如何使用matplotlibpython添加顏色圖和矩形框？

我正在嘗試從python 中的

到目前為止，我能夠添加文本并用計數繪制分類變數。

def plot_precedence_matrix(data,colx,coly,cols,color=['grey','black'],ratio=10,font='Helvetica',save=False,save_name='Default'):
    

    df = data.copy()
    # Create a dict to encode the categeories into numbers (sorted)
    colx_codes=dict(zip(df[colx].sort_values().unique(),range(len(df[colx].unique()))))
    coly_codes=dict(zip(df[coly].sort_values(ascending=False).unique(),range(len(df[coly].unique()))))
    
    # Apply the encoding
    df[colx]=df[colx].apply(lambda x: colx_codes[x])
    df[coly]=df[coly].apply(lambda x: coly_codes[x])
    
    
    ax=plt.gca()
    ax.xaxis.set_label_position('top')
    ax.xaxis.set_ticks_position('top')

    # Prepare the aspect of the plot
    # plt.rcParams['xtick.bottom'] = plt.rcParams['xtick.labelbottom'] = False
    # plt.rcParams['xtick.top'] = plt.rcParams['xtick.labeltop'] = True
    plt.rcParams['font.sans-serif']=font
    
    plt.rcParams['xtick.color']=color[-1]
    plt.rcParams['ytick.color']=color[-1]
    # plt.box(False)

    
    # Plot all the lines for the background
    for num in range(len(coly_codes)):
        plt.hlines(num,-1,len(colx_codes),linestyle='dashed',linewidth=2,color=color[num%2],alpha=0.1)
    for num in range(len(colx_codes)):
        plt.vlines(num,-1,len(coly_codes),linestyle='dashed',linewidth=2,color=color[num%2],alpha=0.1)
        
    
    for x, y, tex in zip(df[colx], df[coly], df[colx]):
        t = plt.text(x, y, round(tex, 1), horizontalalignment='center', 
                     verticalalignment='center', fontdict={'color':'black',
                                                           'size':30})
    
    # Change the ticks numbers to categories and limit them
    plt.xticks(ticks=list(colx_codes.values()),labels=colx_codes.keys(),rotation=90)
    plt.yticks(ticks=list(coly_codes.values()),labels=coly_codes.keys())

    # Lighten borders
    plt.gca().spines["top"].set_alpha(0.1)
    plt.gca().spines["bottom"].set_alpha(0.1)
    plt.gca().spines["right"].set_alpha(0.1)
    plt.gca().spines["left"].set_alpha(0.1)


    # Save if wanted
    if save:
        plt.savefig(save_name '.png')

樣本資料集

|         Antecedent |         Consequent | Count |
|-------------------:|-------------------:|-------|
|   register request | examine thoroughly |     1 |
| examine thoroughly |       check ticket |     2 |
|       check ticket |             decide |     6 |
|             decide |     reject request |     3 |
|   register request |       check ticket |     2 |
|       check ticket |   examine casually |     2 |
|   examine casually |             decide |     2 |
|             decide |   pay compensation |     3 |
|   register request |   examine casually |     3 |
|   examine casually |       check ticket |     4 |
|             decide | reinitiate request |     3 |
| reinitiate request | examine thoroughly |     1 |
|       check ticket | examine thoroughly |     1 |
| examine thoroughly |             decide |     1 |
| reinitiate request |       check ticket |     1 |
| reinitiate request |   examine casually |     1 |

colors=['darkorange','grey','darkblue']

#create the plot
fig = plt.figure(figsize=(12,8))
plot_precedence_matrix(df, 'Antecedent', 'Consequent', 'Count',color=colors,ratio=100, font='cursive')
plt.xticks(fontsize=14)
plt.yticks(fontsize=14)
plt.show()

如何使用matplotlib添加帶有色標的矩形框？有人能解釋一下用 Python 繪制上面的圖嗎？我很高興收到您的任何線索。

uj5u.com熱心網友回復：

您可以在每個位置繪制彩色矩形。顏色圖與規范一起可以定義顏色。

下面是一個例子：

from matplotlib import pyplot as plt
from matplotlib.cm import ScalarMappable
from matplotlib.colors import ListedColormap
import pandas as pd
import numpy as np
from io import StringIO

def plot_precedence_matrix(data, colx, coly, cols, color=['grey', 'black'], ratio=10, font='Helvetica',
                           save=False, save_name='Default'):
    df = data.copy()
    # Create a dict to encode the categeories into numbers (sorted)
    colx_codes = dict(zip(df[colx].sort_values().unique(), range(len(df[colx].unique()))))
    coly_codes = dict(zip(df[coly].sort_values(ascending=False).unique(), range(len(df[coly].unique()))))

    # Apply the encoding
    df[colx] = df[colx].apply(lambda x: colx_codes[x])
    df[coly] = df[coly].apply(lambda x: coly_codes[x])

    ax = plt.gca()
    ax.xaxis.set_label_position('top')
    ax.xaxis.set_ticks_position('top')

    # Prepare the aspect of the plot
    plt.rcParams['font.sans-serif'] = font
    plt.rcParams['xtick.color'] = color[-1]
    plt.rcParams['ytick.color'] = color[-1]

    # Plot the lines for the background
    for num in range(len(coly_codes)):
        ax.hlines(num, -1, len(colx_codes), linestyle='dashed', linewidth=2, color=color[num % 2], alpha=0.1)
    for num in range(len(colx_codes)):
        ax.vlines(num, -1, len(coly_codes), linestyle='dashed', linewidth=2, color=color[num % 2], alpha=0.1)

    cmap = ListedColormap(plt.get_cmap('Blues')(np.linspace(0.1, 1, 256)))  # skip too light colors
    norm = plt.Normalize(df[colx].min(), df[colx].max())
    for x, y, tex in zip(df[colx], df[coly], df[colx]):
        t = ax.text(x, y, round(tex, 1), horizontalalignment='center', verticalalignment='center',
                    fontdict={'color': 'black' if norm(tex) < 0.6 else 'white', 'size': 30})
        ax.add_patch(plt.Rectangle((x - .5, y - .5), 1, 1, color=cmap(norm(tex)), ec='white'))

    plt.colorbar(ScalarMappable(cmap=cmap, norm=norm), ax=ax)
    # Change the ticks numbers to categories and limit them
    ax.set_xticks(list(colx_codes.values()))
    ax.set_xticklabels(colx_codes.keys(), rotation=90, fontsize=14)
    ax.set_yticks(list(coly_codes.values()))
    ax.set_yticklabels(coly_codes.keys(), fontsize=14)

    # Lighten borders
    for spine in ax.spines:
        ax.spines[spine].set_alpha(0.1)

    plt.tight_layout()  # fit the labels into the figure
    if save:
        plt.savefig(save_name   '.png')

df_str = """
      register request | examine thoroughly |     1 
    examine thoroughly |       check ticket |     2 
          check ticket |             decide |     6 
                decide |     reject request |     3 
      register request |       check ticket |     2 
          check ticket |   examine casually |     2 
      examine casually |             decide |     2 
                decide |   pay compensation |     3 
      register request |   examine casually |     3 
      examine casually |       check ticket |     4 
                decide | reinitiate request |     3 
    reinitiate request | examine thoroughly |     1 
          check ticket | examine thoroughly |     1 
    examine thoroughly |             decide |     1 
    reinitiate request |       check ticket |     1 
    reinitiate request |   examine casually |     1 """

df = pd.read_csv(StringIO(df_str), delimiter="\s*\|\s*", engine='python', names=['Antecedent', 'Consequent', 'Count'])
colors = ['darkorange', 'grey', 'darkblue']

fig = plt.figure(figsize=(12, 8))
plot_precedence_matrix(df, 'Antecedent', 'Consequent', 'Count', color=colors, ratio=100, font='cursive')
plt.show()

標籤：Python matplotlib 数据可视化 颜色图

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