双y轴坐标轴图
今天利用matplotlib
绘图,想要完成一个双坐标格式的图。
12345 | fig=plt.figure(figsize=(20,15))ax1=fig.add_subplot(111)ax1.plot(demo0719[\’TPS\’],\’b-\’,label=\’TPS\’,linewidth=2)ax2=ax1.twinx()#这是双坐标关键一步ax2.plot(demo0719[\’successRate\’]*100,\’r-\’,label=\’successRate\’,linewidth=2) |
123 | import matplotlib.dates as mdateax1.xaxis.set_major_formatter(mdate.DateFormatter(\’%Y-%m-%d %H:%M:%S\’))#设置时间标签显示格式plt.xticks(pd.date_range(demo0719.index[0],demo0719.index[–1],freq=\’1min\’)) |
1234 | import matplotlib.ticker as mtickfmt=\’%.2f%%\’yticks = mtick.FormatStrFormatter(fmt)ax2.yaxis.set_major_formatter(yticks) |
在matplotlib中,整个图像为一个Figure对象。在Figure对象中可以包含一个,或者多个Axes对象。每个Axes对象都是一个拥有自己坐标系统的绘图区域。其逻辑关系如下:
一个Figure
对应一张图片。
Title为标题。Axis为坐标轴,Label为坐标轴标注。Tick为刻度线,Tick Label为刻度注释。1
Title为标题。Axis为坐标轴,Label为坐标轴标注。Tick为刻度线,Tick Label为刻度注释。
pyplot.figure()
是返回一个Figure
对象的,也就是一张图片。The Axes instance will be returned.
1 | ax = twinx() |
create a twin of Axes for generating a plot with a sharex x-axis but independent y axis. The y-axis of self will have ticks on left and the returned axes will have ticks on the right.
意思就是,创建了一个独立的Y轴,共享了X轴。双坐标轴!
类似的还有twiny()
Set the formatter of the major ticker
ACCEPTS: A Formatter instance
strftime方法(传入格式化字符串)。
123 | strftime(dt, fmt=None)Refer to documentation for datetime.strftime.fmt is a strftime() format string. |
Use a new-style format string (as used by str.format()) to format the tick. The field formatting must be labeled x
定义字符串格式。
123456789 | # return locs, labels where locs is an array of tick locations and# labels is an array of tick labels.locs, labels = xticks() # set the locations of the xticksxticks( arange(6) ) # set the locations and labels of the xticksxticks( arange(5), (\’Tom\’, \’Dick\’, \’Harry\’, \’Sally\’, \’Sue\’) ) |
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475 | #coding:utf-8import matplotlib.pyplot as plt import matplotlib as mplimport matplotlib.dates as mdateimport matplotlib.ticker as mtickimport numpy as npimport pandas as pdimport os mpl.rcParams[\’font.sans-serif\’]=[\’SimHei\’] #用来正常显示中文标签mpl.rcParams[\’axes.unicode_minus\’]=False #用来正常显示负号mpl.rc(\’xtick\’, labelsize=20) #设置坐标轴刻度显示大小mpl.rc(\’ytick\’, labelsize=20) font_size=30#matplotlib.rcParams.update({\’font.size\’: 60}) %matplotlib inline plt.style.use(\’ggplot\’) data=pd.read_csv(\’simsendLogConvert_20160803094801.csv\’,index_col=0,encoding=\’gb2312\’,parse_dates=True) columns_len=len(data.columns)data_columns=data.columns for x in range(0,columns_len,2): print(\’第{}列\’.format(x)) total=data.ix[:,x] print(\’第{}列\’.format(x+1)) successRate=(data.ix[:,x+1]/data.ix[:,x]).fillna(0) yLeftLabel=data_columns[x] yRightLable=data_columns[x+1] print(\’——————开始绘制类型{}曲线图——————\’.format(data_columns[x])) fig=plt.figure(figsize=(25,20)) ax1=fig.add_subplot(111) #绘制Total曲线图 ax1.plot(total,color=\’#4A7EBB\’,label=yLeftLabel,linewidth=4) # 设置X轴的坐标刻度线显示间隔 ax1.xaxis.set_major_formatter(mdate.DateFormatter(\’%Y-%m-%d %H:%M:%S\’))#设置时间标签显示格式 plt.xticks(pd.date_range(data.index[0],data.index[–1],freq=\’1min\’))#时间间隔 plt.xticks(rotation=90) #设置双坐标轴,右侧Y轴 ax2=ax1.twinx() #设置右侧Y轴显示百分数 fmt=\’%.2f%%\’ yticks = mtick.FormatStrFormatter(fmt) # 绘制成功率图像 ax2.set_ylim(0,110) ax2.plot(successRate*100,color=\’#BE4B48\’,label=yRightLable,linewidth=4) ax2.yaxis.set_major_formatter(yticks) ax1.set_xlabel(\’Time\’,fontsize=font_size) ax1.set_ylabel(yLeftLabel,fontsize=font_size) ax2.set_ylabel(yRightLable,fontsize=font_size) legend1=ax1.legend(loc=(.02,.94),fontsize=16,shadow=True) legend2=ax2.legend(loc=(.02,.9),fontsize=16,shadow=True) legend1.get_frame().set_facecolor(\’#FFFFFF\’) legend2.get_frame().set_facecolor(\’#FFFFFF\’) plt.title(yLeftLabel+\’&\’+yRightLable,fontsize=font_size) plt.savefig(\’D:\\\\JGT\\Work-YL\\\\01布置的任务\\\\04绘制曲线图和报告文件\\\\0803\\出图\\\\{}-{}\’.format(yLeftLabel.replace(r\’/\’,\’ \’),yRightLable.replace(r\’/\’,\’ \’)), |