Tuesday, January 26, 2021

Data Analytics Ireland

Data Analytics and Video Tutorials

Excel Spreadsheet

Presenting data in rows and columns on a computer screen.

Python Tutorial Python working with excel 

Python Tutorial: How to create charts in Excel

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Estimated reading time: 2 minutes

Taking it further with a python excel chart.

We have created some video content here using Python with Excel that illustrates the different ways you can leverage Python to

  • Data cleanse
  • Find unwanted characters
  • And see if the file is empty before import!

What this video is giving as output

Here we are looking to introduce charts in Excel, and how how to use Python to easily work with your data and export to an excel sheet.

Below is the final output of our two charts, this is for illustrative purposes, and is taken from the Irish Governments website as at 1st May 2020, importing the cell ranges associated with them.

A barchart of covid cases bullt in Python a line chart of covid cases built in Python

How we went about it

In the below video on creating a python excel chart, we have approached this as follows:

 

  • Created four separate data frames, they are the four regions that will feed into the creation of the graphs.
  • Separate to this, we merged the four data frames into one, to use with the bar chart.

And to finish off

If you like what this video has explained, please click to see our YouTube channel for more informative videos.

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Python Tutorial Python working with excel 

how to validate cell values in excel

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Estimated reading time: 2 minutes

Validating cells in Excel quickly – how to do it easily!
Are you working with large spreadsheets and looking to quickly at data validation exercise to save you time?

The aim would be to run your code and test it against some predefined rules you or your data analyst would have written to make sure it brings back the expected checks.

If you look at the below, this is the final output of this video, highlighting two cells that are over budget based on the companies predefined budget.

data validation example

The structure of this code can be broken down into the following steps:

  • Read in the excel file, see a previous example here How to import data into excel
  •  Run the first function,  checks if the spreadsheet cell value is over or under budget.
  •  Run the second function that takes the value from the first function and applies the colour red to the cell if it is over budget.

 

Finally

You can expand this code to incorporate more functionality, such as:

  • Change the colour of the cells, to have multiple colours returned.
  •  Update the two functions to include more business rules.
  •  You could check if the file is empty before processing as shown here How to check if a file is empty

Please subscribe to our YouTube channel, the button is the right-hand side of the page if you would like to see more like these.

Data Analytics Ireland

Python Tutorial Python working with excel 

How to import data into excel

admin 245 Views 0 Comments , , , ,

Estimated reading time: 2 minutes

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 data frame 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.

Please remember to subscribe to our channel if you like the work we are doing, thanks!

Data Analytics Ireland