Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.
matplotlib.dates.epoch2num()
The matplotlib.dates.epoch2num()
function is used to convert an epoch or a sequence of epochs to a new date format from the day since 0001.
Syntax: matplotlib.dates.epoch2num(e)
Parameters:
- e: It can be an epoch or a sequence of epochs.
Returns: A new date format since day 0001.
Example 1:
import random import matplotlib.pyplot as plt import matplotlib.dates as mdates # generate some random data # for approx 5 yrs random_data = [ float (random.randint( 1487517521 , 14213254713 )) for _ in range ( 1000 )] # convert the epoch format to # matplotlib date format mpl_data = mdates.epoch2num(random_data) # plotting the graph fig, axes = plt.subplots( 1 , 1 ) axes.hist(mpl_data, bins = 51 , color = 'green' ) locator = mdates.AutoDateLocator() axes.xaxis.set_major_locator(locator) axes.xaxis.set_major_formatter(mdates.AutoDateFormatter(locator)) plt.show() |
Output:
Example 2:
from tkinter import * from tkinter import ttk import time import matplotlib import queue from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk from matplotlib.figure import Figure import matplotlib.animation as animation import matplotlib.dates as mdate root = Tk() graphXData = queue.Queue() graphYData = queue.Queue() def animate(objData): line.set_data( list (graphXData.queue), list (graphYData.queue)) axes.relim() axes.autoscale_view() figure = Figure(figsize = ( 5 , 5 ), dpi = 100 ) axes = figure.add_subplot( 111 ) axes.xaxis_date() line, = axes.plot([], []) axes.xaxis.set_major_formatter(mdate.DateFormatter( '%H:%M' )) canvas = FigureCanvasTkAgg(figure, root) canvas.get_tk_widget().pack(side = BOTTOM, fill = BOTH, expand = True ) for cnt in range ( 600 ): graphXData.put(matplotlib.dates.epoch2num(time.time() - ( 600 - cnt))) graphYData.put( 0 ) ani = animation.FuncAnimation(figure, animate, interval = 1000 ) root.mainloop() |
Output:
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.