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import matplotlib.image as mping #mping用于读取图片 import datetime as dt import matplotlib.dates as mdates from pylab import * def draw_trend_chart(dates,y): mpl.rcParams[ 'font.sans-serif' ] = [ 'SimHei' ] #指定默认字体 mpl.rcParams[ 'axes.unicode_minus' ] = False #解决保存图像是负号'-'显示为方块的问题 x = [dt.datetime.strptime(d, '%Y/%m/%d' ).date() for d in dates] #plt.figure(figsize=(8,8)) plt.figure() #plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%m/%d/%Y')) #plt.gca().xaxis.set_major_locator(mdates.DayLocator()) #plt.plot(x,y,"r--",linewidth=2) plt.plot(x,y, "r" ,linewidth = 1 ) #plt.gcf().autofmt_xdate() #plt.xlabel("DATE") #x轴标签 plt.ylabel( "WEIGHT" ) #y轴标签 plt.title( "MY HEALTH TRACKING" ) #标题 plt.savefig( "liuyang.png" ) #保存图片名称 lena = mping.imread( 'liuyang.png' ) #读取图片文件信息 lena.shape #(512,512,3) plt.imshow(lena) #显示图片 plt.axis( 'off' ) #不显示坐标轴 plt.title("") plt.show() #显示 def get_weight_data(filename): time = [] weight = [] fileContent = open (filename, "r" ) for eachline in fileContent: eachData = eachline.strip( '\n' ).split( "," ) if eachData[ - 1 ].strip() = = '': continue else : time.append(eachData[ 0 ]) weight.append(eachData[ 1 ]) return [time, weight] data = get_weight_data( "data.csv" ) draw_trend_chart(data[ 0 ],data[ 1 ]) |
以上就是python绘制趋势图的示例的详细内容,更多关于python绘制趋势图的资料请关注服务器之家其它相关文章!
原文链接:https://www.cnblogs.com/liuyang92/p/7466600.html