Matplotlib is a module or package or library in python which is used for data visualization. Pyplot is an interface to a Matplotlib module that provides a MATLAB-like interface.
Matplotlib.pyplot.plot_date ()
This function used to add dates to the plot.
Syntax:
matplotlib.pyplot.plot_date(x, y, fmt=’o’, tz=None, xdate=True, ydate=False, data=None, **kwargs)
This is the syntax of date function. It contains various parameters or arguments which are explained below.
S.no. |
Parameter/Arguments |
Description |
|
1. |
x, y |
x and y both are the coordinates of the data i.e. x-axis horizontally and y-axis vertically. |
|
2. |
fmt |
It is a optional string parameter that contains the corresponding plot details like color, style etc. |
|
3. |
tz |
tz stands for timezone used to label dates, default(UTC). |
|
4. |
xdate |
xdate parameter contains boolean value. If xdate is true then x-axis is interpreted as date in matplotlib. By default xdate is true. |
|
5. |
ydate |
If ydate is true then y-axis is interpreted as date in matplotlib. By default ydate is false. |
|
6. |
data |
The data which is going to be used in plot. |
The last parameter **kwargs is the Keyword arguments control the Line2D properties like animation, dash_ joint-style, colors, linewidth, linestyle, marker, etc.
Example 1:
Python3
# importing librariesimport matplotlib.pyplot as pltfrom datetime import datetime# creating array of dates for x axisdates = [ datetime(2020, 6, 30), datetime(2020, 7, 22), datetime(2020, 8, 3), datetime(2020, 9, 14)]# for y axisx = [0, 1, 2, 3]plt.plot_date(dates, x, 'g')plt.xticks(rotation=70)plt.show() |
Output:
Example 2: Creating a plot using dataset.
Python3
# importing librariesimport pandas as pdimport matplotlib.pyplot as pltfrom datetime import datetime# creating a dataframedata = pd.DataFrame({'Date': [datetime(2020, 6, 30), datetime(2020, 7, 22), datetime(2020, 8, 3), datetime(2020, 9, 14)], 'Close': [8800, 2600, 8500, 7400]})# x-axisprice_date = data['Date']# y-axisprice_close = data['Close']plt.plot_date(price_date, price_close, linestyle='--', color='r')plt.title('Market', fontweight="bold")plt.xlabel('Date of Closing')plt.ylabel('Closing Amount')plt.show() |
Output:
Example 3: Changing the format of the date:
Python3
# importing librariesimport pandas as pdimport matplotlib.pyplot as pltfrom datetime import datetime# creating a dataframedata = pd.DataFrame({'Date': [datetime(2020, 6, 30), datetime(2020, 7, 22), datetime(2020, 8, 3), datetime(2020, 9, 14)], 'Close': [8800, 2600, 8500, 7400]})# x-axisprice_date = data['Date']# y-axisprice_close = data['Close']plt.plot_date(price_date, price_close, linestyle='--', color='r')plt.title('Market', fontweight="bold")plt.xlabel('Date of Closing')plt.ylabel('Closing Amount')# Changing the format of the date using# dateformatter classformat_date = mpl_dates.DateFormatter('%d-%m-%Y')# getting the accurate current axes using gca()plt.gca().xaxis.set_major_formatter(format_date)plt.show() |
Output:
The format of the date changed to dd-mm-yyyy. To know more about dataformatter and gca() click here.
