Standardized plots and visualizations in Python
pltviz is a Python package for standardized visualization. Routine and novel plotting approaches are formatted to allow for easy variation while providing quick and exact results. Coloration functions are also included for precise colors across plots and to assure that all functions can be ran with color hexes.
Contents
Installation ⇧
pltviz can be downloaded from PyPI via pip or sourced directly from this repository:
pip install pltviz
git clone https://github.com/andrewtavis/pltviz.git
cd pltviz
python setup.py install
import pltviz
plot ⇧
Plotting methods within pltviz are tailored to provide quick results for staples of data visualization.
See examples/plot for all plotting styles that seamlessly combine graphing functions of seaborn, matplotlib, and pandas.
import matplotlib.pyplot as plt
import pltviz
Examples of routine plotting techniques made easy are:
# The following will be used for the remaining examples
# German political parties
parties = ['CDU/CSU', 'FDP', 'Greens', 'Die Linke', 'SPD', 'AfD']
party_colors = ['#000000', '#ffed00', '#64a12d', '#be3075', '#eb001f', '#009ee0']
# Hypothetical seat allocations to the Bundestag (German parliament)
seat_allocations = [26, 9, 37, 12, 23, 5]
The following shows pltviz.bar that allows all common options to be selected as binaries:
# Bar plot options such as stacked and label bars are booleans
ax = pltviz.bar(
counts=seat_allocations,
labels=parties,
colors=party_colors,
horizontal=False,
stacked=False,
label_bars=True,
)
# Initialize empty handles and labels
handles, labels = pltviz.legend.gen_elements()
# Add a majority line
ax.axhline(int(sum(seat_allocations) / 2) + 1, ls="--", color="black")
handles.insert(0, Line2D([0], [0], linestyle="--", color="black"))
labels.insert(0, "Majority: {} seats".format(int(sum(seat_allocations) / 2) + 1))
ax.legend(
handles=handles,
labels=labels,
title="Bundestag: {} seats".format(sum(seat_allocations)),
loc="upper left",
bbox_to_anchor=(0, 0.9),
title_fontsize=20,
fontsize=15,
frameon=True,
facecolor="#FFFFFF",
framealpha=1,
)
ax.set_ylabel("Seats", fontsize=15)
ax.set_xlabel("Party", fontsize=15)
Also included is a pltviz.semipie via matplotlib artists for cases where a simple and condensed plot is needed:
ax = pltviz.semipie(counts=seat_allocations, colors=party_colors, donut_ratio=0.5)
handles, labels = pltviz.legend.gen_elements(
counts=seat_allocations,
labels=parties,
colors=party_colors,
)
ax.legend(
handles=handles,
labels=labels,
title="Bundestag: {} seats".format(sum(seat_allocations)),
title_fontsize=20,
fontsize=14,
ncol=2,
loc="center",
bbox_to_anchor=(0.5, 0.17),
frameon=False,
facecolor="#FFFFFF",
framealpha=1,
)
plt.show()
pltviz also includes specialized plots such as pltviz.gini to visualize gini coefficients of inequality:
global_gdp_deciles = [0.49, 0.59, 0.69, 0.79, 1.89, 2.55, 5.0, 10.0, 18.0, 60.0]
ax, gini_coeff = pltviz.gini(shares=global_gdp_deciles)
handles, labels = pltviz.legend.gen_elements(labels=["Lorenz Curve", "Perfect Equality"])
ax.legend(
handles=handles,
labels=labels,
loc='upper left',
bbox_to_anchor=(0, 0.9),
fontsize=20,
frameon=True,
facecolor='#FFFFFF',
framealpha=1)
ax.set_title(f'Gini: {gini_coeff}', fontsize=20)
ax.set_ylabel('Cuumlative Share of Global GDP', fontsize=15)
ax.set_xlabel('Income Deciles', fontsize=15)
plt.show()
To-Do ⇧
Please see the contribution guidelines if you are interested in contributing to this project. Work that is in progress or could be implemented includes:
-
Adding standardized examples of further plots and visualizations (see issue)
-
Finishing the coloration on the outer ring of pltviz.pie
-
Improving tests for greater code coverage
-
Improving code quality by refactoring large functions and checking conventions
-
Allowing all plotting variations to be seamlessly plotted from either lists or dataframe columns where applicable
1.6k Jan 6, 2023
5 Nov 12, 2022
9 Jul 15, 2022
7 Sep 9, 2022
2 Nov 29, 2021
38 Dec 20, 2022
97 Nov 4, 2022
30 Dec 10, 2022
13 Sep 29, 2022
![[ImgBot] Optimize images](https://avatars.githubusercontent.com/in/4706?v=4)
2 Dec 16, 2022
72 Dec 15, 2022
820 Jan 06, 2023
34 Dec 09, 2022
27 Jan 02, 2023
5 Nov 22, 2022
10k Jan 01, 2023
67 Dec 28, 2022
10 Oct 27, 2021
4 May 18, 2022
29 Jul 05, 2022
20 Nov 21, 2022
23 Jan 06, 2023
6 Oct 20, 2022
1.3k Dec 13, 2022
1 Nov 15, 2021
45 Jul 31, 2022
0 Aug 25, 2021
4 Jun 20, 2022
5 Jun 02, 2022