Matplotlib.dates.DateFormatter class in Python

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.DateFormatter

The matplotlib.dates.DateFormatter class is used to format a tick (in seconds since the epoch) with a string of strftime format. Its base class is matplotlib.ticker.Formatter.

Syntax: class matplotlib.dates.DateFormatter(fmt, tz=None)

Parameters:

fmt: It accepts a strftime format string for formatting and is a required argument.
tz: It holds information regarding the timezone. If set to none it ignores the timezone information while formatting of the date string.

Example 1:

import numpy 
import matplotlib.pyplot as plt 
import matplotlib.dates as mdates 
import pandas 
  
   
total_bars = 25
numpy.random.seed(total_bars) 
   
dates = pandas.date_range('3/4/2020',  
                          periods=total_bars, 
                          freq='m') 
  
diff = pandas.DataFrame( 
    data=numpy.random.randn(total_bars),  
    index=dates, 
    columns=['A'] 
) 
   
figure, axes = plt.subplots(figsize=(10, 6)) 
  
axes.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m')) 
  
axes.bar(diff.index, 
         diff['A'],  
         width=25,  
         align='center') 

Output:

Example 2:

import matplotlib 
import matplotlib.pyplot as plt 
from datetime import datetime 
  
origin = ['2020-02-05 17:17:55', 
          '2020-02-05 17:17:51',  
          '2020-02-05 17:17:49'] 
  
a = [datetime.strptime(d, '%Y-%m-%d %H:%M:%S') for d in origin] 
  
b = ['35.764299', '20.3008', '36.94704'] 
  
x = matplotlib.dates.date2num(a) 
formatter = matplotlib.dates.DateFormatter('%H:%M:%S') 
  
figure = plt.figure() 
axes = figure.add_subplot(1, 1, 1) 
  
axes.xaxis.set_major_formatter(formatter) 
plt.setp(axes.get_xticklabels(), rotation = 15) 
  
axes.plot(x, b) 
plt.show() 

Output:

My Personal Notes

Matplotlib.dates.DateFormatter

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