improve post about pypalettes

content/posts/matplotlib/pypalettes/index.md

@@ -12,10 +12,6 @@ resources:
     params:
       description: "pypalettes library"
       showOnTop: false
-_build:
-  render: true
-  list: true
-  publishResources: false
 ---
 
 ## Finding the right color has never been easier
@@ -26,3 +22,94 @@ Recently (June 2024), the [pypalettes library](https://github.com/JosephBARBIERD
 - a [web app](https://python-graph-gallery.com/color-palette-finder/) to browse, filter, search and preview all the available palettes (and **bonus**: copy-pastable code to reproduce the charts)
 
 _A small sample of the available palettes_[![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/)
+
+<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 2 websites:
+
+- the [Paletteer gallery](https://pmassicotte.github.io/paletteer_gallery/), which contains all palettes from Paletteer with hexadecimal colors, palette names, and package sources.
+- [coolors.co](https://coolors.co/), another website with cool palettes.
+
+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.
+
+<br>
+
+## How to use it
+
+The goal was to make the simplest API possible, and I'm quite satisfied with the result. For example, I really like the [Ingres palette](https://python-graph-gallery.com/color-palette-finder/?palette=ingres), and I 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="Ingres"`
+
+```python
+cmap = load_cmap("Ingres")
+```
+
+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 geopandas as gpd
+import matplotlib.pyplot as plt
+from pypalettes import load_cmap
+
+# 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"])]
+
+fig, ax = plt.subplots(figsize=(10, 10), dpi=300)
+ax.set_axis_off()
+df.plot(
+    ax=ax,
+    cmap=cmap,  # here we pass the colormap loaded before
+    edgecolor="white",
+    linewidth=0.3,
+)
+
+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
+- the [Github repo](https://github.com/JosephBARBIERDARNAL/pypalettes) with source code and palettes (give us a star! ⭐)
+- this [introduction to PyPalettes](https://python-graph-gallery.com/introduction-to-pypalettes/) for a more in-depth code explanation