使用Python 3将多个matplotlib图形放入Excel

我正在尝试基于Python 3中调用的数据框架创建一些图形，并将它们导出到Excel中。我一直在使用下面响应中的一些代码，但当我将其用于多个图形时，它会给我一些奇怪的结果：

我的代码是：

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import openpyxl

filepath = 'C:\Filepath\Template.xlsx'
writer = pd.ExcelWriter(filepath, engine='xlsxwriter')
back.to_excel(writer, sheet_name='test')
writer.save()

## PLOTS
## ts1 is company 1 and ts2 is company 2
def plot_results(df, ts1, ts2, filepath, cell):
    months = mdates.MonthLocator()  # every month
    fig, ax = plt.subplots()
    ax.plot(df['price_date'], df[ts1], label=ts1)
    ax.plot(df['price_date'], df[ts2], label=ts2)
    ax.xaxis.set_major_locator(months)
    ax.xaxis.set_major_formatter(mdates.DateFormatter('%b %Y'))
#    ax.set_xlim(datetime.datetime(start_year, start_month_num, start_day_num), datetime.datetime(end_year, end_month_num, end_day_num))
    ax.grid(True)
    fig.autofmt_xdate()

    plt.xlabel('Month/Year')
    plt.ylabel('Cumulative Percent Growth')
    plt.title('%s and %s Cumulative Percent Growth' % (ts1, ts2))
    plt.legend()
    plt.savefig('plot.png', dpi=150)

    plt.show()

    wb = openpyxl.load_workbook(filepath)
    ws = wb.active    
    img = openpyxl.drawing.image.Image('plot.png')
    img.anchor(ws.cell(cell))
    ws.add_image(img)
    wb.save(filepath)

def plot_scatter_ts(df, ts1, ts2, filepath, cell):
    plt.xlabel('%s Price ($)' % ts1)
    plt.ylabel('%s Price ($)' % ts2)
    plt.title('%s and %s Price Scatterplot' % (ts1, ts2))
    plt.scatter(df[ts1], df[ts2])

    plt.show()

    wb = openpyxl.load_workbook(filepath)
    ws = wb.active
    plt.savefig('plot.png', dpi=150)    
    img = openpyxl.drawing.image.Image('plot.png')
    img.anchor(ws.cell(cell))
    ws.add_image(img)
    wb.save(filepath)

plot_results(back, 'adj_close_price4.0', 'adj_close_price26.0', filepath, 'P2')
plot_scatter_ts(back, 'adj_close_price4.0', 'adj_close_price26.0', filepath, 'P34')

当我单独运行函数plot\u reults或plot\u scatters时，它们会运行并进入Excel。但是如果我把它们一起运行，只有最后运行的图形会出现在Excel文档中，所以在本例中是散点图。此外，我真的不想在Python界面中看到图形，因此如果我在plot_results函数中去掉plt.show，散点图出于某种原因会变成条形图，这很奇怪，因为这些图形都不是条形图，它们在不同的函数中

有人知道我做错了什么吗

谢谢

更新13/6/18

抱歉，有点忙，我没机会再谈这个了

正如Screenpaver建议的那样，我已经使用Pandas xlsxwriter重写了我的代码。但是，当我试图做一个以上的情节，它似乎仍然混淆了情节。我的代码如下：

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import openpyxl

filepath = 'C:\...\Template.xlsx'


## Chart 1

def plot_results(df, ts1, ts2, sheet_name, filepath, cell):

    ## Create Pandas Excel writer using Xlswriter as the engine
    writer = pd.ExcelWriter(filepath, engine='xlsxwriter')
    back.to_excel(writer, sheet_name=sheet_name, startrow=1, startcol=1)

    ## Access the Xlswriter workbook and worksheets objects from the dataframe.
    workbook = writer.book
    worksheet = writer.sheets[sheet_name]

    ## Create a chart object 
    chart = workbook.add_chart({'type':'line'})

    ## Calculate extremes for axes
    min_x1 = back[ts1].min()
    max_x1 = back[ts1].max()
    min_x2 = back[ts2].min()
    max_x2 = back[ts2].max()    
    min_x = min(min_x1, min_x2)
    max_x = max(max_x1, max_x2)


    ## Configure the series of the chart from the dataframe data
    chart.add_series({
            'name':ts1,
            'categories': '=test!$D$3:$D502',
            'values':'=test!$C$3:$C502'
            })

    chart.add_series({
            'name':ts2,
            'categories': '=test!$D$3:$D502',
            'values':'=test!$E$3:$E502'
            })

    ## Configure chart axis
    chart.set_x_axis({'name':'Month/Year',
                      'date_axis':True,
                      'num_format': 'mm/yy', 
                      'major_gridlines':{
                              'visible':True,
                              'line':{'width':1, 'dash_type':'dash'}
                              }})
    chart.set_y_axis({'name':'Cumulative Percent Growth',
                      'min':min_x,
                      'max':max_x,
                      'major_gridlines':{
                              'visible':True,
                              'line':{'width':1, 'dash_type':'dash'}
                              }                  
                      })
    chart.set_title({'name':'%s and %s Cumulative Percent Growth' % (ts1, ts2)})

    chart.set_legend({'position':'bottom'})
    chart.set_chartarea({'border':{'none':True}})

    ## Insert chart into worksheet
    worksheet.insert_chart(cell, chart)

    writer.save()




## Chart 2
def plot_scatter_ts(df, ts1, ts2, sheet_name, filepath, cell):

    ## Create Pandas Excel writer using Xlswriter as the engine
    writer = pd.ExcelWriter(filepath, engine='xlsxwriter')
    back.to_excel(writer, sheet_name=sheet_name, startrow=1, startcol=1)

    ## Access the Xlswriter workbook and worksheets objects from the dataframe.
    workbook = writer.book
    worksheet = writer.sheets[sheet_name]


    ## Create a chart object 
    chart = workbook.add_chart({'type':'scatter'})


    min_x1 = back[ts1].min()
    max_x1 = back[ts1].max()
    min_x2 = back[ts2].min()
    max_x2 = back[ts2].max()    

    ## Configure the series of the chart from the dataframe data
    chart.add_series({
            #        'name':'Series1',
            'categories': 'test!$E$3:$E502',
            'values':'=test!$C$3:$C502'
            })


    ## Configure chart axis
    chart.set_x_axis({'name':ts1,
                          'min':min_x2,
                          'max':max_x2})
    chart.set_y_axis({'name':ts2,
                          'min':min_x1,
                          'max':max_x1})

    chart.set_title({'name':'%s and %s Price Scatterplot' % (ts1, ts2)})

    chart.set_legend({'none':True})
    chart.set_chartarea({'border':{'none':True}})

    ## Insert chart into worksheet
    worksheet.insert_chart(cell, chart)

    writer.save()

plot_scatter_ts(back, 'adj_close_price4.0', 'adj_close_price26.0', 'test2', filepath, 'Q18')

plot_results(back, 'series1', 'series2', 'test2', filepath, 'Q2')

当分别运行另一个函数时，每个函数都很好，但当我运行这两个函数时，会得到一个混乱的图

---

感谢

感谢screenpaver通过将write移出以下功能使其正常工作：

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import openpyxl

filepath = 'C:\...\Template.xlsx'
sheet_name='test'

writer = pd.ExcelWriter(filepath, engine='xlsxwriter')

## Chart 1

def plot_results(writer, df, ts1, ts2, sheet_name, filepath, cell):

    ## Create Pandas Excel writer using Xlswriter as the engine
    df.to_excel(writer, sheet_name=sheet_name, startrow=1, startcol=1)

    ## Access the Xlswriter workbook and worksheets objects from the dataframe.
    workbook = writer.book
    worksheet = writer.sheets[sheet_name]

    ## Create a chart object 
    chart = workbook.add_chart({'type':'line'})

    ## Calculate extremes for axes
    min_x1 = df[ts1].min()
    max_x1 = df[ts1].max()
    min_x2 = df[ts2].min()
    max_x2 = df[ts2].max()    
    min_x = min(min_x1, min_x2)
    max_x = max(max_x1, max_x2)


    ## Configure the series of the chart from the dataframe data
    chart.add_series({
            'name':ts1,
            'categories': '=test!$D$3:$D502',
            'values':'=test!$C$3:$C502'
            })

    chart.add_series({
            'name':ts2,
            'categories': '=test!$D$3:$D502',
            'values':'=test!$E$3:$E502'
            })

    ## Configure chart axis
    chart.set_x_axis({'name':'Month/Year',
                      'date_axis':True,
                      'num_format': 'mm/yy', 
                      'major_gridlines':{
                              'visible':True,
                              'line':{'width':1, 'dash_type':'dash'}
                              }})
    chart.set_y_axis({'name':'Cumulative Percent Growth',
                      'min':min_x,
                      'max':max_x,
                      'major_gridlines':{
                              'visible':True,
                              'line':{'width':1, 'dash_type':'dash'}
                              }                  
                      })
    chart.set_title({'name':'%s and %s Cumulative Percent Growth' % (ts1, ts2)})

    chart.set_legend({'position':'bottom'})
    chart.set_chartarea({'border':{'none':True}})

    ## Insert chart into worksheet
    worksheet.insert_chart(cell, chart)





## Chart 2
def plot_scatter_ts(writer, df, ts1, ts2, sheet_name, filepath, cell):

    ## Create Pandas Excel writer using Xlswriter as the engine
    df.to_excel(writer, sheet_name=sheet_name, startrow=1, startcol=1)

    ## Access the Xlswriter workbook and worksheets objects from the dataframe.
    workbook = writer.book
    worksheet = writer.sheets[sheet_name]


    ## Create a chart object 
    chart = workbook.add_chart({'type':'scatter'})


    min_x1 = df[ts1].min()
    max_x1 = df[ts1].max()
    min_x2 = df[ts2].min()
    max_x2 = df[ts2].max()    

    ## Configure the series of the chart from the dataframe data
    chart.add_series({
            #        'name':'Series1',
            'categories': 'test!$E$3:$E502',
            'values':'=test!$C$3:$C502'
            })


    ## Configure chart axis
    chart.set_x_axis({'name':ts1,
                          'min':min_x2,
                          'max':max_x2})
    chart.set_y_axis({'name':ts2,
                          'min':min_x1,
                          'max':max_x1})

    chart.set_title({'name':'%s and %s Price Scatterplot' % (ts1, ts2)})

    chart.set_legend({'none':True})
    chart.set_chartarea({'border':{'none':True}})

    ## Insert chart into worksheet
    worksheet.insert_chart(cell, chart)




plot_scatter_ts(writer, back, 'series1', 'series2', sheet_name, filepath, 'Q18')

plot_results(writer, back, 'series1', 'series2', sheet_name, filepath, 'Q2')

writer.save()

---

你看过Pandas xlsxwriter接口图表的使用情况吗？add_系列等等？感谢screenpaver，我在上面添加了一个使用xlswriter的更新，但是在运行这两个函数时，图形仍然混乱。第二个函数不是覆盖了第一个函数创建的电子表格吗？似乎您希望在函数之外创建并传递“writer”，然后在第二个函数调用返回后使用writer.save。感谢screenpaver让它工作起来！