StyleFrame

Exporting DataFrame to designed excel file have never been so easy

A library that wraps pandas and openpyxl and allows easy styling of dataframes in excel

$ pip install styleframe

You can read the documentation at http://styleframe.readthedocs.org/en/latest/

Usage Examples

First, let us create a DataFrame that contains data we would like to export to an .xlsx file

import pandas as pd

df = pd.DataFrame({'Col A': [1, 20, -3],
                   'Col B': [15, 3, 116],
                   'Col C': [33, -6, 9]})

row_max_value = df.idxmax(axis=1)

df['Sum'] = df.sum(axis=1)
df['Mean'] = df.mean(axis=1)

Now, once we have the DataFrame ready, lets create a StyleFrame object

from StyleFrame import StyleFrame

sf = StyleFrame(df)
# it is also possible to directly initiate StyleFrame
sf = StyleFrame({'Col A': [1, 20, -3],
                 'Col B': [15, 3, 116],
                 'Col C': [33, -6, 9]})

The StyleFrame object will auto-adjust the columns width and the rows height but they can be changed manually

sf.set_column_width_dict(col_width_dict={
    ('Col A', 'Col B', 'Col C'): 15.3,
    ('Sum', 'Mean'): 30
})

 # excel rows starts from 1
 # row number 1 is the headers
sf.set_row_height_dict(row_height_dict={
    (1,): 45,
    (2, 3, 4): 25
})

Next, let's change the background color of the maximum values to red and the font to white

from StyleFrame import Styler, colors

for row_index, col_name in rows_max_value.iteritems():
    sf[col_name][row_index].style = Styler(bg_color=colors.red, bold=True, font_color=colors.white).create_style()

And change the font and the font size of Sum and Mean columns

sf.apply_column_style(cols_to_style=['Sum', 'Mean'],
                      font_color='#40B5BF',
                      font_size=18,
                      bold=True,
                      style_header=True)

Finally, let's export to Excel but not before we use more of StyleFrame's features:

• Change the page writing side
• Freeze rows and columns
• Add filters to headers

sf.to_excel('data.xlsx',
            right_to_left=False,
            columns_and_rows_to_freeze='B2', # will freeze the rows above 2 (=row 1 only) and columns that before column 'B' (=col A only)
            row_to_add_filters=0).save()

the result: