解读matplotlib和seaborn颜色图(colormap)和调色板(color palette)

import seaborn as sns

sns.color_palette()

sns.color_palette("deep")

pallettes = ["deep", "muted", "pastel", "bright", "dark", "colorblind"]
data = np.array([sns.color_palette(pat) for pat in pallettes])
fig = plt.figure(figsize=(9,16))
ax = fig.add_subplot(111)
ax.imshow(data)
for i, pat in enumerate(pallettes):
    ax.text(-0.6, i, pat, ha="right")
plt.axis("off");

# 示例
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
col1 = ["A"]*5 + ["B"]*5
col2 = list("abcde")*2
val = np.random.rand(10)
df = pd.DataFrame({"col1":col1, "col2":col2, "val":val})
df
fig = plt.figure(figsize=(8,8))
fig.subplots_adjust(wspace=0.1, hspace=0.25)
for i, palette in enumerate(["deep", "muted", "bright", "dark"]):
    ax = fig.add_subplot(2, 2, i+1)
    sns.barplot(x="col2", y="val", hue="col1", data=df, ax=ax, palette=palette)
    ax.set_title(palette)

sns.color_palette("hls", 8)

sns.color_palette("hls", 16)

sns.color_palette("husl", 8) # husl相比hls，基于人的视觉特点对颜色进行了修正

sns.color_palette("Set2")

sns.color_palette("tab10")

fig = plt.figure(figsize=(24,8))
fig.subplots_adjust(wspace=0.1, hspace=0.25)
palettes = ["rocket", "mako", "flare", "crest", "magma", "viridis"]
palettes += [pat+"_r" for pat in palettes] 
data = np.random.rand(10,10)
for i, palette in enumerate(palettes):
    ax = fig.add_subplot(2, 6, i+1)
    sns.heatmap(data, cmap=palette)
    ax.set_title(palette)

fig = plt.figure(figsize=(16,8))
fig.subplots_adjust(wspace=0.2, hspace=0.25)
palettes = ["vlag", "icefire", "Spectral", "coolwarm"]
palettes += [pat+"_r" for pat in palettes] 
data = np.random.rand(10,10)*2-1
for i, palette in enumerate(palettes):
    ax = fig.add_subplot(2, 4, i+1)
    sns.heatmap(data, cmap=palette)
    ax.set_title(palette)