使用matplotlib打印时基于dataframe列中的字符串创建colormap

Question

我有一个数据帧，看起来像：

            Value   Std         Reciever type
Station ID                                   
ABMF        3.588 0.492         TRIMBLE NETR9
AIRA        8.820 0.256         TRIMBLE NETR9
AREG        7.306 0.356         TRIMBLE NETR9
BRST        6.712 0.166         TRIMBLE NETR9
BRUX        3.151 0.151        SEPT POLARX4TR
          ...   ...                   ...
WTZR       12.374 0.158    LEICA GRX1200+GNSS
WTZZ        1.906 0.179  JAVAD TRE_G3TH DELTA
WUH2        4.422 0.534  JAVAD TRE_G3TH DELTA
ZIM2       11.244 0.171         TRIMBLE NETR5
ZIM3       11.971 0.185         TRIMBLE NETR9

[80 rows x 3 columns]

我正在尝试创建基于聚合的可视化，如下所示：

df = (df.groupby(by=['Station ID'])
              .agg({'Value': np.average, 'Std': np.average, 'Reciever type': 'first'})
              )
            dcb_plot = plt.figure(figsize=(16,9))
            plt.title('Receiver Code Biases for {} station(s) ({})'.format(station, year))
            plt.xlabel('Station(s)')
            plt.ylabel('DCB in ns')
            plt.errorbar(df.index, df['Value'], yerr=df['Std'], marker='o', fmt='o', ms=5, capsize=5, elinewidth=1)  
            ax = plt.gca()
            ax.axes.xaxis.set_ticklabels([])
            ax.yaxis.set_minor_locator(AutoMinorLocator())
            ax.tick_params(which='major', length=8)
            ax.tick_params(which='minor', length=4, color='r')

现在我已经取得了如下成就：

我想根据Reciever type列中的值创建colormap（彩色错误条也不错）。我该怎么做？ 为了更好地理解，这是我想要的输出：

Answer 1

关键是从颜色贴图生成颜色。我这里不使用df，但它应该很容易适应您的数据

from sklearn.datasets import make_blobs
import numpy as np
import matplotlib.pyplot as plt

n_samples = 100
random_state = 170
X, y = make_blobs(n_samples=n_samples, random_state=random_state, centers=3)
names = {0:'a', 1:'b', 2:'c'}
all_names = np.array([names[e] for e in y])
n = len(np.unique(all_names))
# this is how your map colors
colors = plt.cm.Spectral(np.arange(n)/np.arange(n).max())

fig, ax = plt.subplots(1, 1, figsize=(7.2, 7.2))
for i, e in enumerate(np.unique(all_names)):
    mask = all_names == e
    ax.errorbar(X[:, 0][mask], X[:, 1][mask], yerr=0.5, marker='o', fmt='o', ms=5, capsize=5, elinewidth=1, label=e, c=colors[i])
ax.legend()