Creating colormap based on strings in dataframe column while plotting using matplotlib

Question

I hava a dataframe which looks like that:

            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]

and I'm trying to create visualization based on aggregation like that:

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')

right now I've achieved someting like this:

and i want to create colormap based on values inside Reciever type column (colored errorbars would be nice too). How can I do that? For better understanding, this is my desired output:

user_5855131 · Answer

The key is to generate colors form colormaps. I dont use df here, but it should be very easy to adapt to you data.

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()

Creating colormap based on strings in dataframe column while plotting using matplotlib

1 Answers