Write excel file from pandas with bar chart formatting within column created using pandas styles

Question

I have data as:

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)

Which looks like:

        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

I can create the styling required with the following:

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

Which looks as:

But when I write to an excel file using:

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")

It gives me the following:

I'm not sure how to fix this.

Here are the packages that I have installed for the virtualenv creating this example:

-> % 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

I don't think it is possible to have a bar chart with the value over it. Are you OK with a separate column for the bar charts? — jkr
– jkr, Commented Sep 30, 2020 at 23:31
@jakub if that's a limitation of pandas styling and is explained then fair enough - i found it kinda tricky to research anything definite on this, so it'd be handy if this post could serve as that for others in future. — baxx
– baxx, Commented Sep 30, 2020 at 23:33
Sorry, it is possible. please see my answer below stackoverflow.com/a/64147995/5666087 — jkr
– jkr, Commented Oct 1, 2020 at 2:32

jkr · Accepted Answer · 2020-11-19 14:29:06Z

In Excel, the in-cell bar plot is called a data bar, and you can add it with conditional formatting. I have demonstrated how to do this with openpyxl and xlsxwriter. I would suggest using xlsxwriter because it allows you to choose gradient or solid background, whereas openpyxl does not have this option and produces a data bar with a gradient.

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()

Sample output:

Openpyxl (does not support solid data bars)

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()

Sample output:

`REPT` function

Another option is to create in-cell bar plots is to use the REPT function in Excel. It's not as pretty as the data bar :)

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()

Sample output:

i think REPT has a certain charm of it's own :) To be clear, it's not (currently) possible to produce this output using pandas style - therefore the above are necessary? If I'm understanding correctly, then all good, I'd consider the above a solution to the problem. Perhaps some are interested in the output - it's here (the order of the output there is repl / openpyxl / xlsxwriter ) imgur.com/a/iZdgYN8
Yes, it seems like exporting in-cell bar charts to Excel is not supported yet with the pandas style API. But in the pandas user guide, there is a note that features are being added, so perhaps data bars are on their list.
hope so! until then I think this is a good alternative, thank you :)

BENY · Accepted Answer · 2020-04-04 16:59:09Z

1

You just do the format which is for the display purpose, we should assign the columns

df.Volume= df.Volume.map(lambda x: "{:,}".format(x))
df#df.to_excel("demo.xlsx")

         Date   Close      Volume Symbol
0  2016-10-03   31.50  14,070,500   CSCO
1  2016-10-03  112.52  21,701,800   AAPL
2  2016-10-03   57.42  19,189,500   MSFT
3  2016-10-04  113.00  29,736,800   AAPL
4  2016-10-04   57.24  20,085,900   MSFT
5  2016-10-04   31.35  18,460,400   CSCO
6  2016-10-05   57.64  16,726,400   MSFT
7  2016-10-05   31.59  11,808,600   CSCO
8  2016-10-05  113.05  21,453,100   AAPL

answered Apr 4, 2020 at 16:59

BENY

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1 Comment

baxx Over a year ago

thanks, that makes sense... I'm particularly interested in the bar charts within the column though

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