Excel

pandas also supports reading table data stored in Excel 2003 (and higher) files, either with the ExcelFile class or the pandas.read_excel function. Internally, these tools use the add-on packages xlrd and openpyxl to read XLS and XLSX files respectively. These must be installed separately from pandas with pipenv.

To use ExcelFile, create an instance by passing a path to an xls or xlsx file:

[1]:
import pandas as pd
[2]:
xlsx = pd.ExcelFile("library.xlsx")

You can then display the sheets of the file with:

[3]:
xlsx.sheet_names
[3]:
['books']
[4]:
books = pd.read_excel(xlsx, "books")

books
[4]:
Titel Sprache Autor*innen Lizenz Veröffentlichungsdatum
0 Python basics en Veit Schiele BSD-3-Clause 2021-10-28
1 Jupyter Tutorial en Veit Schiele BSD-3-Clause 2019-06-27
2 Jupyter Tutorial de Veit Schiele BSD-3-Clause 2020-10-26
3 PyViz Tutorial en Veit Schiele BSD-3-Clause 2020-04-13

If you are reading in multiple sheets of a file, it is quicker to create the Excel file, but you can also just pass the file name to pandas.read_excel:

[5]:
pd.read_excel("library.xlsx", "books")
[5]:
Titel Sprache Autor*innen Lizenz Veröffentlichungsdatum
0 Python basics en Veit Schiele BSD-3-Clause 2021-10-28
1 Jupyter Tutorial en Veit Schiele BSD-3-Clause 2019-06-27
2 Jupyter Tutorial de Veit Schiele BSD-3-Clause 2020-10-26
3 PyViz Tutorial en Veit Schiele BSD-3-Clause 2020-04-13

To write pandas data in Excel format, you must first create an ExcelWriter and then write data to it using pandas.DataFrame.to_excel:

[6]:
writer = pd.ExcelWriter("library.xlsx")
books.to_excel(writer, "books")
writer.close()

You can also pass a file path to_excel and thus bypass the ExcelWriter:

[7]:
books.to_excel("library.xlsx")