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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 ])
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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