python - 在使用 pandas 样式创建的列中使用条形图格式从 pandas 写入 excel 文件

Question

我的数据为:

s = '{"Date":{"0":"2016-10-03 00:00:00","1":"2016-10-03 00:00:00","2":"2016-10-03 00:00:00","3":"2016-10-04 00:00:00","4":"2016-10-04 00:00:00","5":"2016-10-04 00:00:00","6":"2016-10-05 00:00:00","7":"2016-10-05 00:00:00","8":"2016-10-05 00:00:00"},"Close":{"0":31.5,"1":112.52,"2":57.42,"3":113.0,"4":57.24,"5":31.35,"6":57.64,"7":31.59,"8":113.05},"Volume":{"0":14070500,"1":21701800,"2":19189500,"3":29736800,"4":20085900,"5":18460400,"6":16726400,"7":11808600,"8":21453100},"Symbol":{"0":"CSCO","1":"AAPL","2":"MSFT","3":"AAPL","4":"MSFT","5":"CSCO","6":"MSFT","7":"CSCO","8":"AAPL"}}'
df = pd.read_json(s)

看起来像:

        Date  Close    Volume Symbol
0 2016-10-03  31.50  14070500   CSCO
1 2016-10-03 112.52  21701800   AAPL
2 2016-10-03  57.42  19189500   MSFT
3 2016-10-04 113.00  29736800   AAPL
4 2016-10-04  57.24  20085900   MSFT
5 2016-10-04  31.35  18460400   CSCO
6 2016-10-05  57.64  16726400   MSFT
7 2016-10-05  31.59  11808600   CSCO
8 2016-10-05 113.05  21453100   AAPL

我可以通过以下方式创建所需的样式:

format_dict = dict(Date="{:%m/%d/%y}", Close="${:.2f}", Volume="{:,}")
(
    df.style.format(format_dict)
    .hide_index()
    .bar("Volume", color="lightblue", align="zero")
)

看起来像:

但是当我使用以下方法写入 excel 文件时:

format_dict = dict(Date="{:%m/%d/%y}", Close="${:.2f}", Volume="{:,}")
df_formatted = (
    df.style.format(format_dict)
    .hide_index()
    .bar("Volume", color="lightblue", align="zero")
)
df_formatted.to_excel("demo.xlsx")

它给了我以下信息:

我不确定如何解决这个问题。

以下是我为创建此示例的 virtualenv 安装的软件包:

-> % pip freeze
et-xmlfile==1.0.1
jdcal==1.4.1
Jinja2==2.11.1
MarkupSafe==1.1.1
numpy==1.18.2
openpyxl==3.0.3
pandas==1.0.3
python-dateutil==2.8.1
pytz==2019.3
six==1.14.0

Answer 1

在 Excel 中，单元格内条形图称为 data bar , 您可以使用条件格式添加它。我已经演示了如何使用 openpyxl 执行此操作和 xlsxwriter .我建议使用 xlsxwriter，因为它允许您选择渐变或纯色背景，而 openpyxl 没有此选项并会生成带有渐变的数据栏。

XlsxWriter

import pandas as pd
from xlsxwriter.utility import xl_range

s = '{"Date":{"0":"2016-10-03 00:00:00","1":"2016-10-03 00:00:00","2":"2016-10-03 00:00:00","3":"2016-10-04 00:00:00","4":"2016-10-04 00:00:00","5":"2016-10-04 00:00:00","6":"2016-10-05 00:00:00","7":"2016-10-05 00:00:00","8":"2016-10-05 00:00:00"},"Close":{"0":31.5,"1":112.52,"2":57.42,"3":113.0,"4":57.24,"5":31.35,"6":57.64,"7":31.59,"8":113.05},"Volume":{"0":14070500,"1":21701800,"2":19189500,"3":29736800,"4":20085900,"5":18460400,"6":16726400,"7":11808600,"8":21453100},"Symbol":{"0":"CSCO","1":"AAPL","2":"MSFT","3":"AAPL","4":"MSFT","5":"CSCO","6":"MSFT","7":"CSCO","8":"AAPL"}}'
df = pd.read_json(s)

def get_range(df, column_name):
    """Return coordinates for a column range given a column name.

    For example, if "Volume" is the third column and has 10 items,
    output is "C2:C10".
    """
    col = df.columns.get_loc(column_name)
    rows = df.shape[0]
    # Use 1 to skip the header.
    return xl_range(1, col, rows, col)

writer = pd.ExcelWriter("output.xlsx", engine="xlsxwriter")
df.to_excel(writer, sheet_name="Sheet1", index=False)
worksheet = writer.sheets["Sheet1"]
range_ = get_range(df, "Volume")
worksheet.conditional_format(range_, {'type': 'data_bar', 'bar_solid': True})
writer.save()

示例输出:

Openpyxl(不支持实心数据条)

from openpyxl.formatting.rule import DataBar, FormatObject, Rule
import pandas as pd

s = '{"Date":{"0":"2016-10-03 00:00:00","1":"2016-10-03 00:00:00","2":"2016-10-03 00:00:00","3":"2016-10-04 00:00:00","4":"2016-10-04 00:00:00","5":"2016-10-04 00:00:00","6":"2016-10-05 00:00:00","7":"2016-10-05 00:00:00","8":"2016-10-05 00:00:00"},"Close":{"0":31.5,"1":112.52,"2":57.42,"3":113.0,"4":57.24,"5":31.35,"6":57.64,"7":31.59,"8":113.05},"Volume":{"0":14070500,"1":21701800,"2":19189500,"3":29736800,"4":20085900,"5":18460400,"6":16726400,"7":11808600,"8":21453100},"Symbol":{"0":"CSCO","1":"AAPL","2":"MSFT","3":"AAPL","4":"MSFT","5":"CSCO","6":"MSFT","7":"CSCO","8":"AAPL"}}'
df = pd.read_json(s)

first = FormatObject(type='min')
second = FormatObject(type='max')
data_bar = DataBar(cfvo=[first, second], color="ADD8E6", showValue=None, minLength=None, maxLength=None)
rule = Rule(type='dataBar', dataBar=data_bar)

writer = pd.ExcelWriter("output.xlsx", engine="openpyxl")
df.to_excel(writer, sheet_name="Sheet1", index=False)
worksheet = writer.sheets['Sheet1']

# Add data bar to Volume column.
start = worksheet["C"][1].coordinate
end = worksheet["C"][-1].coordinate
worksheet.conditional_formatting.add(f"{start}:{end}", rule)

writer.save()
writer.close()

示例输出:

REPT 函数

另一种创建单元格内条形图的方法是使用 Excel 中的 REPT 函数。它不如数据栏漂亮:)

import pandas as pd
s = '{"Date":{"0":"2016-10-03 00:00:00","1":"2016-10-03 00:00:00","2":"2016-10-03 00:00:00","3":"2016-10-04 00:00:00","4":"2016-10-04 00:00:00","5":"2016-10-04 00:00:00","6":"2016-10-05 00:00:00","7":"2016-10-05 00:00:00","8":"2016-10-05 00:00:00"},"Close":{"0":31.5,"1":112.52,"2":57.42,"3":113.0,"4":57.24,"5":31.35,"6":57.64,"7":31.59,"8":113.05},"Volume":{"0":14070500,"1":21701800,"2":19189500,"3":29736800,"4":20085900,"5":18460400,"6":16726400,"7":11808600,"8":21453100},"Symbol":{"0":"CSCO","1":"AAPL","2":"MSFT","3":"AAPL","4":"MSFT","5":"CSCO","6":"MSFT","7":"CSCO","8":"AAPL"}}'
df = pd.read_json(s)

writer = pd.ExcelWriter("output.xlsx", engine="openpyxl")
df.to_excel(writer, sheet_name="Sheet1", index=False)
worksheet = writer.sheets['Sheet1']

# Use column E because that is the next empty column.
for row, cell in enumerate(worksheet["E"]):
    # Add 1 because Python's indexing starts at 0 and Excel's does not.
    row += 1
    if row != 1:
        # Column C corresponds to Volume.
        value = f'=REPT("|", C{row} / 1000000)'
    else:
        value = "Bar"
    worksheet[f"E{row}"] = value

writer.save()
writer.close()

示例输出: