如何并排绘制两个图

Question

I found the following example on matplotlib:

import numpy as np
import matplotlib.pyplot as plt


x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 2.0)

y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
y2 = np.cos(2 * np.pi * x2)

plt.subplot(2, 1, 1)
plt.plot(x1, y1, 'ko-')
plt.title('A tale of 2 subplots')
plt.ylabel('Damped oscillation')


plt.subplot(2, 1, 2)
plt.plot(x2, y2, 'r.-')
plt.xlabel('time (s)')
plt.ylabel('Undamped')

plt.show()

My question is: What do i need to change, to have the plots side-by-side?

Answer 1

Change your subplot settings to:

plt.subplot(1, 2, 1)

...

plt.subplot(1, 2, 2)

The parameters for subplot are: number of rows, number of columns, and which subplot you're currently on. So 1, 2, 1 means "a 1-row, 2-column figure: go to the first subplot." Then 1, 2, 2 means "a 1-row, 2-column figure: go to the second subplot."

You currently are asking for a 2-row, 1-column (that is, one atop the other) layout. You need to ask for a 1-row, 2-column layout instead. When you do, the result will be:

In order to minimize the overlap of subplots, you might want to kick in a:

plt.tight_layout()

before the show. Yielding:

Answer 2

Check this page out: http://matplotlib.org/examples/pylab_examples/subplots_demo.html

plt.subplots is similar. I think it's better since it's easier to set parameters of the figure. The first two arguments define the layout (in your case 1 row, 2 columns), and other parameters change features such as figure size:

import numpy as np
import matplotlib.pyplot as plt

x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 2.0)
y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
y2 = np.cos(2 * np.pi * x2)

fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(5, 3))
axes[0].plot(x1, y1)
axes[1].plot(x2, y2)
fig.tight_layout()

Answer 3

When stacking subplots in one direction, the matplotlib documentation advocates unpacking immediately if you are just creating a few axes.

fig, (ax1, ax2) = plt.subplots(1,2, figsize=(20,8))
sns.histplot(df['Price'], ax=ax1)
sns.histplot(np.log(df['Price']),ax=ax2)
plt.show()

Answer 4

You can use - matplotlib.gridspec.GridSpec

Check - https://matplotlib.org/stable/api/_as_gen/matplotlib.gridspec.GridSpec.html

The below code displays a heatmap on right and an Image on left.

#Creating 1 row and 2 columns grid
gs = gridspec.GridSpec(1, 2) 
fig = plt.figure(figsize=(25,3))

#Using the 1st row and 1st column for plotting heatmap
ax=plt.subplot(gs[0,0])
ax=sns.heatmap([[1,23,5,8,5]],annot=True)

#Using the 1st row and 2nd column to show the image
ax1=plt.subplot(gs[0,1])
ax1.grid(False)
ax1.set_yticklabels([])
ax1.set_xticklabels([])

#The below lines are used to display the image on ax1
image = io.imread("https://images-na.ssl-images- amazon.com/images/I/51MvhqY1qdL._SL160_.jpg")

plt.imshow(image)
plt.show()

Output image

Answer 5

Basically we have to define how many rows and columns we require. Lets Say we have total 4 categorical columns to be plotted. Lets have total 4 plots in 2 rows and 2 columns.

    import matplotlib.pyplot as plt
    import matplotlib
    import seaborn as sns
    sns.set_style("darkgrid")
    %matplotlib inline
    #15 by 15 size set for entire plots
    plt.figure(figsize=(15,15));
    #Set rows variable to 2
    rows = 2
    #Set columns variable to 2, this way we will plot 2 by 2 = 4 plots
    columns = 2
    #Set the plot_count variable to 1
    #This variable will be used to define which plot out of total 4 plot
    plot_count = 1
    cat_columns = [col for col in df.columns if df[col].dtype=='O']
    for col in cat_columns:
        plt.subplot(rows, columns, plot_count)
        sns.countplot(x=col, data=df)
        plt.xticks(rotation=70);
        #plot variable is incremented by 1 till 4, specifying which plot of total 4 plots
        plot_count += 1