为多个属性绘制图形+matplotlib

鉴于数据是时变的,线图最适合它。

老实说,如果我是您的话,我会对数据集做一些预处理,您需要做的事情非常简单;分别创建一个时间戳数组和每台机器的一些数组。不过,我不知道您在数据中保留的限制有多大。

import matplotlib.pylab as plt
import pandas as pd


efficiency = [{'weights': '21', 'sets': '5', 'time': '1', 'machine': 'a'}, 
{'weights': '93', 'sets': '25', 'time': '2', 'machine': 'a'},
{'weights': '53', 'sets': '5', 'time': '1', 'machine': 'b'},
{'weights': '61', 'sets': '25', 'time': '2', 'machine': 'b'},
{'weights': '66', 'sets': '5', 'time': '1', 'machine': 'c'},
{'weights': '90', 'sets': '25', 'time': '2', 'machine': 'c'},
{'weights': '79', 'sets': '5', 'time': '1', 'machine': 'd'},
{'weights': '100', 'sets': '25', 'time': '1', 'machine': 'd'}]



class Efficiency:
    plt.rcParams['figure.figsize'] = (16,6)
    def __init__(self, data):
        self.data = data
        self.machines = []
        self.Timestamp = []
        for i in data:
            setattr(self, 'machine_'+i['machine'], dict(efficiency=[]))
            if not i['machine'] in self.machines: self.machines.append(i['machine'])
            if not i['time'] in self.Timestamp: self.Timestamp.append(i['time'])

    def readData(self):
        for i in self.data:
            getattr(self, 'machine_' + i['machine'])['efficiency'].append(float(i['weights']))

    def plotData(self):
        eff_dict = {}
        for i in self.machines:
            eff_dict['machine ' + i] = getattr(self, 'machine_' + i)['efficiency']
        self.df = pd.DataFrame(eff_dict, index= self.Timestamp)

        self.df.plot()
        plt.grid()
        plt.xticks(fontsize=12, rotation=90)
        plt.tick_params(axis='both', which='major', labelsize=18)
        plt.legend(fontsize=12)
        plt.tight_layout()

        plt.show()
        print(self.df)

test = Efficiency(efficiency)
test.readData()
test.plotData()

这是你的密码;

如果数据定义如下:

import matplotlib.pylab as plt
import pandas as pd
import numpy as np
import datetime

efficiency2 = [{'weights': np.random.uniform(60,100, 10),'sets':np.random.randint(5,25, 10), 'time': np.arange(0,10,1), 'machine': 'a'},\
{'weights': np.random.uniform(60,100, 10), 'sets': np.random.randint(5,25, 10), 'time': np.arange(0,10,1), 'machine': 'b'}]



class Efficiency:
    plt.rcParams['figure.figsize'] = (16,6)
    def __init__(self, data):
        self.data = data
        self.machines = []
        self.Timestamp = []
        for i in data:
            setattr(self, 'machine_'+i['machine'], dict(weight=i['weights'], sets = i['sets']))
            if not i['machine'] in self.machines: self.machines.append(i['machine'])
        self.Timestamp = data[0]['time']


    def plotData(self):
        weight_dict = {}
        for i in self.machines:
            weight_dict['machine ' + i + ' weight'] = getattr(self, 'machine_' + i)['weight']
            weight_dict['machine ' + i + ' sets'] = getattr(self, 'machine_' + i)['sets']
        self.df = pd.DataFrame(weight_dict, index= self.Timestamp)

        self.df.plot()
        plt.grid()
        plt.xticks(fontsize=12, rotation=90)
        plt.tick_params(axis='both', which='major', labelsize=18)
        plt.legend(fontsize=20)
        plt.ylabel('(%)',fontsize=20)
        plt.xlabel('time',fontsize=20)

        plt.show()
        print(self.df)

test = Efficiency(efficiency2)
test.plotData()

你会得到这个:

您可以有两个Y标签,需要 x_axis 格式和各种属性,这取决于您的喜好。

数据看起来应该用条形图很好地表示,其中时间显示在y轴上。

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame(efficiency) # efficiency as defined in the question
df["time"] = df["time"].astype(float)
piv = df.pivot(columns="machine", index="weights", values="time")
piv.plot(kind="bar")

或者由机器订购,

piv = df.pivot(columns="weights", index="machine", values="time")
piv.plot(kind="bar")