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* * * [ Matplotlib Reference](https://example.com/matplotlib/matplotlib-apiref.html) `boxplot()` is used to draw box plots, visually displaying the five-number summary of data: minimum, first quartile, median, third quartile, maximum, and possible outliers. Box plots are a core tool for exploratory data analysis, suitable for comparing distribution characteristics of multiple groups of data. ## Function Definition matplotlib.pyplot.boxplot(x, notch=None, sym=None, vert=None, whis=None, positions=None, widths=None, patch_artist=None, bootstrap=None, usermedians=None, conf_intervals=None, meanline=None, showmeans=None, showcaps=None, showbox=None, showfliers=None, boxprops=None, labels=None, flierprops=None, medianprops=None, meanprops=None, capprops=None, whiskerprops=None, manage_ticks=True, autorange=False, zorder=None, capwidths=None, **kwargs) ## Parameter Description | Parameter | Type | Description | | --- | --- | --- | | x | array or array sequence | Input data, 1D array draws one box plot, 2D array sequence draws multiple | | notch | bool | Whether to draw notched box plot (notch for median confidence interval), default False | | vert | bool | True=vertical (default), False=horizontal | | whis | float or (float, float) | Whisker length (multiple of IQR), default 1.5. e.g., (5, 95) represents 5th and 95th percentiles | | sym | str or None | Marker style for outliers, None means not showing outliers | | widths | float or array-like | Width of each box | | patch_artist | bool | If True, box uses fill color (can customize with facecolor) | | showmeans | bool | Whether to show mean point, default False | | showfliers | bool | Whether to show outliers, default True | | labels | list | Labels for each box | | boxprops / flierprops / medianprops / meanprops | dict | Control appearance properties of box/outliers/median line/mean respectively | > Box plot structure: box spans from Q1 to Q3, middle line is median. Whiskers extend to the farthest data points within Q1-1.5*IQR to Q3+1.5*IQR range. Values beyond whiskers are outliers. * * * ## Usage Examples ### Example 1: Basic Box Plot ## Example import matplotlib.pyplot as plt import numpy as np np.random.seed(42) # Three groups of data with different distributions data =[ np.random.normal(0,1,100),# standard normal np.random.normal(2,1.5,100),# mean=2, std=1.5 np.random.normal(-1,0.5,100),# mean=-1, std=0.5 ] fig, ax = plt.subplots(figsize=(7,5), layout='constrained') bp = ax.boxplot(data, labels=['Group A','Group B','Group C'], patch_artist=True) # Custom colors colors =['#3498db','#e74c3c','#2ecc71'] for patch, color in zip(bp['boxes'], colors): patch.set_facecolor(color) ax.set_title('Box Plot: Comparing Three Groups') ax.set_ylabel('Value') ax.grid(axis='y', alpha=0.3) plt.show() ### Example 2: Notched Box Plot + Show Means ## Example import matplotlib.pyplot as plt import numpy as np np.random.seed(42) data =[ np.random.normal(0,1,100), np.random.normal(0,1.2,100), np.random.normal(0.3,1,100), ] fig, ax = plt.subplots(figsize=(7,5), layout='constrained') bp = ax.boxplot(data, notch=True,# notch (median confidence interval) showmeans=True,# show means meanprops=dict(marker='D', markerfacecolor='red', markersize=8), patch_artist=True, labels=['Control','Test A','Test B']) colors =['#bdc3c7','#3498db','#2ecc71'] for patch, color in zip(bp['boxes'], colors): patch.set_facecolor(color) ax.set_title('Notched Box Plot with Means') ax.set_ylabel('Measurement') ax.grid(axis='y', alpha=0.3) plt.show() ### Example 3: Horizontal Box Plot ## Example import matplotlib.pyplot as plt import numpy as np np.random.seed(42) data =[np.random.exponential(scale=s, size=100)for s in[1,2,3,4]] labels =['Scale=1','Scale=2','Scale=3','Scale=4'] fig, ax = plt.subplots(figsize=(8,5), layout='constrained') bp = ax.boxplot(data, labels=labels, vert=False,# horizontal patch_artist=True) colors =['#e74c3c','#f39c12','#2ecc71','#3498db'] for patch, color in zip(bp['boxes'], colors): patch.set_facecolor(color) patch.set_alpha(0.7) ax.set_title('Horizontal Box Plot') ax.set_xlabel('Value') ax.grid(axis='x', alpha=0.3) plt.show() * * * ## FAQ ### What do the parts of a box plot mean? Box: IQR from Q1 (25%) to Q3 (75%). Median line: line in the middle of box = Q2 (50%). Whiskers: extend to the farthest data points within Q1-1.5*IQR and Q3+1.5*IQR. Outliers: individual data points outside the whisker range. [ Matplotlib Reference](https://example.com/matplotlib/matplotlib-apiref.html)