.github.io/blitzly/plots/bar/) | [`model_feature_importances`](https://invia-flights.github.io/blitzly/plots/bar/#blitzly.plots.bar.model_feature_importances) | Creates a bar chart with the feature importance of a model. |\n| [`bar`](https://invia-flights.github.io/blitzly/plots/bar/) | [`multi_chart`](https://invia-flights.github.io/blitzly/plots/bar/#blitzly.plots.bar.multi_chart) | Creates a bar chart with multiple groups. |\n| [`dumbbell`](https://invia-flights.github.io/blitzly/plots/dumbbell/) | [`simple_dumbbell`](https://invia-flights.github.io/blitzly/plots/dumbbell/#blitzly.plots.dumbbell.simple_dumbbell) | Plots a dumbbell plot. This can be used to compare two columns of data to visualize changes. |\n| [`histogram`](https://invia-flights.github.io/blitzly/plots/histogram/) | [`simple_histogram`](https://invia-flights.github.io/blitzly/plots/histogram/#blitzly.plots.histogram.simple_histogram) | Plots a histogram with one ore more distributions. |\n| [`matrix`](https://invia-flights.github.io/blitzly/plots/matrix/) | [`binary_confusion_matrix`](https://invia-flights.github.io/blitzly/plots/matrix/#blitzly.plots.matrix.binary_confusion_matrix) | Plots a confusion matrix for binary classification data. |\n| [`matrix`](https://invia-flights.github.io/blitzly/plots/matrix/) | [`cramers_v_corr_matrix`](https://invia-flights.github.io/blitzly/plots/matrix/#blitzly.plots.matrix.cramers_v_corr_matrix) | Cramer's V correlation for categorical features. |\n| [`matrix`](https://invia-flights.github.io/blitzly/plots/matrix/) | [`pearson_corr_matrix`](https://invia-flights.github.io/blitzly/plots/matrix/#blitzly.plots.matrix.pearson_corr_matrix) | Plots a Pearson product-moment correlation coefficients matrix. |\n| [`scatter`](https://invia-flights.github.io/blitzly/plots/scatter/) | [`scatter_matrix`](https://invia-flights.github.io/blitzly/plots/scatter/#blitzly.plots.scatter.scatter_matrix) | Plots a scatter matrix. |\n| [`scatter`](https://invia-flights.github.io/blitzly/plots/scatter/) | [`multi_scatter`](https://invia-flights.github.io/blitzly/plots/scatter/#blitzly.plots.scatter.multi_scatter) | Create a multi scatter plot. It can be used to visualize the relationship between multiple variables from the same Pandas DataFrame. |\n| [`scatter`](https://invia-flights.github.io/blitzly/plots/scatter/) | [`dimensionality_reduction`](https://invia-flights.github.io/blitzly/plots/scatter/#blitzly.plots.scatter.dimensionality_reduction) | Creates a plot to visualize higher dimensionality reduced data using matrix decomposition |\n\n\n### Subplots \ud83d\udc69\u200d\ud83d\udc69\u200d\ud83d\udc67\u200d\ud83d\udc66\n\n| Module | Method | Description |\n| ------ | ------ | ----------- |\n| [`subplots`](https://invia-flights.github.io/blitzly/plots/subplots/) | [`make_subplots`](https://invia-flights.github.io/blitzly/plots/subplots/#blitzly.subplots.make_subplots) | Create subplots using figure objects created with any of the above available plots. |\n\n## Usage \ud83e\udd0c\nHere are some examples. You can also open the [playground notebook](https://github.com/invia-flights/blitzly/blob/main/examples/playground.ipynb) \ud83d\udcd2.\n\n**[`dimensionality_reduction`](https://invia-flights.github.io/blitzly/plots/scatter/#blitzly.plots.scatter.dimensionality_reduction):**\n```python\nfrom blitzly.plots.scatter import dimensionality_reduction\nimport plotly.express as px\n\ndf = px.data.iris()\ndimensionality_reduction(\n df,\n n_components=2,\n target_column=\"species\",\n reduction_funcs=[\"PCA\", \"TNSE\"],\n)\n```\nGives you this:\n<img src=\"https://github.com/invia-flights/blitzly/raw/main/docs/assets/images/example_plots/dimensionality_reduction.png\" alt=\"dimensionality reduction plot\" width=\"1000\" height=\"555\"/>\n\n\n**[`multi_bar`](https://invia-flights.github.io/blitzly/plots/bar/#blitzly.plots.bar.multi_bar):**\n```python\nfrom blitzly.plots.bar import multi_bar\nimport numpy as np\n\ndata = np.array([[8, 3, 6], [9, 7, 5]])\nerror_array = np.array([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]])\n\nmulti_bar(\n data,\n x_labels=[\"Vienna\", \"Berlin\", \"Lisbon\"],\n group_labels=[\"Personal rating\", \"Global rating\"],\n errors=error_array,\n title=\"City ratings \ud83c\udfd9\",\n mark_x_labels=[\"Lisbon\"],\n write_html_path=\"see_the_blitz.html\",\n)\n```\nGives you this:\n<img src=\"https://github.com/invia-flights/blitzly/raw/main/docs/assets/images/example_plots/multi_bars.png\" alt=\"multi bars plot\" width=\"1000\" height=\"555\"/>\n\n**[`scatter matrix`](https://invia-flights.github.io/blitzly/plots/scatter/#blitzly.plots.scatter.scatter_matrix):**\n```python\n from blitzly.plots.scatter import scatter_matrix\n import numpy as np\n import pandas as pd\n\n foo = np.random.randn(1000)\n bar = np.random.randn(1000) + 1\n blitz = np.random.randint(2, size=1000)\n licht = np.random.randint(2, size=1000)\n data = np.array([foo, bar, blitz, licht])\n df = pd.DataFrame(data.T, columns=[\"foo\", \"bar\", \"blitz\", \"licht\"])\n\n scatter_matrix(\n df,\n dimensions=[\"foo\", \"bar\", \"blitz\"],\n color_dim=df[\"licht\"],\n title=\"My first scatter matrix \ud83d\ude43\",\n show_upper_half=True,\n diagonal_visible=False,\n marker_color_scale=\"Rainbow\",\n marker_line_color=\"blue\",\n size=(500, 500),\n )\n```\nGives you this:\n<img src=\"https://github.com/invia-flights/blitzly/raw/main/docs/assets/images/example_plots/scatter_matrix.png\" alt=\"scatter-matrix plot\" width=\"500\" height=\"500\"/>\n\n## Contributing \ud83d\udc69\u200d\ud83d\udcbb\n\nPlease check out the [guide](https://invia-flights.github.io/blitzly/CONTRIBUTING/) on how to contribute to this project.\n",
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