我在刷新图表方面有点困难,所以我能够运行直方图,然后运行箱线图。我想需要的是一个带有“.design”和“初始化窗口”的按钮,或者在每个绘图开始时都有一个刷新功能,这样就可以为新的绘图做好准备。
我尝试了很多与stackoverflow不同的方法,但似乎都不起作用。我主要尝试了canvas.delete('all'),但它并没有真正起作用。所以我希望stackoverflow上的人知道如何在这种结构中正确工作。
此外,我必须高度赞扬用户“j_4321”。j_4321真的帮助我弄清楚了如何在Tkinter中正确绘图以及如何初始化这个框架!
import tkinter as tk
from tkinter import ttk
from tkinter import filedialog
from tkinter import Toplevel
from tkinter.filedialog import askopenfilename
from tkinter.messagebox import showinfo, showwarning, askquestion
from tkinter import OptionMenu
from tkinter import StringVar
import seaborn as sns
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk
from matplotlib.figure import Figure
from matplotlib import style
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import matplotlib.dates as mdates
from psutil import cpu_percent
from psutil import virtual_memory
from datetime import datetime, timedelta
from sklearn.metrics import silhouette_score
from sklearn.cluster import KMeans
import sklearn.cluster as cluster
import scipy.spatial.distance as sdist
from sklearn.ensemble import IsolationForest
from sklearn.model_selection import train_test_split
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.metrics import accuracy_score
import pandas as pd
import numpy as np
import seaborn as sn
from sklearn.preprocessing import MinMaxScaler
from sklearn.preprocessing import StandardScaler
RANDOM_STATE = 42 #used to help randomly select the data points
low_memory=False
LARGE_FONT= ("Verdana", 12)
style.use("ggplot")
f = Figure(figsize=(5,5), dpi=100)
a = f.add_subplot(111)
df = None
df_nan = None
df_r = None
check_transformer = None
df_output = None
ContNum = None
GB_Classifier_score = None
df = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
columns=['age', 'collection_agency', 'number'])
class Analyticsapp(tk.Tk):
def __init__(self, *args, **kwargs):
tk.Tk.__init__(self, *args, **kwargs)
#tk.Tk.iconbitmap(self, default="iconimage_kmeans.ico") #Icon for program
tk.Tk.wm_title(self, "Advanched analytics")
container = tk.Frame(self)
container.pack(side="top", fill="both", expand=True)
container.grid_rowconfigure(0, weight=1)
container.grid_columnconfigure(0, weight=1)
self.frames = {}
for F in (StartPage, PlottingDFPage):
frame = F(container, self)
self.frames[F] = frame
frame.grid(row=0, column=0, sticky="nsew")
self.show_frame(StartPage)
def show_frame(self, cont):
frame = self.frames[cont]
frame.tkraise()
class StartPage(tk.Frame):
def __init__(self, parent, controller):
tk.Frame.__init__(self, parent)
label = tk.Label(self, text="Advanched analytics", font=LARGE_FONT)
label.pack(pady=10, padx=10)
button4 = ttk.Button(self, text="Plot Example",
command=lambda: controller.show_frame(PlottingDFPage))
button4.pack(fill='x')
class PlottingDFPage(tk.Frame):
def __init__(self, parent, controller):
tk.Frame.__init__(self, parent)
label = tk.Label(self, text="Plotting Dataframe", font=LARGE_FONT)
label.pack(pady=10, padx=10)
global df, Plot_type, Plot_define
def PlotMaster():
Plot_define = Plot_type.get()
if df is None:
showwarning("Warning", "Read file first")
elif Plot_define == '-Choose an option-':
showwarning("Warning", "Choose a plot type")
elif Plot_define == 'Histogram':
Plot_text = "Plot set to: "+Plot_define
showinfo(title="Results", message=Plot_text)
HistogramDF()
elif Plot_define == 'Scatterplot':
Plot_text = "Plot set to: "+Plot_define
showinfo(title="Results", message=Plot_text)
ScatterplotDF()
elif Plot_define == 'Boxplot':
Plot_text = "Plot set to: "+Plot_define
showinfo(title="Results", message=Plot_text)
BoxplotDF()
else: None
def HistogramDF():
f = None
f = plt.figure(figsize=(10, 8))
# REMOVE AFTER DF X, y generation!!!
ax = sns.distplot(df['age'])
canvas = FigureCanvasTkAgg(f, self)
canvas.draw()
canvas.get_tk_widget().pack(side=tk.BOTTOM, fill=tk.BOTH, expand=True)
toolbar = NavigationToolbar2Tk(canvas, self)
toolbar.update()
canvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
def ScatterplotDF():
f = None
f = plt.figure(figsize=(10, 8))
x = df['age']
y = df['collection_agency']
plt.scatter(x, y)
plt.draw()
canvas = FigureCanvasTkAgg(f, self)
canvas.draw()
canvas.get_tk_widget().pack(side=tk.BOTTOM, fill=tk.BOTH, expand=True)
toolbar = NavigationToolbar2Tk(canvas, self)
toolbar.update()
canvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
def BoxplotDF():
f = None
f = plt.figure(figsize=(10, 8))
# REMOVE AFTER DF X, y generation!!!
boxplot_df = df.filter(['age', 'collection_agency'])
boxplot_columns = list(boxplot_df.columns)
sns.set_style('whitegrid')
ax = sns.boxplot(x='collection_agency',y='age',data=boxplot_df)
ax = sns.stripplot(x='collection_agency', y='age',data=boxplot_df)
canvas = FigureCanvasTkAgg(f, self)
canvas.draw()
canvas.get_tk_widget().pack(side=tk.BOTTOM, fill=tk.BOTH, expand=True)
toolbar = NavigationToolbar2Tk(canvas, self)
toolbar.update()
canvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
Options_plot = ['-Choose an option-', 'Histogram', 'Scatterplot', 'Boxplot']
Plot_type = StringVar(self)
Plot_type.set(Options_plot[0]) # default value
label1 = tk.Label(self, text='Plot type:')
label1.pack()
dropdown1 = tk.OptionMenu(self, Plot_type, *Options_plot)
dropdown1.pack()
button1 = ttk.Button(self, text="Run plot", command=PlotMaster)
button1.pack(fill='x')
button2 = ttk.Button(self, text="Back",
command=lambda: controller.show_frame(StartPage))
app = Analyticsapp()
app.geometry('500x400')
app.mainloop()
