如何使用matplotlib绘制具有不同颜色和形状的多个组？

Question

Given the following DataFrame (in pandas):

        X    Y    Type   Region
 index
 1      100  50   A      US
 2      50   25   A      UK
 3      70   35   B      US
 4      60   40   B      UK
 5      80   120  C      US
 6      120  35   C      UK

In order to generate the DataFrame:

import pandas as pd

data = pd.DataFrame({'X': [100, 50, 70, 60, 80, 120],
                     'Y': [50, 25, 35, 40, 120, 35],
                     'Type': ['A', 'A', 'B', 'B', 'C', 'C'],
                     'Region': ['US', 'UK'] * 3
                    },
                    columns=['X', 'Y', 'Type', 'Region']
       )

I tried to make a scatter plot of X and Y , colored by Type and shaped by Region . How could I achieve it in matplotlib?

Answer 1

With more Pandas:

from pandas import DataFrame
from matplotlib.pyplot import show, subplots 
from itertools import cycle # Useful when you might have lots of Regions

data = DataFrame({'X': [100, 50, 70, 60, 80, 120],
                     'Y': [50, 25, 35, 40, 120, 35],
                     'Type': ['A', 'A', 'B', 'B', 'C', 'C'],
                     'Region': ['US', 'UK'] * 3
                    },
                    columns=['X', 'Y', 'Type', 'Region']
       )

cs = {'A':'red',
      'B':'blue',
      'C':'green'}

markers = ('+','o','>') 
fig, ax = subplots()

for region, marker in zip(set(data.Region),cycle(markers)):
    reg_data = data[data.Region==region]
    reg_data.plot(x='X', y='Y',
          kind='scatter',
          ax=ax,
          c=[cs[x] for x in reg_data.Type],
          marker=marker,
          label=region)
ax.legend()
show()

For this kind of multi-dimensional plot, though, check out seaborn (works well with pandas).

Answer 2

An approach would be to do the following. It is not elegant, but works import matplotlib.pyplot as plt import matplotlib as mpl import numpy as np plt.ion()

colors  = ['g', 'r', 'c', 'm', 'y', 'k', 'b'] 
markers = ['*','+','D','H']
for iType in range(len(data.Type.unique())):
    for iRegion in range(len(data.Region.unique())):
        plt.plot(data.X.values[np.bitwise_and(data.Type.values   == data.Type.unique()[iType],
                                              data.Region.values == data.Region.unique()[iRegion])],
                 data.Y.values[np.bitwise_and(data.Type.values   == data.Type.unique()[iType],
                                              data.Region.values == data.Region.unique()[iRegion])],
                 color=colors[iType],marker=markers[iRegion],ms=10)

I am not familiar with Panda, but there must some more elegant way to do the filtering. A marker list can be obtained using markers.MarkerStyle.markers.keys() from matplotlib and the conventional color cycle can be obtained using gca()._get_lines.color_cycle.next()