Pandas subplots=True will arange the axes in a single column. import numpy as np import matplotlib.pyplot as plt import pandas as pd df = pd.DataFrame(np.random.rand(7,20)) df.plot(subplots=True) plt.tight_layout() plt.show() Here, tight_layout isn’t applied, because the figure is too small to arange the axes nicely. One can use a bigger figure (figsize=(…)) though. In order to have … Read more
There are several ways to do this. The easy way is to exploit the y-labels and titles of the plot and then use fig.tight_layout() to make room for the labels. Alternatively, you can place additional text in the right location with annotate and then make room for it semi-manually. If you don’t have y-labels on … Read more
You can nest your GridSpec using SubplotSpec. The outer grid will be a 2 x 2 and the inner grids will be 2 x 1. The following code should give you the basic idea. import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec fig = plt.figure(figsize=(10, 8)) outer = gridspec.GridSpec(2, 2, wspace=0.2, hspace=0.2) for i in … Read more
You can do it in multiple ways: Here is one solution making use of tick_params: ax.tick_params(labelrotation=45) Here is another solution making use of set_xticklabels: ax.set_xticklabels(labels, rotation=45) Here is a third solution making use of set_rotation: for tick in ax.get_xticklabels(): tick.set_rotation(45)
We create the figure with the subplots: f, axes = plt.subplots(1, 2) Where axes is an array with each subplot. Then we tell each plot in which subplot we want them with the argument ax. sns.boxplot( y=”b”, x= “a”, data=df, orient=”v” , ax=axes[0]) sns.boxplot( y=”c”, x= “a”, data=df, orient=”v” , ax=axes[1]) And the result is:
Use pyplot.suptitle or Figure.suptitle: import matplotlib.pyplot as plt import numpy as np fig=plt.figure() data=np.arange(900).reshape((30,30)) for i in range(1,5): ax=fig.add_subplot(2,2,i) ax.imshow(data) fig.suptitle(‘Main title’) # or plt.suptitle(‘Main title’) plt.show()
Typically, you just pass the axes instance to a function. For example: import matplotlib.pyplot as plt import numpy as np def main(): x = np.linspace(0, 6 * np.pi, 100) fig1, (ax1, ax2) = plt.subplots(nrows=2) plot(x, np.sin(x), ax1) plot(x, np.random.random(100), ax2) fig2 = plt.figure() plot(x, np.cos(x)) plt.show() def plot(x, y, ax=None): if ax is None: ax … Read more
Eaiser and better to just pass your function an Axes: def my_plot_1(x, y, ax): ax.plot(x, y) def my_plot_2(x, y, ax): ax.plot(x, y) fig, axs = plt.subplots(ncols=2, nrows=1) # pass the Axes you created above my_plot_1(x, y, axs[0]) my_plot_2(x, y, axs[1])
You can define a function based on the subplots command (note the s at the end, different from the subplot command pointed by urinieto) of matplotlib.pyplot. Below is an example of such a function, based on yours, allowing to plot multiples axes in a figure. You can define the number of rows and columns you … Read more
The problem is that Matlab assigns the position property of each axis such that there is space around each plot. You can either adjust the position property, or you can get subaxis from the File Exchange and set up the subplots the way you like.