post about pypalettes

content/posts/matplotlib/pypalettes/index.md

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+---
+title: "PyPalettes: all the colors you'll ever need"
+description: "Matplotlib is the go-to library for data visualization in Python. While it offers quality built-in colormaps like viridis and inferno, the limited selection can make Matplotlib charts look similar. To address this, I developed pypalettes, a Python library with over 2,500 high-quality, pre-made color palettes. The library includes a web app for browsing and previewing all of them."
+date: 2024-07-10T21:37:03-04:00
+tags: ["matplotlib", "color", "colormap"]
+displayInList: true
+author: ["Joseph Barbier", "Yan Holtz"]
+draft: false
+resources:
+  - name: featuredImage
+    src: "preview.png"
+    params:
+      description: "pypalettes library"
+      showOnTop: false
+---
+
+## Finding the right color has never been easier
+
+[PyPalettes](https://github.com/JosephBARBIERDARNAL/pypalettes) is a new Python library designed to simplify the use of color palettes in Python charts.
+
+It provides mainly two things:
+
+- a [super-easy-to-use library](https://github.com/JosephBARBIERDARNAL/pypalettes) that requires only 1 line of code (in 99.99% of cases, 2 otherwise 🙃) to access thousands of pre-defined and attractive palettes.
+- a [web app](https://python-graph-gallery.com/color-palette-finder/) to browse, filter, search, and preview all available palettes (with **bonus**: copy-pastable code to reproduce the charts).
+
+[![Preview and try all the palettes](https://github.com/holtzy/The-Python-Graph-Gallery/raw/master/static/asset/pypalettes.gif)](https://python-graph-gallery.com/color-palette-finder/)
+
+<center><i>A small sample of the available palettes</i></center>
+
+<br>
+
+## How it happened
+
+In R, there are dozens of packages dedicated to colors for data visualization. Then [Paletteer](https://emilhvitfeldt.github.io/paletteer/) came out to **aggregate** every color palette from those packages into a single one, meaning you **only need one package** to access almost all the color palettes people have created!
+
+While re-crafting the [colors section of the Python Graph Gallery](https://python-graph-gallery.com/python-colors/), I started thinking of a way to have a similar tool to Paletteer but for Python.
+
+<center><h3 style="color: lightgray;">That's where PyPalettes comes in.</h3></center>
+
+Basically, I scraped the [Paletteer gallery](https://pmassicotte.github.io/paletteer_gallery/), which contains all palettes from Paletteer with hexadecimal colors, palette names, and package sources. Then, I added all **built-in colors** from `Matplotlib`.
+
+With these, I was able to create a dataset with around **2500 different palettes**, each with a name and a list of hexadecimal colors.
+
+At this point, the hardest part was already done. I just had to create a simple API to make them usable in a Python environment and add some additional simple features.
+
+And since [Yan](https://www.yan-holtz.com/) supported the idea, he created this amazing [web app](https://python-graph-gallery.com/color-palette-finder/), making it much easier to browse available palettes.
+
+<br>
+
+## How to use pypalettes
+
+The goal was to make the simplest API possible, and I'm quite satisfied with the result. For example, you really like the ["Esox lucius" palette](https://python-graph-gallery.com/color-palette-finder/?palette=Esox_lucius), and you want to make a chart with it.
+
+First, you import the `load_cmap()` function (the main function of the library):
+
+```python
+from pypalettes import load_cmap
+```
+
+And then you just have to call this function with `name="Esox_lucius"`
+
+```python
+cmap = load_cmap("Esox_lucius")
+```
+
+The output of `load_cmap()` is either a [matplotlib.colors.ListedColormap](https://matplotlib.org/stable/api/_as_gen/matplotlib.colors.ListedColormap.html) or a [matplotlib.colors.LinearSegmentedColormap](https://matplotlib.org/stable/api/_as_gen/matplotlib.colors.LinearSegmentedColormap.html), depending on the value of the `type` argument (default is `"discrete"`, so it's `ListedColormap` in this case).
+
+Finally, you can create your chart as you normally would:
+
+```python
+# load libraries
+import cartopy.crs as ccrs
+import geopandas as gpd
+import matplotlib.pyplot as plt
+from matplotlib.font_manager import FontProperties
+from highlight_text import fig_text
+
+# load font
+personal_path = "/Users/josephbarbier/Library/Fonts/"  # change this to your own path
+font = FontProperties(fname=personal_path + "FiraSans-Light.ttf")
+bold_font = FontProperties(fname=personal_path + "FiraSans-Medium.ttf")
+
+# projection
+proj = ccrs.Mercator()
+
+# load the world dataset
+df = gpd.read_file(
+    "https://raw.githubusercontent.com/holtzy/The-Python-Graph-Gallery/master/static/data/all_world.geojson"
+)
+df = df[~df["name"].isin(["Antarctica"])]
+df = df.to_crs(proj.proj4_init)
+
+fig, ax = plt.subplots(figsize=(12, 8), dpi=300, subplot_kw={"projection": proj})
+ax.set_axis_off()
+df.plot(
+    column="name",
+    ax=ax,
+    cmap=cmap,  # here we pass the colormap loaded before
+    edgecolor="black",
+    linewidth=0.2,
+)
+fig_text(
+    x=0.5,
+    y=0.93,
+    s="World map with <PyPalettes> colors",
+    fontsize=25,
+    ha="center",
+    font=font,
+    highlight_textprops=[{"font": bold_font}],
+)
+fig_text(
+    x=0.85, y=0.14, s="Joseph Barbier & Yan Holtz", fontsize=8, ha="right", font=font
+)
+
+plt.show()
+```
+
+<center>
+
+![](map.png)
+
+</center>
+
+And once the code is working, you can change the color map name and see straight away what it would look like!
+
+<br>
+
+## Other usages
+
+PyPalettes is primarily designed for `matplotlib` due to its **high compatibility** with the `cmap` argument, but one can imagine **much more**.
+
+For example, it also provides the `get_hex()` and `get_rgb()` functions that return a list of hexadecimal colors or RGB values that can then be used in **any context**: other Python visualization libraries (plotly, plotnine, altair), colorimetry, image processing, or anything that requires color!
+
+<br>
+
+## Learn more
+
+The main links to find out more about this project are as follows:
+
+- the [web app](https://python-graph-gallery.com/color-palette-finder/) to browse the palettes
+- this [introduction to PyPalettes](https://python-graph-gallery.com/introduction-to-pypalettes/) for a more in-depth code explanation
+- the [Github repo](https://github.com/JosephBARBIERDARNAL/pypalettes) with source code and palettes (give us a star! ⭐)