如何将图添加到subplot matplotlib中

Question

我有这样的情节

fig = plt.figure()
desire_salary = (df[(df['inc'] <= int(salary_people))])
print desire_salary
# Create the pivot_table
result = desire_salary.pivot_table('city', 'cult', aggfunc='count')

# plot it in a separate step. this returns the matplotlib axes
ax = result.plot(kind='bar', alpha=0.75, rot=0, label="Presence / Absence of cultural centre")

ax.set_xlabel("Cultural centre")
ax.set_ylabel("Frequency")
ax.set_title('The relationship between the wage level and the presence of the cultural center')
plt.show()

我想将其添加到subplot。我试试

fig, ax = plt.subplots(2, 3)
...
ax = result.add_subplot()

但它返回 AttributeError：'Series'对象没有属性'add_subplot'。我该如何检查此错误？

Answer 1

matplotlib.pyplot具有当前图形和当前轴的概念。所有绘图命令都适用于当前轴。

import matplotlib.pyplot as plt

fig, axarr = plt.subplots(2, 3)     # 6 axes, returned as a 2-d array

#1 The first subplot
plt.sca(axarr[0, 0])                # set the current axes instance to the top left
# plot your data
result.plot(kind='bar', alpha=0.75, rot=0, label="Presence / Absence of cultural centre")

#2 The second subplot
plt.sca(axarr[0, 1])                # set the current axes instance 
# plot your data

#3 The third subplot
plt.sca(axarr[0, 2])                # set the current axes instance 
# plot your data

<强>演示：

源代码，

import matplotlib.pyplot as plt
fig, axarr = plt.subplots(2, 3, sharex=True, sharey=True)     # 6 axes, returned as a 2-d array

for i in range(2):
    for j in range(3):
        plt.sca(axarr[i, j])                        # set the current axes instance 
        axarr[i, j].plot(i, j, 'ro', markersize=10) # plot 
        axarr[i, j].set_xlabel(str(tuple([i, j])))  # set x label
        axarr[i, j].get_xaxis().set_ticks([])       # hidden x axis text
        axarr[i, j].get_yaxis().set_ticks([])       # hidden y axis text

plt.show()

Answer 2

result是pandas.Series类型，没有add_subplot()方法。

使用fig.add_subplot(...)代替

这是example（使用seaborn模块）：

labels = df.columns.values
fig, axes = plt.subplots(nrows = 3, ncols = 4, gridspec_kw =  dict(hspace=0.3),figsize=(12,9), sharex = True, sharey=True)
targets = zip(labels, axes.flatten())
for i, (col,ax) in enumerate(targets):
    sns.boxplot(data=df, ax=ax, color='green', x=df.index.month, y=col)

您可以使用pandas图而不是seaborn