python主流绘图工具：matplotlib ，seaborn,pandas ，openpyxl ,xslwriter

openpyxl :首先说下这个官网的demo，看的有点懵，没有具体说明多个图在一个excel引用不通ws Rererence 只是简单的一个deepcopy 用的一点懵逼，反正我是没看懂，其次多sheet写入也未做拓展，

看了下博客哪些水军一篇粘贴复制毫无新意：

下面以openpyxl 3d bar 柱状图为例：演示效果多sheet 生成柱状图：

from openpyxl import Workbook

from openpyxl.chart import (

Reference,

Series,

BarChart3D,

)

def bar_3d(configurations: dict):

""""

paint 3d bar in the excel ,

configuration={"data":None,"Title":None,"sheet_name":None,"index":None}

data:[

[姓名，column1,column2],

[value_name,value_col1,value_col2],

[value_name2,value_column2,value_column2]

]

"""

wb = Workbook()

for configuration in configurations:

sheet = configuration["sheet_name"]

ws = wb.create_sheet(sheet, index=configuration["index"])

rows = configuration["data"]

rows.insert(0, configuration["axis_x"])

for row in rows:

ws.append(row)

data = Reference(ws, min_col=2, min_row=1, max_col=3, max_row=7)

titles = Reference(ws, min_col=1, min_row=2, max_row=7)

chart = BarChart3D()

chart.title = configuration["Title"]

chart.add_data(data=data, titles_from_data=True)

chart.set_categories(titles)

chart.height=16

chart.width=28

chart.shape="box"

ws.add_chart(chart, "E5")

save_path = "test_static.xlsx"

wb.save(save_path)

解释参数：configurations 是一个存放许多configranition 的列表：每个configration 结构如注释：

configuration={"data":None,"Title":None,"sheet_name":None,"index":None}

data:[

[value_name,value_col1,value_col2],

[value_name2,value_column2,value_column2]

]

data就是要写入的数据包含header 和value,data[0]是表头，data[1:]全部是数据，index代表插入excel的sheet的index也就是第几个sheet,Title是绘制柱状图的title：

chart.height是图表的高度，width是宽度，add_chart 是插入chart 方法“E5"指定在excel插入位置，

rows.insert(0, configuration["axis_x"]) 这里插入是type分类的名称也就是rows.insert(0,[姓名，column1,column2])

，看个实际效果吧这个type就对应周日饱和，和bug提交量两列

多个sheet查看：

第二部分:使用pandas 绘图结合xslwriter：

官网：https://xlsxwriter.readthedocs.io/example_pandas_chart_columns.html

我就直接上代码了数据自己造了个用pandas：

import pandas as pd

def panda_chart(df_list, cols, title_x, title_y):

"""

data of narray

index of data_frame: [0,1,2,3]

cols numbers of static columns

"""

writer = pd.ExcelWriter('pandas_chart_columns2.xlsx', engine='xlsxwriter')

for i, df in enumerate(df_list):

# df = pd.DataFrame(data, index=None, columns=["姓名", "饱和度", "人力"])

sheet_name = f'Sheet{i}'

df.to_excel(writer, sheet_name=sheet_name,index=False)

workbook = writer.book

worksheet = writer.sheets[sheet_name]

chart = workbook.add_chart({'type': 'column'})

# set colors for the chart each type .

colors = ['#E41A1C', '#377EB8'] # , '#4DAF4A', '#984EA3', '#FF7F00']

# Configure the series of the chart from the dataframe data.

for col_num in range(1, cols + 1):

chart.add_series({

'name': [f'{sheet_name}', 0, col_num],

'categories': [f'{sheet_name}', 1, 0, 4, 0], # axis_x start row ,start col,end row ,end col

'values': [f'{sheet_name}', 1, col_num, 4, col_num], # axis_y value of

'fill': {'color': colors[col_num - 1]}, # each type color choose

'overlap': -10,

})

# Configure the chart axes.

chart.set_x_axis({'name': f'{title_x}'})

chart.set_y_axis({'name': f'{title_y}', 'major_gridlines': {'visible': False}})

chart.set_size({'width': 900, 'height': 400})

# Insert the chart into the worksheet.

worksheet.insert_chart('H2', chart)

writer.save()

if __name__ == '__main__':

data=[("a",2,4),("b",5,7)]

df = pd.DataFrame(data, index=None, columns=["姓名", "饱和度", "人力"])

panda_chart([df],2,"title x","title y")

标签：index,sheet,name,excel,chart,value,绘图,data,pandas

来源： https://www.cnblogs.com/SunshineKimi/p/12131884.html