Matplotlib & Plotly Charts#

Matplotlib#

通过使用 pictures.add() ，能很容易地把Matplotlib图表当作图片贴进Excel中。

从头开始#

最简单的例子都可以归结为下面的模式:

import matplotlib.pyplot as plt
import xlwings as xw

fig = plt.figure()
plt.plot([1, 2, 3])

sheet = xw.Book().sheets[0]
sheet.pictures.add(fig, name='MyPlot', update=True)
_images/mpl_basic.png

备注

如果设置 update=True,就可以做Excel里移动和缩放图表：后续调用 pictures.add() 时如果图表名称相同('MyPlot')，会更新图表，不改变它的位置和大小

全面集成到Excel#

用 RunPython 调用上面的代码并把它绑定到一个按钮上是件水到渠成的事情，并且能够跨平台工作。

不过，在Windows系统上可以通过下面的代码来定义一个 UDF 使得集成度更高:

@xw.func
def myplot(n, caller):
    fig = plt.figure()
    plt.plot(range(int(n)))
    caller.sheet.pictures.add(fig, name='MyPlot', update=True)
    return 'Plotted with n={}'.format(n)

导入这个UDF函数并在B2上调用它，图表会随着B1的值而变化：

_images/mpl_udf.png

属性#

大小、位置和其他属性可以通过 pictures.add() 的参数设定，也可以通过对返回的图片对象进行操作，参见 xlwings.Picture().

例如:

>>> sht = xw.Book().sheets[0]
>>> sht.pictures.add(fig, name='MyPlot', update=True,
                     left=sht.range('B5').left, top=sht.range('B5').top)

或:

>>> plot = sht.pictures.add(fig, name='MyPlot', update=True)
>>> plot.height /= 2
>>> plot.width /= 2

获得Matplotlib图片#

下面是一些如何取得matplotlib figure 对象的例子：

  • 通过PyPlot接口:

    import matplotlib.pyplot as plt
fig = plt.figure()
plt.plot([1, 2, 3, 4, 5])

    或:

    import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4, 5])
fig = plt.gcf()

  • 通过面向对象接口:

    from matplotlib.figure import Figure
fig = Figure(figsize=(8, 6))
ax = fig.add_subplot(111)
ax.plot([1, 2, 3, 4, 5])

  • 通过Pandas:

    import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.rand(10, 4), columns=['a', 'b', 'c', 'd'])
ax = df.plot(kind='bar')
fig = ax.get_figure()

备注

When working with Google Sheets, you can use a maximum of 1 million pixels per picture. Total pixels is a function of figure size and dpi: (width in inches * dpi) * (height in inches * dpi). For example, fig = plt.figure(figsize=(6, 4)) with 200 dpi (default dpi when using pictures.add()) will result in (6 * 200) * (4 * 200) = 960,000 px. To change the dpi, provide export_options: pictures.add(fig, export_options={"bbox_inches": "tight", "dpi": 300}). Existing figure size can be checked via fig.get_size_inches(). pandas also accepts figsize like so: ax = df.plot(figsize=(3, 3)). Note that "bbox_inches": "tight" crops the image and therefore will reduce the number of pixels in a non-deterministic way. export_options will be passed to figure.figsave() when using Matplotlib and to figure.write_image() when using Plotly.

Plotly static charts#

Prerequisites#

In addition to plotly, you will need kaleido, psutil, and requests. The easiest way to get it is via pip:

$ pip install kaleido psutil requests

or conda:

$ conda install -c conda-forge python-kaleido psutil requests

See also: https://plotly.com/python/static-image-export/

How to use#

It works the same as with Matplotlib, however, rendering a Plotly chart takes slightly longer. Here is a sample:

import xlwings as xw
import plotly.express as px

# Plotly chart
df = px.data.iris()
fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species")

# Add it to Excel
wb = xw.Book()
wb.sheets[0].pictures.add(fig, name='IrisScatterPlot', update=True)
_images/plotly.png