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diff --git a/docs/tutorial.rst b/docs/tutorial.rst index 7545e66..421954a 100644 --- a/docs/tutorial.rst +++ b/docs/tutorial.rst @@ -121,30 +121,38 @@ Tablib's killer feature is the ability to export your :class:`Dataset` objects i **Comma-Separated Values** :: - >>> data.csv + >>> data.export('csv') Last Name,First Name,Age Reitz,Kenneth,22 Monke,Bessie,20 **JavaScript Object Notation** :: - >>> data.json + >>> data.export('json') [{"Last Name": "Reitz", "First Name": "Kenneth", "Age": 22}, {"Last Name": "Monke", "First Name": "Bessie", "Age": 20}] **YAML Ain't Markup Language** :: - >>> data.yaml + >>> data.export('yaml') - {Age: 22, First Name: Kenneth, Last Name: Reitz} - {Age: 20, First Name: Bessie, Last Name: Monke} **Microsoft Excel** :: - >>> data.xls + >>> data.export('xls') <redacted binary data> +**Pandas DataFrame** :: + + >>> data.export('df') + First Name Last Name Age + 0 Kenneth Reitz 22 + 1 Bessie Monke 21 + + ------------------------ Selecting Rows & Columns ------------------------ @@ -224,7 +232,7 @@ In this example, we have a function that generates a random grade for our studen Let's have a look at our data. :: - >>> data.yaml + >>> data.export('yaml') - {Age: 22, First Name: Kenneth, Grade: 0.6, Last Name: Reitz} - {Age: 20, First Name: Bessie, Grade: 0.75, Last Name: Monke} @@ -255,7 +263,7 @@ For example, we can use the data available in the row to guess the gender of a s Adding this function to our dataset as a dynamic column would result in: :: - >>> data.yaml + >>> data.export('yaml') - {Age: 22, First Name: Kenneth, Gender: Male, Last Name: Reitz} - {Age: 20, First Name: Bessie, Gender: Female, Last Name: Monke} @@ -292,6 +300,14 @@ Now that we have extra meta-data on our rows, we can easily filter our :class:`D It's that simple. The original :class:`Dataset` is untouched. +Open an Excel Workbook and read first sheet +-------------------------------- + +To open an Excel 2007 and later workbook with a single sheet (or a workbook with multiple sheets but you just want the first sheet), use the following: + +data = tablib.Dataset() +data.xlsx = open('my_excel_file.xlsx', 'rb').read() +print(data) Excel Workbook With Multiple Sheets ------------------------------------ @@ -358,7 +374,7 @@ it's often useful to create a blank row containing information on the upcoming d # Write spreadsheet to disk with open('grades.xls', 'wb') as f: - f.write(tests.xls) + f.write(tests.export('xls')) The resulting **tests.xls** will have the following layout: |