在 Excel 中,单元格内的条形图称为数据条,您可以使用条件格式添加它。openpyxl
我已经演示了如何使用and来做到这一点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()
样本输出:
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()
样本输出:
REPT
功能
另一种选择是创建单元内条形图是使用REPT
Excel 中的函数。它不像数据栏那么漂亮:)
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()
样本输出: