openpyxl

Practical Use Cases

First things first, when would you need to tát use a package lượt thích openpyxl in a real-world scenario? You’ll see a few examples below, but really, there are hundreds of possible scenarios where this knowledge could come in handy.

Learning Some Basic Excel Terminology

Here’s a quick list of basic terms you’ll see when you’re working with Excel spreadsheets:

Getting Started With openpyxl

Now that you’re aware of the benefits of a tool lượt thích openpyxl, let’s get down to tát it and start by installing the package. For this tutorial, you should use Python 3.7 and openpyxl 2.6.2. To install the package, you can vì thế the following:

After you install the package, you should be able to tát create a super simple spreadsheet with the following code:

The code above should create a tệp tin called hello_world.xlsx in the thư mục you are using to tát lập cập the code. If you open that tệp tin with Excel you should see something lượt thích this:

Woohoo, your first spreadsheet created!

Dataset for This Tutorial

Before you dive deep into some code examples, you should download this sample dataset and store it somewhere as sample.xlsx:

This is one of the datasets you’ll be using throughout this tutorial, and it’s a spreadsheet with a sample of real data from Amazon’s online product reviews. This dataset is only a tiny fraction of what Amazon provides, but for testing purposes, it’s more than thở enough.

A Simple Approach to tát Reading an Excel Spreadsheet

Finally, let’s start reading some spreadsheets! To begin with, open our sample spreadsheet:

In the code above, you first open the spreadsheet sample.xlsx using load_workbook(), and then you can use workbook.sheetnames to tát see all the sheets you have available to tát work with. After that, workbook.active selects the first available sheet and, in this case, you can see that it selects Sheet 1 automatically. Using these methods is the mặc định way of opening a spreadsheet, and you’ll see it many times during this tutorial.

Now, after opening a spreadsheet, you can easily retrieve data from it lượt thích this:

To return the actual value of a cell, you need to tát vì thế .value. Otherwise, you’ll get the main Cell object. You can also use the method .cell() to tát retrieve a cell using index notation. Remember to tát add .value to tát get the actual value and not a Cell object:

You can see that the results returned are the same, no matter which way you decide to tát go with. However, in this tutorial, you’ll be mostly using the first approach: ["A1"].

The above shows you the quickest way to tát open a spreadsheet. However, you can pass additional parameters to tát change the way a spreadsheet is loaded.

Importing Data From a Spreadsheet

Now that you’ve learned the basics about loading a spreadsheet, it’s about time you get to tát the fun part: the iteration and actual usage of the values within the spreadsheet.

This section is where you’ll learn all the different ways you can iterate through the data, but also how to tát convert that data into something usable and, more importantly, how to tát vì thế it in a Pythonic way.

Appending New Data

Before you start creating very complex spreadsheets, have a quick look at an example of how to tát append data to tát an existing spreadsheet.

Go back to tát the first example spreadsheet you created (hello_world.xlsx) and try opening it and appending some data to tát it, lượt thích this:

Et voilà, if you open the new hello_world_append.xlsx spreadsheet, you’ll see the following change:

Notice the additional writing ;) on cell C1.

Creating a Simple Spreadsheet

Previously, you saw a very quick example of how to tát write “Hello world!” into a spreadsheet, so sánh you can start with that:

The highlighted lines in the code above are the most important ones for writing. In the code, you can see that:

• Line 5 shows you how to tát create a new empty workbook.
• Lines 8 and 9 show you how to tát add data to tát specific cells.
• Line 11 shows you how to tát save the spreadsheet when you’re done.

Even though these lines above can be straightforward, it’s still good to tát know them well for when things get a bit more complicated.

One thing you can vì thế to tát help with coming code examples is add the following method to tát your Python tệp tin or console:

It makes it easier to tát print all of your spreadsheet values by just calling print_rows().

Basic Spreadsheet Operations

Before you get into the more advanced topics, it’s good for you to tát know how to tát manage the most simple elements of a spreadsheet.

Freezing Rows and Columns

Something that you might want to tát vì thế when working with big spreadsheets is to tát freeze a few rows or columns, so sánh they remain visible when you scroll right or down.

Freezing data allows you to tát keep an eye on important rows or columns, regardless of where you scroll in the spreadsheet.

Again, openpyxl also has a way to tát accomplish this by using the worksheet freeze_panes attribute. For this example, go back to tát our sample.xlsx spreadsheet and try doing the following:

If you open the sample_frozen.xlsx spreadsheet in your favorite spreadsheet editor, you’ll notice that row 1 and columns A and B are frozen and are always visible no matter where you navigate within the spreadsheet.

Xem thêm: ăn hết giới giải trí

This feature is handy, for example, to tát keep headers within sight, so sánh you always know what each column represents.

Here’s how it looks in the editor:

Notice how you’re at the kết thúc of the spreadsheet, and yet, you can see both row 1 and columns A and B.

Adding Filters

You can use openpyxl to tát add filters and sorts to tát your spreadsheet. However, when you open the spreadsheet, the data won’t be rearranged according to tát these sorts and filters.

At first, this might seem lượt thích a pretty useless feature, but when you’re programmatically creating a spreadsheet that is going to tát be sent and used by somebody else, it’s still nice to tát at least create the filters and allow people to tát use it afterward.

The code below is an example of how you would add some filters to tát our existing sample.xlsx spreadsheet:

You should now see the filters created when opening the spreadsheet in your editor:

You don’t have to tát use sheet.dimensions if you know precisely which part of the spreadsheet you want to tát apply filters to tát.

Adding Formulas

Formulas (or formulae) are one of the most powerful features of spreadsheets.

They gives you the power to tát apply specific mathematical equations to tát a range of cells. Using formulas with openpyxl is as simple as editing the value of a cell.

You can see the list of formulas supported by openpyxl:

Let’s add some formulas to tát our sample.xlsx spreadsheet.

Starting with something easy, let’s kiểm tra the average star rating for the 99 reviews within the spreadsheet:

If you open the spreadsheet now and go to tát cell P2, you should see that its value is: 4.18181818181818. Have a look in the editor:

You can use the same methodology to tát add any formulas to tát your spreadsheet. For example, let’s count the number of reviews that had helpful votes:

You should get the number 21 on your P3 spreadsheet cell lượt thích so:

You’ll have to tát make sure that the strings within a formula are always in double quotes, so sánh you either have to tát use single quotes around the formula lượt thích in the example above or you’ll have to tát escape the double quotes inside the formula: "=COUNTIF(I2:I100, \">0\")".

There are a ton of other formulas you can add to tát your spreadsheet using the same procedure you tried above. Give it a go yourself!

Adding Styles

Even though styling a spreadsheet might not be something you would vì thế every day, it’s still good to tát know how to tát vì thế it.

Using openpyxl, you can apply multiple styling options to tát your spreadsheet, including fonts, borders, colors, and so sánh on. Have a look at the openpyxl documentation to tát learn more.

You can also choose to tát either apply a style directly to tát a cell or create a template and reuse it to tát apply styles to tát multiple cells.

Let’s start by having a look at simple cell styling, using our sample.xlsx again as the base spreadsheet:

If you open your spreadsheet now, you should see quite a few different styles on the first 5 cells of column A:

There you go. You got:

• A2 with the text in bold
• A3 with the text in red and bigger fonts size
• A4 with the text centered
• A5 with a square border around the text

You can also combine styles by simply adding them to tát the cell at the same time:

Have a look at cell A6 here:

When you want to tát apply multiple styles to tát one or several cells, you can use a NamedStyle class instead, which is lượt thích a style template that you can use over and over again. Have a look at the example below:

If you open the spreadsheet now, you should see that its first row is bold, the text is aligned to tát the center, and there’s a small bottom border! Have a look below:

As you saw above, there are many options when it comes to tát styling, and it depends on the use case, so sánh feel không tính tiền to tát kiểm tra openpyxl documentation and see what other things you can vì thế.

Conditional Formatting

This feature is one of my personal favorites when it comes to tát adding styles to tát a spreadsheet.

It’s a much more powerful approach to tát styling because it dynamically applies styles according to tát how the data in the spreadsheet changes.

In a nutshell, conditional formatting allows you to tát specify a list of styles to tát apply to tát a cell (or cell range) according to tát specific conditions.

For example, a widespread use case is to tát have a balance sheet where all the negative totals are in red, and the positive ones are in green. This formatting makes it much more efficient to tát spot good vs bad periods.

Without further ado, let’s pick our favorite spreadsheet—sample.xlsx—and add some conditional formatting.

You can start by adding a simple one that adds a red background to tát all reviews with less than thở 3 stars:

Now you’ll see all the reviews with a star rating below 3 marked with a red background:

Code-wise, the only things that are new here are the objects DifferentialStyle and Rule:

• DifferentialStyle is quite similar to tát NamedStyle, which you already saw above, and it’s used to tát aggregate multiple styles such as fonts, borders, alignment, and so sánh forth.
• Rule is responsible for selecting the cells and applying the styles if the cells match the rule’s logic.

Using a Rule object, you can create numerous conditional formatting scenarios.

However, for simplicity sake, the openpyxl package offers 3 built-in formats that make it easier to tát create a few common conditional formatting patterns. These built-ins are:

• ColorScale
• IconSet
• DataBar

The ColorScale gives you the ability to tát create color gradients:

Now you should see a color gradient on column H, from red to tát green, according to tát the star rating:

You can also add a third color and make two gradients instead:

This time, you’ll notice that star ratings between 1 and 3 have a gradient from red to tát yellow, and star ratings between 3 and 5 have a gradient from yellow to tát green:

The IconSet allows you to tát add an icon to tát the cell according to tát its value:

You’ll see a colored arrow next to tát the star rating. This arrow is red and points down when the value of the cell is 1 and, as the rating gets better, the arrow starts pointing up and becomes green:

The openpyxl package has a full list of other icons you can use, besides the arrow.

Finally, the DataBar allows you to tát create progress bars:

You’ll now see a green progress bar that gets fuller the closer the star rating is to tát the number 5:

As you can see, there are a lot of cool things you can vì thế with conditional formatting.

Here, you saw only a few examples of what you can achieve with it, but kiểm tra the openpyxl documentation to tát see a bunch of other options.

Adding Images

Even though images are not something that you’ll often see in a spreadsheet, it’s quite cool to tát be able to tát add them. Maybe you can use it for branding purposes or to tát make spreadsheets more personal.

To be able to tát load images to tát a spreadsheet using openpyxl, you’ll have to tát install Pillow:

Apart from that, you’ll also need an image. For this example, you can grab the Real Python logo below and convert it from .webp to tát .png using an online converter such as cloudconvert.com, save the final tệp tin as logo.png, and copy it to tát the root thư mục where you’re running your examples:

Afterward, this is the code you need to tát import that image into the hello_word.xlsx spreadsheet:

You have an image on your spreadsheet! Here it is:

The image’s left top corner is on the cell you chose, in this case, A3.

Adding Pretty Charts

Another powerful thing you can vì thế with spreadsheets is create an incredible variety of charts.

Charts are a great way to tát visualize and understand loads of data quickly. There are a lot of different chart types: bar chart, pie chart, line chart, and so sánh on. openpyxl has tư vấn for a lot of them.

Here, you’ll see only a couple of examples of charts because the theory behind it is the same for every single chart type:

For any chart you want to tát build, you’ll need to tát define the chart type: BarChart, LineChart, and so sánh forth, plus the data to tát be used for the chart, which is called Reference.

Before you can build your chart, you need to tát define what data you want to tát see represented in it. Sometimes, you can use the dataset as is, but other times you need to tát mas sa the data a bit to tát get additional information.

Let’s start by building a new workbook with some sample data:

Now you’re going to tát start by creating a bar chart that displays the total number of sales per product:

There you have it. Below, you can see a very straightforward bar chart showing the difference between online product sales online and in-store product sales:

Like with images, the top left corner of the chart is on the cell you added the chart to tát. In your case, it was on cell E2.

Try creating a line chart instead, changing the data a bit:

With the above code, you’ll be able to tát generate some random data regarding the sales of 3 different products across a whole year.

Once that’s done, you can very easily create a line chart with the following code:

Here’s the outcome of the above piece of code:

One thing to tát keep in mind here is the fact that you’re using from_rows=True when adding the data. This argument makes the chart plot row by row instead of column by column.

In your sample data, you see that each product has a row with 12 values (1 column per month). That’s why you use from_rows. If you don’t pass that argument, by mặc định, the chart tries to tát plot by column, and you’ll get a month-by-month comparison of sales.

Another difference that has to tát vì thế with the above argument change is the fact that our Reference now starts from the first column, min_col=1, instead of the second one. This change is needed because the chart now expects the first column to tát have the titles.

There are a couple of other things you can also change regarding the style of the chart. For example, you can add specific categories to tát the chart:

Add this piece of code before saving the workbook, and you should see the month names appearing instead of numbers:

Code-wise, this is a minimal change. But in terms of the readability of the spreadsheet, this makes it much easier for someone to tát open the spreadsheet and understand the chart straight away.

Another thing you can vì thế to tát improve the chart readability is to tát add an axis. You can vì thế it using the attributes x_axis and y_axis:

This will generate a spreadsheet lượt thích the below one:

As you can see, small changes lượt thích the above make reading your chart a much easier and quicker task.

There is also a way to tát style your chart by using Excel’s mặc định ChartStyle property. In this case, you have to tát choose a number between 1 and 48. Depending on your choice, the colors of your chart change as well:

With the style selected above, all lines have some shade of orange:

There is no clear documentation on what each style number looks lượt thích, but this spreadsheet has a few examples of the styles available.

There are a lot more chart types and customization you can apply, so sánh be sure to tát kiểm tra out the package documentation on this if you need some specific formatting.

Convert Python Classes to tát Excel Spreadsheet

You already saw how to tát convert an Excel spreadsheet’s data into Python classes, but now let’s vì thế the opposite.

Let’s imagine you have a database and are using some Object-Relational Mapping (ORM) to tát map DB objects into Python classes. Now, you want to tát export those same objects into a spreadsheet.

Let’s assume the following data classes to tát represent the data coming from your database regarding product sales:

Now, let’s generate some random data, assuming the above classes are stored in a db_classes.py file:

By running this piece of code, you should get 5 products with 5 months of sales with a random quantity of sales for each month.

Now, to tát convert this into a spreadsheet, you need to tát iterate over the data and append it to tát the spreadsheet:

That’s it. That should allow you to tát create a spreadsheet with some data coming from your database.

However, why not use some of that cool knowledge you gained recently to tát add a chart as well to tát display that data more visually?

All right, then you could probably vì thế something lượt thích this:

Now we’re talking! Here’s a spreadsheet generated from database objects and with a chart and everything:

That’s a great way for you to tát wrap up your new knowledge of charts!

Bonus: Working With Pandas

Even though you can use Pandas to tát handle Excel files, there are few things that you either can’t accomplish with Pandas or that you’d be better off just using openpyxl directly.

For example, some of the advantages of using openpyxl are the ability to tát easily customize your spreadsheet with styles, conditional formatting, and such.

But guess what, you don’t have to tát worry about picking. In fact, openpyxl has tư vấn for both converting data from a Pandas DataFrame into a workbook or the opposite, converting an openpyxl workbook into a Pandas DataFrame.

First things first, remember to tát install the pandas package:

Then, let’s create a sample DataFrame:

Now that you have some data, you can use .dataframe_to_rows() to tát convert it from a DataFrame into a worksheet:

You should see a spreadsheet that looks lượt thích this:

If you want to tát add the DataFrame’s index, you can change index=True, and it adds each row’s index into your spreadsheet.

On the other hand, if you want to tát convert a spreadsheet into a DataFrame, you can also vì thế it in a very straightforward way lượt thích so:

Alternatively, if you want to tát add the correct headers and use the review ID as the index, for example, then you can also vì thế it lượt thích this instead:

Using indexes and columns allows you to tát access data from your DataFrame easily:

There you go, whether you want to tát use openpyxl to tát prettify your Pandas dataset or use Pandas to tát vì thế some hardcore algebra, you now know how to tát switch between both packages.