blitzly โก๏ธ
Lightning-fast way to get plots with Plotly
Introduction ๐
Plotly is great and powerful. But with great power comes great responsibility
Check out some examples in the Jupyter notebook.
Install the package ๐ฆ
If you are using pip, you can install the package with the following command:
pip install blitzlyIf you are using Poetry, you can install the package with the following command:
poetry add blitzly
installing dependencies ๐งโ๐ง
With pip:
pip install -r requirements.txtWith Poetry:
poetry install
Available plots (so far ๐ )
| Module | Method | Description |
|---|---|---|
bar |
multi_chart |
Creates a bar chart with multiple groups. |
dumbbell |
simple_dumbbell |
Plots a dumbbell plot. This can be used to compare two columns of data to visualize changes. |
histogram |
simple_histogram |
Plots a histogram with one ore more distributions. |
matrix |
binary_confusion_matrix |
Plots a confusion matrix for binary classification data. |
matrix |
pearson_corr_matrix |
Plots a Pearson product-moment correlation coefficients matrix. |
scatter |
scatter_matrix |
Plots a scatter matrix. |
scatter |
multi_scatter |
Create a multi scatter plot. It can be used to visualize the relationship between multiple variables from the same Pandas DataFrame. |
Subplots ๐จโ๐ฉโ๐งโ๐ฆ
| Module | Method | Description |
|---|---|---|
subplots |
make_subplots |
Create subplots using figure objects created with any of the above available plots. |
Usage ๐ค
Here are some examples. You can also open the playground notebook
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 ๐",
mark_x_labels=["Lisbon"],
write_html_path="see_the_blitz.html",
)Gives you this:
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 ๐",
show_upper_half=True,
diagonal_visible=False,
marker_color_scale="Rainbow",
marker_line_color="blue",
size=(500, 500),
)Gives you this:
Contributing ๐ฉโ๐ป
Please check out the guide on how to contribute to this project.
![github-actions[bot]](https://avatars.githubusercontent.com/u/41898282?size=120)
