This import will not cost you anything except running some code!

The need to productively have an all in one solution to manage your data as your code has become more critical as volumes of data become larger. Do you, as a data analyst, therefore, need to send your data into an excel file? Previously we would have posted a video How do I remove unwanted characters, and here we build on that theme, linking in with Excel.

Two techniques used here to achieve this are  XLSX writer explained, and Openpyxl explained.

The elements we cover off are:

• Load data from a dataframe and populate into an excel file.
•  Renaming of a sheet.
• Creating a new sheet and giving it a name.
• We look at properties, namely changing the colour of a tab to yellow.
• You may need to put some text in a sheet cell, to act as a header or to show you have a total figure there.
• And the final piece of functionality covered in this video is how to copy data from one sheet into another one.

There are several benefits to putting all the upfront work in Python:

1. The benefits of cleansing the data or format will save time further down the road.
2. After you receive the document, you can quickly review without fixing errors in the data.
3. If you are distributing the output to several people, it quickly gets them what they want, without manual intervention after the logic has completed.

I have certainly benefited in this data cleansing and importing into excel exercise, as the two are combined now, makes it a more efficient process.

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