廢話不多說，直接上代碼，執行時有問題可留言。

依賴包

- python == 3.7.5 - numpy == 1.17.3 - pandas == 0.24.2 - matplotlib == 3.3.2 - pymysql == 0.9.2

draw_table.py

from matplotlib import pyplot as plt import pymysql import pandas as pd from pandas import * from pylab import mpl mpl.rcParams['font.sans-serif'] = ['Microsoft YaHei'] # 指定默認字體：解決plot不能顯示中文問題 mpl.rcParams['axes.unicode_minus'] = False # 解決保存圖像是負號'-'顯示為方塊的問題def pd_data():mysql_cn = pymysql.connect(host='mysqlHost', port=3306, user='mysqlUser',passwd='mysqlPassword', db='mysqlDb')sql ='sql語句'stu = pd.read_sql(sql, con=mysql_cn)mysql_cn.close()num = stu.shape[0] # 獲取行號return stu, numdef plot_table(row, col, vals):"""函數功能: 繪制二維表格，草圖如下:-----------------|col1 |col2 |-----------------row1|value|value|-----------------row2|value|value|-----------------輸入：row:string,(N) #['row1', 'row2']col:string,(M) #['col1', 'col2']vals:np, (N,M)"""R, C = len(row), len(col)idx = Index(row)df = DataFrame(np.random.randn(R, C), index=idx, columns=col)# 根據行數列數設置表格大小figC, figR = 2.25 * C, Rfig = plt.figure(figsize=(figC, figR))# 設置fig并去掉邊框ax = fig.add_subplot(111, frameon=True, xticks=[], yticks=[])ax.spines['top'].set_visible(False)ax.spines['right'].set_visible(False)ax.spines['bottom'].set_visible(False)ax.spines['left'].set_visible(False)the_table = plt.table(cellText=vals, rowLabels=df.index, colLabels=df.columns, colWidths=[0.1] * vals.shape[1],rowLoc='center', loc='center', cellLoc='center')the_table.set_fontsize(30)# 伸縮表格大小常數,可自行調節表格的寬高the_table.scale(figR / R * 1.2, figC / C * 2.0)# 設置每行隨機顏色for ro in row:from DingMessage.colorDict import cnamesimport randomcolor = cnames.get(random.sample(cnames.keys(), 1)[0])for co in range(len(col)):the_table._cells[(int(ro), co)].set_facecolor(color)plt.savefig("test.jpg")# plt.show()if __name__ == '__main__':# 讀庫獲取pd數據及總行數S,num = pd_data()# 設置表格titlecol = ["服務號","關注","分量","openid數","openID獲取準確率","匹配廣告來源openID數","微信廣告銷售線索","回傳準確率","全流程數據準確性","廣告來源占比"]# 自動匹配總行數，行數不統一會報錯：ValueError: 'rowLabels' must be of length XXX（正確的行數）row = [str(i) for i in range(1,int(num+1))]# 轉numpy數組vals = np.array(S)# 制表plot_table(row, col, vals)

顏色對照表：colorDict.py

cnames = { 'aliceblue': '#DDDDDD', 'antiquewhite': '#AAAAAA', 'aqua': '#888888', 'aquamarine': '#FFB7DD', 'azure': '#FF88C2', 'beige': '#FF44AA', 'bisque': '#FFCCCC', 'black': '#FF8888', 'blanchedalmond': '#FF3333', 'blue': '#FFC8B4', 'blueviolet': '#FFA488', 'brown': '#FF7744', 'burlywood': '#FFDDAA', 'cadetblue': '#FFBB66', 'chartreuse': '#FFAA33', 'chocolate': '#FFEE99', 'coral': '#FFDD55', 'cornflowerblue': '#FFFFBB', 'cornsilk': '#FFFF77', 'crimson': '#EEFFBB', 'cyan': '#DDFF77', 'darkblue': '#CCFF33', 'darkcyan': '#CCFF99', 'darkgoldenrod': '#BBFF66', 'darkgray': '#99FF33', 'darkgreen': '#99FF99', 'darkkhaki': '#66FF66', 'darkmagenta': '#33FF33', 'darkolivegreen': '#BBFFEE', 'darkorange': '#77FFCC', 'darkorchid': '#33FFAA', 'darkred': '#AAFFEE', 'darksalmon': '#77FFEE', 'darkseagreen': '#33FFDD', 'darkslateblue': '#99FFFF', 'darkslategray': '#66FFFF', 'darkturquoise': '#33FFFF', 'darkviolet': '#CCEEFF', 'deeppink': '#77DDFF', 'deepskyblue': '#33CCFF', 'dimgray': '#5599FF', 'dodgerblue': '#99BBFF', 'firebrick': '#CCDDFF', 'floralwhite': '#CCCCFF', 'forestgreen': '#9999FF', 'fuchsia': '#CCBBFF', 'gainsboro': '#9F88FF', 'ghostwhite': '#D1BBFF', 'gold': '#B088FF', 'goldenrod': '#9955FF', 'gray': '#E8CCFF', 'green': '#D28EFF', 'greenyellow': '#B94FFF', 'honeydew': '#F0BBFF', 'hotpink': '#E38EFF', 'indianred': '#E93EFF', 'indigo': '#FFB3FF', 'ivory': '#FF77FF', 'khaki': '#FF3EFF'}

當前路徑下的test.jpg即為生成的圖片，如有問題歡迎留言。

結果：

總結

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