Pandas To Excel

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First of all, this post is the first piece of the solution, where you should specify startrow=: Append existing excel sheet with new dataframe using python pandas. You might also consider header=False. So it should look like. First of all, this post is the first piece of the solution, where you should specify startrow=: Append existing excel sheet with new dataframe using python pandas. You might also consider header=False. So it should look like.

Python Pandas is a Python data analysislibrary. It can read, filter and re-arrange small and large data sets andoutput them in a range of formats including Excel.

Pandas writes Excel files using the Xlwt module for xls files and the Openpyxl or XlsxWriter modules for xlsxfiles.

Import pandas writer = pandas.ExcelWriter ('Masterfile.xlsx') datafiltered.toexcel (writer, 'Main', cols= 'Diff1', 'Diff2') writer.save Masterfile.xlsx already consists of number of different tabs. However, it does not yet contain 'Main'. Pandas correctly writes to 'Main' sheet, unfortunately it also deletes all other tabs. Example: Pandas Excel output with user defined header format An example of converting a Pandas dataframe to an Excel file with a user defined header format using Pandas and XlsxWriter. The pandas DataFrame toexcel function is used to save a pandas dataframe to an excel file. It’s like the tocsv function but instead of a CSV, it writes the dataframe to a.xlsx file. The following is its syntax.

Using XlsxWriter with Pandas

To use XlsxWriter with Pandas you specify it as the Excel writer engine:

The output from this would look like the following:

See the full example at Example: Pandas Excel example.

Accessing XlsxWriter from Pandas

In order to apply XlsxWriter features such as Charts, Conditional Formattingand Column Formatting to the Pandas output we need to access the underlyingworkbook and worksheet objects. Afterthat we can treat them as normal XlsxWriter objects.

Continuing on from the above example we do that as follows:

This is equivalent to the following code when using XlsxWriter on its own:

The Workbook and Worksheet objects can then be used to access other XlsxWriterfeatures, see below.

Adding Charts to Dataframe output

Once we have the Workbook and Worksheet objects, as shown in the previoussection, we we can use them to apply other features such as adding a chart:

The output would look like this:

See the full example at Example: Pandas Excel output with a chart.

Note

The above example uses a fixed string =Sheet1!$B$2:$B$8 for the datarange. It is also possible to use a (row,col) range which can bevaried based on the length of the dataframe. See for exampleExample: Pandas Excel output with a line chart and Working with Cell Notation.

Adding Conditional Formatting to Dataframe output

Another option is to apply a conditional format like this:

Which would give:

See the full example at Example: Pandas Excel output with conditional formatting.

Formatting of the Dataframe output

XlsxWriter and Pandas provide very little support for formatting the outputdata from a dataframe apart from default formatting such as the header andindex cells and any cells that contain dates or datetimes. In addition itisn’t possible to format any cells that already have a default format applied.

If you require very controlled formatting of the dataframe output then youwould probably be better off using Xlsxwriter directly with raw data takenfrom Pandas. However, some formatting options are available.

For example it is possible to set the default date and datetime formats viathe Pandas interface:

Which would give:

See the full example at Example: Pandas Excel output with datetimes.

It is possible to format any other, non date/datetime column data usingset_column():

Note: This feature requires Pandas >= 0.16.

See the full example at Example: Pandas Excel output with column formatting.

Formatting of the Dataframe headers

Pandas writes the dataframe header with a default cell format. Since it is acell format it cannot be overridden using set_row(). If you wish touse your own format for the headings then the best approach is to turn off theautomatic header from Pandas and write your own. For example:

See the full example at Example: Pandas Excel output with user defined header format.

Adding a Dataframe to a Worksheet Table

As explained in Working with Worksheet Tables, tables in Excel are a way of grouping a rangeof cells into a single entity, like this:

The way to do this with a Pandas dataframe is to first write the data withoutthe index or header, and by starting 1 row forward to allow space for thetable header:

We then create a list of headers to use in add_table():

Finally we add the Excel table structure, based on the dataframe shape andwith the column headers we generated from the dataframe columns:

Pandas To Excel Append

See the full example at Example: Pandas Excel output with a worksheet table.

Adding an autofilter to a Dataframe output

As explained in Working with Autofilters, autofilters in Excel are away of filtering a 2d range of data to only display rows that match a userdefined criteria.

The way to do this with a Pandas dataframe is to first write the data withoutthe index (unless you want to include it in the filtered data):

We then get the dataframe shape and add the autofilter:

We can also add an optional filter criteria. The placeholder “Region” in thefilter is ignored and can be any string that adds clarity to the expression:

However, it isn’t enough to just apply the criteria. The rows that don’t matchmust also be hidden. We use Pandas to figure our which rows to hide:

This gives us a filtered worksheet like this:

See the full example at Example: Pandas Excel output with an autofilter.

Handling multiple Pandas Dataframes

It is possible to write more than one dataframe to a worksheet or to severalworksheets. For example to write multiple dataframes to multiple worksheets:

See the full example at Example: Pandas Excel with multiple dataframes.

It is also possible to position multiple dataframes within the sameworksheet:

See the full example at Example: Pandas Excel dataframe positioning.

Passing XlsxWriter constructor options to Pandas

XlsxWriter supports several Workbook() constructor options such asstrings_to_urls(). These can also be applied to the Workbook objectcreated by Pandas as follows:

Saving the Dataframe output to a string

It is also possible to write the Pandas XlsxWriter DataFrame output to abyte array:

Note: This feature requires Pandas >= 0.17.

Additional Pandas and Excel Information

Here are some additional resources in relation to Pandas, Excel and XlsxWriter.

  • The XlsxWriter Pandas examples later in the document: Pandas with XlsxWriter Examples.
  • The Pandas documentation on the pandas.DataFrame.to_excel() method.
  • A more detailed tutorial on Using Pandas and XlsxWriter to create Excelcharts.
  • The series of articles on the “Practical Business Python” website aboutUsing Pandas and Excel.

In this post, we will see examples of saving a Pandas dataframe as Excel file. Pandas has to_excel() function to write a dataframe into Excel file.

Let us load Pandas.

We will create two lists and us these to create a dataframe as before.

We can create a Pandas dataframe using the two lists to make a dictionary with DataFrame() function. Our toy dataframe contains two columns.

Pandas to excel append sheet

Now we have the dataframe ready and we can use Pandas’ to_excel() function to write the dataframe to excel file. In the example, below we specify the Excel file name as argument to to_excel() function.

Pandas to_excel() function has number of useful arguments to customize the excel file. For example, we can save the dataframe as excel file without index using “index=False” as additional argument.

One of the common uses in excel file is naming the excel sheet. We can name the sheet using “sheet_name” argument as shown below.

This post is part of the series on Byte Size Pandas: Pandas 101, a tutorial covering tips and tricks on using Pandas for data munging and analysis.

Pandas To Excel Example

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