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I get the fanfare around infographics. They’re used to make information more appealing, grab attention, awaken interest, lessen boredom and make that information memorable and easier to understand.

However sometimes they don’t deliver on all points and often miss the most important point, which is to quickly and clearly communicate your message.

Just take the graphic below by chúng tôi titled “Rebalance of power”, which I wouldn’t say is strictly an infographic but it’s had a bit of zhushing. To test its effectiveness see how long it takes you to:

compare one region’s results to another

find the region with the lowest unemployment %

compare the shape of each region’s radar charts

Now, my economics training consists of one semester as part of my accounting qualification so perhaps I’m not the target audience for this infographic. That said, if the target audience are economists then I’d have thought they don’t need it all pretty to get the message.

So for the purpose of this post let’s assume that the target audience is your average man on the street because I want to address the use of radar charts in general and look at alternatives for them.

Chart Effectiveness

Before we dive in to critiquing the infographic let’s recap the purpose of a chart, which also applies to an infographic:

The goal with any chart or graph is to clearly and quickly communicate your message.

Testing the info-graphic against that statement, and assuming the target audience is your average Joe Blow, it falls short.

To Map or not to Map

Whenever you’re reporting data by region or country it’s tempting to use a map. However the map in this example, while attention grabbing, is really just a space hogging, fancy legend with no substance or message to deliver.

Off the Radar

The radar charts are the real problem here though.

Radar charts display data in a circular fashion, which is the opposite of the straight line comparisons we’re able to subconsciously perform. This means we have to work hard to make any comparisons and as a result we’re likely to make mistakes in our assumptions.

I could go on scolding radar charts but Stephen Few has already written this paper; “Keep Radar Graphs Below the Radar – Far Below”.

The data consists of multiple measures that require different quantitative scales, which a bar graph cannot accommodate.

The objective of the graph is to assess the symmetry of the values rather than to compare their magnitudes.

The data fits a circular display because it is intuitively circular in nature or by convention.

That said, I still think most of the time you’re better off using charts that allow you to plot data in a linear fashion as this makes it easier for all ability levels to interpret. i.e. not only Economists.

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Excel Alternatives to Radar Charts

One option is to use Conditional Formatting Data Bars as shown below:

Boring, I hear you say 🙂 I agree it doesn’t have the same attention grabbing appeal of the infographic but it’s a lot quicker and easier to interpret and your readers will thank you for that.

If you wanted to retain some of the eye catching infographic effect you could do something like this:

But, personally I think grouping the data by region makes comparisons difficult. And if you retain the grouping by measure (see below), then the colour coding makes it look like a Christmas tree and you don’t know where to look first:

Note: the map in this example is a static image. This tutorial does not cover creating choropleth maps in Excel but you can find some choropleth chart templates here.

Moral of the Story

If you want to compare data across multiple criteria and regions then radar charts are not ideal. Better choices are Conditional Formatting Data Bars, bar charts, small multiples and Sparklines.

You're reading Excel Alternatives To Radar Charts

How To Add Legends To Charts In Python?

Introduction…

The main purpose of charts is to make understand data easily. “A picture is worth a thousand words” means complex ideas that cannot be expressed in words can be conveyed by a single image/chart.

When drawing graphs with lot of information, a legend may be pleasing to display relevant information to improve the understanding of the data presented.

How to do it..

In matplotlib, legends can be presented in multiple ways. Annotations to draw attention to specific points are also useful to help the reader understand the information displayed on the graph.

1. Install matplotlib by opening up the python command prompt and firing pip install matplotlib.

2. Prepare the data to be displayed.

Example import matplotlib.pyplot as plt # data prep (I made up data no accuracy in these stats) mobile = ['Iphone','Galaxy','Pixel'] # Data for the mobile units sold for 4 Quaters in Million units_sold = (('2023',12,8,6), ('2023',14,10,7), ('2023',16,12,8), ('2023',18,14,10), ('2023',20,16,5),)

3. Split the data into arrays for each company company’s mobile units.

Example # data prep - splitting the data IPhone_Sales = [Iphones for Year, Iphones, Galaxy, Pixel in units_sold] Galaxy_Sales = [Galaxy for Year, Iphones, Galaxy, Pixel in units_sold] Pixel_Sales = [Pixel for Year, Iphones, Galaxy, Pixel in units_sold] # data prep - Labels Years = [Year for Year, Iphones, Galaxy,Pixel in units_sold] # set the position Position = list(range(len(units_sold))) # set the width Width = 0.2

4. Creating a Bar graph with the data chúng tôi product sales gets a call to .bar, specifying its position and sales.

Annotation is added using the xy and xytext attributes. Looking at the data, the Google Pixel mobile sales have dropped by 50% i.e. from 10Million units sold in 2023 to just 5Million in 2023. So we are going to set the text and annotation to out last bar.

Finally, we will add the legend using the legend chúng tôi default, matplotlib will draw the legend over an area where there’s the least overlap of data.

Example plt.bar([p - Width for p in Position], IPhone_Sales, width=Width,color='green') plt.bar([p for p in Position], Galaxy_Sales , width=Width,color='blue') plt.bar([p + Width for p in Position], Pixel_Sales, width=Width,color='yellow')

# Set X-axis as years plt.xticks(Position, Years)

# Set the Y axis label plt.xlabel('Yearly Sales') plt.ylabel('Unit Sales In Millions')

# Set the annotation Use the xy and xytext to change the arrow plt.annotate('50% Drop in Sales', xy=(4.2, 5), xytext=(5.0, 12), horizontalalignment='center', arrowprops=dict(facecolor='red', shrink=0.05))

# Set the legent Finally let us save the figure.

import matplotlib.pyplot as plt

# data prep (I made up data no accuracy in these stats) mobile = ['Iphone','Galaxy','Pixel']

# Data for the mobile units sold for 4 Quaters in Million units_sold = (('2023',12,8,6), ('2023',14,10,7), ('2023',16,12,8), ('2023',18,14,10), ('2023',20,16,5),)

# data prep - splitting the data IPhone_Sales = [Iphones for Year, Iphones, Galaxy, Pixel in units_sold] Galaxy_Sales = [Galaxy for Year, Iphones, Galaxy, Pixel in units_sold] Pixel_Sales = [Pixel for Year, Iphones, Galaxy, Pixel in units_sold]

# data prep - Labels Years = [Year for Year, Iphones, Galaxy,Pixel in units_sold]

# set the position Position = list(range(len(units_sold)))

# set the width Width = 0.2

plt.bar([p - Width for p in Position], IPhone_Sales, width=Width,color='green') plt.bar([p for p in Position], Galaxy_Sales , width=Width,color='blue') plt.bar([p + Width for p in Position], Pixel_Sales, width=Width,color='yellow')

# Set X-axis as years plt.xticks(Position, Years)

# Set the Y axis label plt.xlabel('Yearly Sales') plt.ylabel('Unit Sales In Millions')

# Set the legent plt.legend(mobile, title='Manufacturers')

plt.legend(mobile, title='Manufacturers') plt.subplots_adjust(right=1.2)

# plt.show()

Open Source Alternatives To Google

Is it feasible to drop Google for a period of time in exchange for unfettered open source alternatives?

When I first pondered the notion of such an idea, I figured I must be losing my mind. Drop Google? The search giant, regardless of how well-intentioned it may be, has an octopus-like hold on the Internet – its tentacles are everywhere.

Oddly enough, though, it turned out to be easier than I expected. Let’s look at the mindset, software choices and habit changes needed to make this idea doable.

Dropping Google

Considering Google’s contributions to the open source world, why would anyone want to stop supporting such a company? Well, the problem with Google is that despite their support of open source developers, their track record with privacy concerns is spotty.

Perhaps even worse, the fact is that we are becoming entirely too dependent on Google products over those from smaller vendors. Everything from document management to revenue generation is almost entirely tied to Google these days. Ask anyone using the Web regularly and the odds are huge they’re using at least one Google product.

So when we think of dropping Google products, we’re really saying that you’re going to be changing your natural behavior when using your computer. Can open source software seriously meet this challenge head on?

It turns out that it really comes down to one thing: software.

The software lineup

Which specific tools and applications are viable options to replace their Google-powered counterparts? After much searching, I ended up with a compilation of known open source applications and one tool that is just another search engine.

Face it, just because we’re trying to break the Google habit doesn’t mean that starting a new search engine from scratch is in order. Instead let’s use existing open source solutions and see if they have what it takes to replace their Google-based counterparts.

Chrome replacement: Initially I looked into Chromium, but found that it’s still too much of a Google product. So clearly that wouldn’t work. Finally after many hours hunting, I settled on Firefox from Mozilla. Yes, Firefox uses Google search by default. Luckily this can be remedied easily by simply switching to something else for handling search queries.

Google search replacement: Don’t shoot the messenger folks – no, technically DuckDuckGoisn’t an open source search engine.

But after looking into managing my own search engine, I decided that DuckDuckGo might be the best alternative to Google after all. In addition to offering a great API, DuckDuckGo does something very important that Google does not. DuckDuckGo doesn’t track you. They also don’t collect any privacy-harming “cookied data” on you, either.

Gmail replacement: I honestly thought I was out of luck finding a Gmail replacement. Luckily it turns out a trip to SourceForge was all that was needed. I found an open source Webmail solution called Roundcube.

Everything you could want from a webmail client from threaded email to multiple sender identities is available within this software package. The only thing I found missing was a list of hosting companies supporting Roundcube, and perhaps indications of spam filtering. Apart from these quibbles, Roundcube looks awesome.

Google Reader replacement: At first I figured I was going to be subjected to a desktop RSS client to replace Google Reader. It turns out that this wasn’t going to be a problem at all. There’s a Web app called NewsBlur that not only feels like a true Google Reader replacement, it’s also open source and imports content from your existing Reader account. How’s that for awesome functionality?

Google Talk replacement: Finding a replacement for Google Talk was brain-dead simple, I just needed to install Ekiga! Using Ekiga is a natural fit as it supports open protocols like SIP and will work on both Linux and Windows.

The only downside I could find is getting other people to install it. Without the second party making that installation happen, you’d be have only a number of short one-way conversations.

Google Docs replacement: This replacement was perhaps the most difficult so far. Sure, one could stick to the proprietary route and use one of the countless alternatives in the collaborative space. But the idea is to use open source software as the alternative. After extensive searching, I finally located something called the “TeamDrive extension” for Open Office.

The good news is that TeamDrive is supporting the open source office suite Open Office. It would also stand to reason this will be carried over to Libre Office in the future as well. The bad news is that the extension itself is freeware – it’s not open source at all. Surely we can give kudos to the extension developers for selecting Open Office rather than Microsoft Office, right?

Transitioning From Excel To Python

Transitioning from Excel to Python

Written by

CFI Team

Published April 27, 2023

Updated July 7, 2023

Transitioning from Excel to Python

Many companies are now transitioning from Excel to Python, a high-level, general-purpose programming language created by Dutch programmer Guido van Rossum. A growing number of software developers today consider Python a worthy replacement tool for Excel due to the benefits the former can offer.

Summary

The transition from Excel to Python can be justified due to the capability of the latter in executing complex calculations and algorithms.

Python is easier to learn and master, unlike Excel, which includes a personalized language known as VBA that is complex to master and execute.

Transitioning from Excel to Python enables users to enjoy various benefits, such as an open-source coding platform, many volunteer contributors, and free libraries.

Using Excel and Python

Excel is a common tool for data analysis, and it is commonly used to carry out analytical operations in the financial industry. However, Excel tends to be more complex since it requires the application of VBAs. VBAs are complex to operate, and they make Excel difficult to work with when dealing with multiple operations during data analysis.

Python, as a programming language, offers various benefits compared to Excel. It is an open-source programming language, with numerous contributors who volunteer to provide regular updates to the code and improve its functionality.

On the contrary, Excel is a paid software that only provides program updates to those who bought the application, thus limiting its use. Python also comes with a wide variety of preinstalled libraries, which saves time for developers who would otherwise be required to create projects from scratch.

Functional Integrations

A good data analysis software should be able to integrate with other analytical and non-analytical software. Python fits well into this description since it integrates well with other programs. Users can import and export different types of file formats into Python.

For example, Python is compatible with SQL syntax and can even run it within its framework to extract data and tables to its environment. The Python environment is also efficient in automating tasks such as importing data and writing analyzed data to Excel or CSV functions for data analysis.

Transitioning from Excel to Python can be justified from a functional integration point of view. First, Python is user-friendly, and both beginners and experienced analysts can use the language with ease. Excel uses VBA language, which is a personalized platform that uses macros to automate tasks for data analysis.

The use of macros to automate tasks is more complex than the automation of tasks in the Python environment. Also, the fact that Python can be easily integrated with other programs makes it more suitable for data analysis.

To learn more about the inner workings of Python, check out CFI’s Machine Learning for Finance – Python Fundamentals course!

Code Compatibility

Data analysis code can be stored as scripts for reuse and further manipulation. Python code is reproducible and compatible, which makes it suitable for further manipulation by other contributors who are running independent projects. Unlike the VBA language used in Excel, data analysis using Python is cleaner and provides better version control.

Better still is Python’s consistency and accuracy in the execution of code. Other users can replicate the original code and still experience a smooth execution at the same level as the original code. The ability to reproduce code makes Python more efficient than Excel since users can bypass the initial coding process and start with an already functioning framework.

Scalability and Efficiency

Data scientists prefer Python over Excel due to its ability to handle large data sets, as well as incorporate machine learning and modeling. When handling large amounts of data, Excel takes longer to finish calculations compared to Python. When data is loaded onto the two programs simultaneously, Excel will lag behind Python since it is not built to handle large amounts of data.

Compared to Excel, Python is better placed for handling data pipelines, automating tasks, and performing complex calculations. Moreover, it comes with a wide pool of manipulation tools and libraries.

Python vs. Excel in Organizations

Python is considered a more efficient data analysis tool for complex calculations and large volumes of data. However, Excel is still more popular overall than Python, and it is used by a large number of people in financial analysis.

While Excel is not ideal for handling large volumes of data, it is a more convenient tool for organizations with small volumes of data that require simple calculations. Python, on the other hand, is more efficient than Excel when the organization handles large volumes of data that require automation to produce results within a short period.

Additional Resources

How To Create Excel Template?

Create Templates in Excel

We have different types and categories of templates available in Excel, which can access from the File menu ribbon’s New section. This has different types of Templates such as Business, Calendar, Budget, Planner, Financial Management, etc. To create customized templates other than these, we can use Data Validation for drop-down, Table, and Images and give them proper header names. We can also insert a logo for our template. To standardize the template, always fix the theme or template, and visuals should see the purpose of creation. In this article, we will learn about Create Templates in Excel.

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How to create Templates?

Templates can be made by saving an Excel file with a specialized extension and then saving the file in a specified directory.

What type of content can be stored as a Template?

Text data can be stored as a template. Various document sections, such as page titles, column and row labels, text, section headings, and any cell in Excel containing text or numbers, or any kind of data, can all be included in a template. We can also include any graphical shapes, logos of companies, or any background image and even Excel formulae.

The type of text formatting, such as font, color, or size, can be saved along with the data as a template. Formats of cells or worksheets, such as column width or background fill color or alignment of text and even formats of numbers and dates, and several sheets can be saved in templates.

All hidden and protected areas, such as locked cells that cannot be altered and hidden columns and rows, or even worksheets that may contain data not meant for general view.

All Macros are specially customized toolbars that may contain frequently used options; macros and the quick access toolbar can be saved as templates.

How to Create Templates in Excel?

To create a template in recent versions of Excel, very little work must be done.

Excel 2013 & later versions – Before saving a file as a template, one has to define the custom template directory.

Go to File.

Select the option Save in the menu ribbon.

Find the option Default personal templates location among the various options.

Choose a directory where you want to save all the templates. DocumentsCustom Office Templates is regarded as a good choice.

Firstly, go to the File.

Now, the option to provide a name to your template file appears.

Here we see that in the drop-down menu, there is an option called Excel Template (*.xltx)

Note: It is better to choose “Excel Macro-Enabled Template” (.xltm) for cases where the workbook might contain macros. “Excel 97-2003 Template” (.xlt) is to be chosen for the cases where the version of the Excel workbook is very old. “Excel Template” (.xltx) should be chosen for all other cases.

Examples to Create Templates in Excel

Below are some examples to create templates in Excel.

Example #1

First, we will make all the changes in a new file and modify it until all the items you wish to save in the template are ready. Then you have to save the file as a template. Template files have a special extension.

In the screenshot above, we have added an image and text as the template’s structure. Now we shall follow the steps below to create the Excel template.

Step 1 – Firstly, go to File.

Now, the option to provide a name to your template file appears.

Step 3 – Here, we see that in the drop-down menu, select Excel Template (*.xltx)

Now, automatically, Excel will place this template file in the appropriate directory. And new Excel documents can be created based on this template file by navigating and choosing “Personal” in the new file window (right next to Featured) and then choosing the appropriate template.

Concepts always become much clearer when we have more examples. So, let us look at yet another example of creating Excel Templates.

Example #2

Let us explore how to save a Macro-Enabled Excel template through an example. Suppose we have an Excel with some macros(s) to be used as a base for other files; then we need to save this Excel as a macro-enabled Excel template.

In the screenshots above, we added a macro in the template file, and now we shall create the template in Excel.

Now, the option to provide a name to your template file appears.

Here we see that in the drop-down menu, there is an option called Excel Macro-Enabled Template (*.xltm)

Now, automatically, Excel will place this template file in the appropriate directory. And new Excel documents can be created based on this template file by navigating.

Firstly, go to File.

Choose Personal in the new file window (next to Featured) and then choose Template 2.

Example #3

Now, let us look at another example. Firstly, we will make all the changes in the new file and modify it until all the items you wish to save in the template are ready. Then you have to save the file as a template. Template files have a special extension.

We have added an image and text as the template’s structure in the above screenshot. Now we shall follow the steps below to create the Excel template.

Now, the option to provide a name to your template file appears.

Step 2 – Here, we see that in the drop-down menu, select Excel Template (*.xltx)

Example #4

Now, let us look at yet another example. Now, we will make all the changes in a new file and modify it until all the items you wish to save in the template are ready. Then you have to save the file as a template. Template files have a special extension.

In the screenshot above, as you can see, we have added the template structure – we have added a world map, increased the default worksheets, and renamed them, and now we shall proceed to save this file as a template.

Now we shall follow the steps below to create the Excel template.

Now, the option to provide a name to your template file appears.

Step 2 – Here, from the drop-down menu, select Excel 97-2003 Template (*.xlt)

Example #5

Now we shall use a template file to create a new file in Excel. We will make use of the Example #4 template file.

Firstly, go to File.

Choose “Personal” in the new file window (next to Featured) and choose the appropriate template.

We shall choose Template 4 as the base and create a new file in Excel.

As we can see, all the template structures are retained, and the new file is named Template4 1 – the first file based on Template 4.

Example #6

Now we shall use another template file to create a new file in Excel. We will make use of the Example #3 template file.

We shall choose Template 3 as the base and create a new file in Excel.

Hence, we can see that the image and the header structure are retained in the new file. And it is also important to note that this new file is named Template 3 1 – signifying that it is the first file based on Template 3.

Example #7

Now we shall create another new template. We will create the template structure in Excel, as shown below.

Now we shall follow the steps below to create the Excel template.

Now, the option to provide a name to your template file appears.

Step 2 – Here, from the drop-down menu, select Excel Template (*.xltx)

This will create a Template 7 template with the template structure defined in the Default Template location in Excel.

Example #8

Now we shall attempt to use Template 7 to create another file in Excel.

Now, automatically, Excel will place this file in the appropriate directory.

Example #9

Let us see an example where we have Excel formulae in the Template file.

As we can see above, we have created a Template structure with the formula for Net Profit Margin defined as:

Net Profit Margin = (Net Profit/Total Revenue)*100

Since this is the template, no data is present here. Let us see how to create the template file in Excel.

Now we shall follow the steps below to create the Excel template.

Now, the option to provide a name to your template file appears.

Step 2 – Here, from the drop-down menu, select Excel Template (*.xltx)

This will create a Template 9. xltx template with the template structure defined in the Default Template location.

Example #10

Now, we shall attempt to use the previous example template to create a new file and see if that works in Excel.

We see that in the new file, we have the structure defined, and once we feed in the data on Columns A, B, and C, the Net Profit Margin in Column D is automatically calculated using the Template File formula.

Example #11

Let us now use our second example – Template 2 to create a new file in Excel. Template2 has a defined macro, so let us see if the same is available in the new file.

Now let us see what happens when we select “Template2”.

It opens up a new file with the same macro (that was defined in the template file) loaded automatically.

We will get the desired result.

Things to Remember

For versions of Excel 2013 and later, it is possible to change Excel’s default template for a workbook by saving the template at the appropriate location. All default templates must have a specific name – chúng tôi or chúng tôi and must be saved in Excel’s startup directory. C:Users%username%AppDataRoamingMicrosoftExcelXLSTART

The template has to be named xltx or Sheet to modify the template to add new sheets in existing files. xltm and must be saved in the same folder.

Convert Numbers To Text In Excel

Convert Numbers to Text in Excel (Table of Contents)

How to Convert Numbers to Text in Excel

There are different ways to convert numbers to text in excel. In Excel, we have the TEXT function, which is used to convert numbers to text named. Text function is one of the ways to convert numbers to text. For this, we just have to select the numbers we want to convert into text and select the format we want to change that number to text. Selecting Zero will keep that number but into text, and if we change that format, the value will be changed in that format but will be in the text.

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Steps to Convert Numbers to Text in Excel

Below mentioned is the easiest way to Convert Numbers to Text in Excel. If you have only two or three cell data that needs to be converted into text, these are the simple steps you can follow.

Once done with the above steps, you can confirm whether the number has been changed to the text format or not.

Step 3 – Select the cell which already changed into the text; while selecting the cell, a message box icon with a drop-down appears on the left side.

Once you point on the message box icon, the corresponding text will be displayed, which shows if the number in the cell is converted into text?

Step 4 – By selecting the dropdown arrow, it is possible to change the text to its old form using Convert to Number.

Examples to Convert Numbers to Text in Excel

You can download this Convert Numbers to Text in Excel Template here – Convert Numbers to Text in Excel Template

These are the following examples to convert numbers to text:

1. Using General Formula

2. Using format cells command

3. Using addon tools

Example #1

As a simple method, you can use this inbuilt function Text which is shown in the below screenshot, and the format is as follows.

=Text(value, format_text)

Value refers to the cell that contains the data you want to convert, and the next part format_text represents in which format you want to see the data.

Example #2

In cell C2 please enter the formula =Text (B2, “0”).

Then press Enter key.

Drag and fill up to the range that you want to apply. The results as shown below.

After applying the formula, the values are pasted in the same sheet. The numbers are changed into text format. The green indication in the upper corner of the cell commonly shows when you have entered a text formatted value into the cell. Or when you change the format of any given data to the text format.

Example #3

To change the format of the result, we can change the formula as =Text(B1, ”000000”), which will result in the whole data will be shown in six-digit numbers. The missing place values will be filled with “0”. If you want to change the whole data into a unique format or a unique number of decimals, then this format is preferred.

In the above example, column Data1 consists of integer numbers with different decimal places. So here we want to make it in a unique way. To change the given numbers into a similar number of decimal values, we have applied the formula. The format has given 6 decimal places =Text(B1, ”000000”). So the numbers are changed to 6 digit numbers, and the missing decimal places are filled with zero.

Example #4

To convert numbers to Text in Excel with different decimal points, the changes to do with the formula is

=Text(B1,”00.000’). Which will keep the given data into a similar format in such a way number of digits after the decimal point? The figure is given shows the result after applying the formula in the given data.

In this example, we want to make the number of digits after the decimal point into a unique number. So the formula is changed into =Text(B1, ”00.000’. This will show 3 digits after the decimal point.

Using Format Cells Command

According to your recommendation, theFormat_Cells Command is commonly used to change the data of the given cells into another format.

Automatically set the data type of empty cells.

How to Set the Data Type Automatically in Excel?

The same method is preferred in this case. Below is the screenshot where the format of the empty cells is changed into text. So if you enter the numbers into these cells, the data will keep the format as text automatically.

How to Avoid Missing Numbers while Converting Numbers into Text?

It is better to keep the numbers in text format to prevent missing numbers while processing or changing from one sheet to another.

In the above, once you press enter after entering the numbers, the common result will be as below.

The initial “0” will be lost since you haven’t set any data type to this column. The same will happen when you try to copy-paste the same numbers from this sheet to another.

Using Add-On Tools

Different Add-on Tools like Kutools for Excel. These are built-in tools for excel which can be downloaded and used as add-on functions with your excel.

Step to Download Kutools

Go to Google and search for free Kutools and download the setup of Kutools from there.

This provides different options to process your data in any way you want.

More than the available functions with normal excel here, you can find customized options to deal with functions.

Which shows two different options as Text to numbers and Numbers to Text.

Using Excel Macros

Excel macros are another option where you can design your own customized functions to change the numbers into text.

If you are good at VBA, then go for this method where you can design functions and apply that to the data where ever you want.

It is possible to create VBA functions like stored procedures /functions. So as like the normal functions can directly apply this to the excel cells.

Another option is to create separate macro fixing buttons and assign created functions to the macro that you have created.

Things to Remember About Convert Numbers to Text in Excel

If the number starts with “0”, be aware of changing the data into text before processing it further. There are chances to lose this initial zero while doing copy paste into another cell.

If you know the data type prior to processing, it sets the empty cell format before you process it.

If you want to keep the numbers as text and found any issues on copy-pasting it into another sheet, keep the data in a note pad and again copy it from the notepad

Select the better option according to the quantity of data you need to process.