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plt.py
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import sys
from PyQt5.QtCore import Qt
import pandas as pd
import numpy as np
from PyQt5.QtWidgets import *
from matplotlib.figure import Figure
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from PyQt5.QtWidgets import QMainWindow, QApplication, QWidget, QGridLayout
import matplotlib.pyplot as plt
from scipy.stats import gaussian_kde
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] =False
class MyFigureCanvas(FigureCanvas):
"""
画布
"""
def __init__(self):
# 画布上初始化一个图像
self.figure = Figure()
super().__init__(self.figure)
class Demo(QWidget):
def __init__(self,h):
super(Demo, self).__init__()
self.resize(1200, 900)
#self.h=h
self.h=pd.DataFrame(h)
self.label1 = QLabel(self.h.iloc[0,5]+'学院\n\n专业数：4')
self.label1.setStyleSheet("color:rgb(20,20,20,255);font-size:20px")
self.label2 = QLabel('总人数：'+str(len(self.h))+'\n\n学院平均成绩：'+str(np.mean([float(i) for i in self.h.iloc[:,9]]))[0:4])
self.label2.setStyleSheet("color:rgb(20,20,20,255);font-size:20px")
self.figureCanvas = MyFigureCanvas()
self.__draw_figure__()
self.plot_btn = QPushButton('返回', self)
self.plot_btn.clicked.connect(self.plot_slot)
self.v_layout = QGridLayout()
self.v_layout.addWidget(self.label1, 0, 0)
self.v_layout.addWidget(self.label2, 0, 1)
self.v_layout.addWidget(self.figureCanvas,1,0,4,2)
self.v_layout.addWidget(self.plot_btn,5,1)
self.setLayout(self.v_layout)
def plot_slot(self):
self.close()
def __draw_figure__(self):
# 下面的步骤和调用的方法和plot大致相同，这里我写一个简单的折线图
self.axes = self.figureCanvas.figure.add_subplot(221)
self.axes.set_title("专业设置")
self.axes.set_xlabel("")
self.axes.set_ylabel("人数")
result = pd.value_counts(self.h.iloc[:,6])
x = result.index.to_list()
y = result.values.tolist()
self.axes.bar(x, y, color = "m",width = 0.6 )
self.axes2 = self.figureCanvas.figure.add_subplot(222)
self.axes2.set_title("年级")
result2 = pd.value_counts(self.h.iloc[:,3])
lab = result2.index.to_list()
num = result2.values.tolist()
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
self.axes2.pie(x = num, labels =lab ,autopct='%1.1f%%',colors=colors, shadow=True, startangle=90,pctdistance = 0.6)
self.axes2.axis('equal')
self.axes3 = self.figureCanvas.figure.add_subplot(223)
self.axes3.set_title("")
jidian = self.h.iloc[:,9]
density = gaussian_kde(jidian)
density.covariance_factor = lambda: .25
density._compute_covariance()
xs = np.linspace(1, 4.5, 100)
self.axes3.set_ylabel("绩点分布")
self.axes3.plot(xs,density(xs))
self.axes4 = self.figureCanvas.figure.add_subplot(224)
self.axes4.set_title("就业去向")
self.axes4.set_xlabel("")
self.axes4.set_ylabel("")
result2 = pd.value_counts(self.h.iloc[:, 18])
x2 = result2.index.to_list()
y2 = result2.values.tolist()
self.axes4.bar(x2, y2, color="m", width=0.6)
if __name__ == '__main__':
app = QApplication(sys.argv)
t=pd.read_csv('data/data.csv')
demo = Demo(h=t)
demo.show()
sys.exit(app.exec_())
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