Matplotlib:在一幅图中创建多个子图 [英] Matplotlib: create multiple subplot in one figure

问题描述

我有一个数据列，其列为x1, x2, x3, x4, x5, x6, my_y.我正在为每个xi〜y绘制散点图，例如:

I have a data frame has columns x1, x2, x3, x4, x5, x6, my_y. I am making a scatter plot for each xi ~ y like:

%matplotlib notebook
import matplotlib.pyplot as plt
import matplotlib
matplotlib.style.use('ggplot')
my_df.plot(x='x1', y='my_y', kind = 'scatter', marker = 'x', color = 'black', ylim = [0, 10])

我对x1, x2, x3, x4, x5, x6重复了上述代码6次，以创建6个图形.我想知道是否可以用6个散点图制作一个图形?谢谢！

I repeated the above code 6 times for x1, x2, x3, x4, x5, x6, to create 6 figures. I am wondering if it possible to make one figure with 6 scatter subplots? Thanks!

推荐答案

df = pd.DataFrame(
    np.random.randint(10, size=(5, 7)),
    columns='x1 x2 x3 x4 x5 x6 my_y'.split()
)

df

   x1  x2  x3  x4  x5  x6  my_y
0   0   8   3   2   7   5     8
1   0   6   2   5   8   4     9
2   4   7   1   2   6   4     5
3   8   5   4   0   5   7     4
4   5   6   0   1   8   7     2

---

选项1
使用axes元素中的scatter方法.

---

Option1
Use the scatter method from the axes elements.

fig, axes = plt.subplots(2, 3, figsize=(6, 4), sharex=True, sharey=True)
y = df.my_y.values
for i in range(6):
    axes[i//3, i%3].scatter(df.iloc[:, i].values, y)

fig.tight_layout()

选项2
使用pandas.DataFrame.plot

fig, axes = plt.subplots(2, 3, figsize=(6, 4), sharex=True, sharey=True)
y = df.my_y.values
for i in range(6):
    df.plot(x='x' + str(i+1),
            y='my_y',
            kind='scatter',
            marker='x',
            color='black',
            ylim=[0, 10],
            ax=axes[i//3, i%3])

fig.tight_layout()

回复评论
没有sharex=True

fig, axes = plt.subplots(2, 3, figsize=(6, 4), sharey=True)
y = df.my_y.values
for i in range(6):
    df.plot(x='x' + str(i+1),
            y='my_y',
            kind='scatter',
            marker='x',
            color='black',
            ylim=[0, 10],
            ax=axes[i//3, i%3])

fig.tight_layout()

这篇关于Matplotlib:在一幅图中创建多个子图的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！