Add error bars to a Matplotlib bar plot Last Updated : 01 May, 2025 Comments Improve Suggest changes Like Article Like Report In this article, we will create a bar plot with error bars using Matplotlib. Error bar charts are a great way to represent the variability in your data. It can be applied to graphs to provide an additional layer of detailed information on the presented data.Approach:Import the required Python libraryMaking simple dataPlot using the plt.errorbar() functionDisplay graphThe errorbar() function in the pyplot module of the matplotlib library plots data points of y versus x with optional error bars, either as lines, markers, or both.Syntax for the Functionmatplotlib.pyplot.errorbar( x, y, yerr=None, xerr=None, fmt='', ecolor=None, elinewidth=None, capsize=None, barsabove=False, lolims=False, uplims=False, xlolims=False, xuplims=False, errorevery=1, capthick=None, *, data=None, **kwargs)Description of Parametersx, y: Horizontal and vertical coordinates of the data points (required).yerr, xerr: Errors for the y and x coordinates, can be a single value or an array.fmt: Format for the markers (e.g. 'o', 's', 'b-'). Default is ''.ecolor: Color of the error bars. Default is None (uses the current axis color).elinewidth: Line width of error bars. Default is None (default line width).capsize: Length of the caps at the ends of the error bars. Default is None.barsabove: If True, error bars are drawn above the plot symbols. Default is False.lolims, uplims, xlolims, xuplims: Limit error bars to certain regions. Default is False for all.errorevery: Frequency of error bars (default is 1, for all points).capthick: Thickness of the cap lines. Default is None.data: Data object (e.g. pandas DataFrame) to use.kwargs: Additional keyword arguments for customizing properties.Implementing Error bars in PythonExample 1: Â Adding some errors in a 'y' value Python import matplotlib.pyplot as plt x = [1, 3, 5, 7] y = [11, 2, 4, 19] c = [1, 3, 2, 1] plt.bar(x, y) plt.errorbar(x, y, yerr=c, fmt="o", color="r") plt.show() Output:Example 2: Â Adding Some errors in the 'x' value Python import matplotlib.pyplot as plt x = [1, 3, 5, 7] y = [11, 2, 4, 19] c = [1, 3, 2, 1] plt.bar(x, y) plt.errorbar(x, y, xerr=c, fmt="o", color="r") plt.show() Output:Example 3: Adding error in x and y Python import matplotlib.pyplot as plt x = [1, 3, 5, 7] y = [11, 2, 4, 19] c = [1, 3, 2, 1] d = [1, 3, 2, 1] plt.bar(x, y) plt.errorbar(x, y, xerr=c, yerr=d, fmt="o", color="r") plt.show() Output:Example 4: Adding variable error in x and y Python import matplotlib.pyplot as plt x = [1, 2, 3, 4, 5] y = [1, 2, 1, 2, 1] y_errormin = [0.1, 0.5, 0.9, 0.1, 0.9] y_errormax = [0.2, 0.4, 0.6, 0.4, 0.2] x_error = 0.5 y_error = [y_errormin, y_errormax] plt.bar(x, y) plt.errorbar(x, y, yerr=y_error, xerr=x_error, fmt='o', color="r") plt.show() Output: Comment More infoAdvertise with us Next Article Add error bars to a Matplotlib bar plot S skrg141 Follow Improve Article Tags : Python Python-matplotlib Practice Tags : python Similar Reads Plotting back-to-back bar charts Matplotlib In this article, we will learn how to plot back-to-back bar charts in matplotlib in python. Let's discuss some concepts : Matplotlib: 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 d 2 min read Use error bars in a Matplotlib scatter plot When visualizing data, error bars provide a great way to indicate variability or uncertainty in your measurements. In this article, weâll explore how to create scatter plots with error bars using Matplotlib's errorbar() function.Syntaxmatplotlib.pyplot.errorbar( x, y, yerr=None, xerr=None, fmt='', e 2 min read Matplotlib.pyplot.barbs() in Python Matplotlib is a library of Python bindings which provides the user with a MATLAB-like plotting framework. Matplotlib can be used in Python scripts, the Python and IPython shell, web application servers, and various graphical user interface toolkits like Tkinter, awxPython, etc. Note: For more inform 3 min read Adding value labels on a Matplotlib Bar Chart A Bar Chart is a graphical representation of data using bars of different heights. It is widely used for comparing different datasets visually. However, by default, Matplotlib does not display value labels on each bar, making it difficult to analyze the exact values represented by individual bars. I 5 min read Matplotlib.axes.Axes.barbs() in Python Matplotlib is a library in Python and it is numerical - mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute. 2 min read Like