How can i read an excel file

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Want to know about apps to open excel files? This article will provide all the necessary information. Excel is a pivotal tool for almost all spheres of life. It is used by everyone who wishes to keep their data in an organized and easy-to-access manner.

But there’s catch to this, you can’t access the excel smoothly on your mobile right? Here’s the solution. Tap the blue button below and explore the easiest excel on your mobile.

Check out the screenshot of Lio App – easy excel sheet on your mobile.

There are several apps that are available today to open excel files. For example, Lio makes your task of calculating and keeping track of things very simple and completely hassle-free. Let’s look at it in detail along with other apps.

THE TOP PICKS OF APPS TO OPEN EXCEL DOCUMENTS

Lio

If you are looking for an easy app to keep a track of your things, then Lio is the answer. The amazing application is made for anybody and everybody under the sky. Whether you are a business owner, shop owner, taxi driver, teacher, student or anyone else, Lio can help you get more organised.

The app offers many templates that one can select based on their needs and requirements. You can share the file with others and work with different people on the same file and see real-time changes. You can also upload images and add them to these files to better manage your task.

AndrOpen Office

AndrOpen Office is a legit Open Office Software. It offers a tonne of features. It is a cellular port OpenOffice System. It has a phrase processor as well as a presentation function. The main feature is the spreadsheet. The app even lets you draw and even do calculations on the page. 

Considering the functionality of the spreadsheet. It is a great cellular app and offers decent competition to favourably the biggest players in the show even if it doesn’t have all the functionality features of the others.

The process of importing Microsoft Excel files in XLS or XLT format is fairly simple. It is a brilliant chance for Google and Microsoft solutions. Access to the app is free

OfficeSuite

OfficeSuite is a tough competitor. It gives intense competition to Google Drive and Microsoft Office on Mobile. It has been around for a long time and incorporates a variety of functions and features. This provides a complete workplace experience. The spreadsheet functionality is also great and has tutorials for assistance with Excel documents and more. 

It is pretty easy to use, and is fairly good enough as the loose model makes it a bit dry in terms of functionality. The app comes with a subscription fee. It is charged every month. It is about 5 dollars every month. You can take an annual subscription for 30 dollars to save some money. The premium subscription completely removes ads and provides preset report formats and offers access to an extra set of functions. The office suite app has about 154 report formats.

The information is applicable for both Android, iOS, or PC. The app uses the same license across all platforms. Once you take the subscription, the app can be used on any device 

Irrespective of the operating system.

SmartOffice

The SmartOffice is a long-term player in the field. Considering the competition the app seems to be a bit mature in terms of functionality. The app has a long list of features and capabilities. The spreadsheet functionality is also quite good. However, the app is not as effective as many of its rivals. It is completely loose which ensures you get enough for the money you paid.

Nowadays, Excel apps in terms of usability have fared far better than SmartOffice. Google Sheets is one of the best among them. But if you are a person who does a lot of offline editing then this software is a great pick for you.

It utilizes Google Drive and Dropbox as a means to store the data. Both of them act as a cloud garage. Since the method is not as effective, people have moved to different apps. However, a few long term users are still using SmartOffice. They enjoy using it.

Google Sheets

A time was there when creating excel sheets was a tussle. It always involved sitting down at a desk to make a spreadsheet. However, with the introduction of Google sheets making spreadsheets has never been easier. You can create and modify sheets using your mobile. How more compact should it get.

Google Sheets, sync with Google Drive, and the app could be used across platforms along with the web. The files work well with Microsoft Office and provide the same functionality as the trusted Microsoft excel. Moreover, the app automatically saves each modification you make. 

The app incorporates a collaborative function where multiple people can create and modify the same spreadsheet. Offers loads of customization features and capabilities. Many consider that microsoft excel is the king of spreadsheet software but Google Shees does it graeter and better. The App has a short learning curve and could be mastered even by a newbie

There is no subscription as such. All functionalities can be used for free unless your it stays within your drive space of 15GB. If you want more drive space then you have to pay for it.

WPS Office

We can say it is a great workplace app. It is frequently used by people. The app can be used free of charge but you need to deal with a lot of annoying ads. I mean a lot. To unlock the full functionality and get rid of the ads you have to pay for a subscription. You will do so because you dont want ads annoying especially when you are up doing something productive.

With respect to functionality, It has a list of functions that help access Microsoft Excel. It also has some extra gimmicks for Slack, Zoom and Google drive. This makes the app good as it integrates the functionality of storage and ease of use during online meetings. All the proceedings received by the app are used for marketing the app outside and within a loose version.

Quip

Quip is well developed excel software. An ideal alternative for google groups. The app has all the capabilities needed for a workspace. However, it requires a subscription to be purchased. The app can be used to edit a document with a group of people. The app also allows you to coordinate with other members using the chat feature that is inbuilt.

Possess as many as 400 features for the spreadsheets. The app can be used to include spreadsheets within any document. The subscription plans primarily focus on group users. But can be utilized for non-public use as well.

Docs To Go

Docs to Go is a relatively good option for use in a workspace. It has all the basic features of a phrase processor, a worksheet and a shows function. The spreadsheet function is ideal for running all Microsoft Office files and offers a lot of customization. This feature makes it ideal for less difficult tasks. It has 111 unique functions and a number of customization for columns and sorting.

The app finds it difficult to handle difficult, complex styling imported from different apps. If the easy ones are used, the app works fairly well

It boasts one hundred and eleven unique functions, numerous column customization, and sorting.

How to Open XLS Files

XLS is the specified format for any kind of Microsoft Excel document. This file format is supported by all spreadsheet apps and works quite well to examine documents.

If you are constantly on a run and want to edit your spreadsheet then and where you are comfortable. You can get this done through Google Sheets. The modified data will be synced across all devices with the same user account and stored in Google drive. You can use any app mentioned above to modify the XLS documents on your device

Your choice of the right app depends on whether you want your data saved on one device or should be synced across all devices. The benefit of having data synced is that you can modify the data on any device. You can choose based on the software and device you use to work on your files.

All the apps mentioned in the article is compatible with mobile phone and could be opened when and edited whenever needed.

Google Drive

1. Upload your spreadsheet to Google Drive from your pc. The old cellular model is not available anymore and will not assist in adding documents outside your device

2. Using the phone’s search engine go to Google Drive using the link drive.google.com.You will be taken to the cellular model page. If you want you can switch to the Web app model in Google drive.

3. Once the upload is complete Open the spreadsheet. You can view the spreadsheet and edit the contents once you have it uploaded

Documents To Go

1. Install the Docs to Go app from App Store for Apple devices or Google Playstore for your android phone. This App comes pre-installed with Blackberry devices. The App requires a subscription to be purchased. The fees depend on the device you use
2. Now launch the App. If you have the XLS document as an email attachment you can click on the attachment and select open with Docs to Go App. This will automatically
3. Sync your phone with a PC using a USB to duplicate the files on pc to your phone. This ensures a backup for your XLS files

Also Read: Making Attendance Sheets In Excel For Employees/Students

Spreadsheet For IOS

1. Install the spreadsheet app on your iPhone and launch the app on your Pc
2. Select the settings icon and appears like a gear and slide the On button after you enable the file sharing option. At the lowest part of the screen, you can see an IP deal which you should hook up with the application
3. Enter the IP address using your web browser from your PC. Your phone should be linked with the identical community as your pc
4. Select the document to download out of your phone, or add a new XLS document. This way, you can sync dat using the IP address

First, you need to install Spreadsheet to your iPhone or a different iOS tool and open it to your pc.

Mention the current file extensions?

Format	Extensions
Excel Workbook	.xlxs
Excel add-in	.xlam
Excel Macro enabled Template	.xltm
Excel Binary Workbook	.xlxb
Excel Macro enabled Workbook	.xlxm

LIST THE STEPS TO DISPLAY EXCEL FILES IN AN APP

Step 1: Click on an info source. The app mainly consists of the information on the Excel file, Google sheet etc. It may also contain sales force, Microsoft dynamics CRM and plenty more

Step 2: Select applicable enter and output cells.

Step 3: Choose a layout for your calculation app.

Step 4: Share the App.

Also Read: In-Depth Look At Spreadsheets VS Database

How Does Lio help?

Lio is a useful application that helps in maintaining records in the form of tables and spreadsheets.

It helps to record the activities, which are easily accessible 24/7. Various templates are provided for specified purposes which are handy to use for anyone.

The mobile integrated app is convenient and the users find it not so difficult to use. It is one of the best for managing inventory, ordering, and holding it to be available for the right time.

Not downloaded the Lio App yet? Here is how you can start with Lio App.

Step 1: Select the Language you want to work on. Lio for Android

Step 2: Create your account using your Phone Number or Email Id.

Verify the OTP and you are good to go.

Step 3: Select a template in which you want to add your data.

Add your Data with our Free Cloud Storage.

Step 4: All Done? Share and Collaborate with your contacts.

Frequently Asked Questions

Conclusion

It is the best way to store the information in a way that when you share it, others can access it easily. The purpose of getting information is to examine and to get insights out of it. Excel has a number of the maximum effective gear to examine data.

When you’ve got facts with lots of rows, you may insert a pivot desk out of that information and create a precise desk. You can also obtain free templates that you can download and create as well.

The system of cleansing and remodelling statistics takes a long time and it may be a tedious system.

For this, Microsoft has delivered the energy question: a statistics transformation and cleansing engine. You may load statistics from a couple of sources, and remodel them, after which the load is returned to the worksheet. I hope this article is beneficial to you and you have learnt all about apps to open excel files.

Microsoft Excel is one of the most powerful spreadsheet software applications in the world, and it has become critical in all business processes. Companies across the world, both big and small, are using Microsoft Excel to store, organize, analyze, and visualize data.

As a data professional, when you combine Python with Excel, you create a unique data analysis bundle that unlocks the value of the enterprise data.

In this tutorial, we’re going to learn how to read and work with Excel files in Python.

After you finish this tutorial, you’ll understand the following:

• Loading Excel spreadsheets into pandas DataFrames
• Working with an Excel workbook with multiple spreadsheets
• Combining multiple spreadsheets
• Reading Excel files using the xlrd package

In this tutorial, we assume you know the fundamentals of pandas DataFrames. If you aren’t familiar with the pandas library, you might like to try our Pandas and NumPy Fundamentals – Dataquest.

Let’s dive in.

Reading Spreadsheets with Pandas

Technically, multiple packages allow us to work with Excel files in Python. However, in this tutorial, we’ll use pandas and xlrd libraries to interact with Excel workbooks. Essentially, you can think of a pandas DataFrame as a spreadsheet with rows and columns stored in Series objects. Traversability of Series as iterable objects allows us to grab specific data easily. Once we load an Excel workbook into a pandas DataFrame, we can perform any kind of data analysis on the data.

Before we proceed to the next step, let’s first download the following spreadsheet:

Sales Data Excel Workbook — xlsx ver.

The Excel workbook consists of two sheets that contain stationery sales data for 2020 and 2021.

---

NOTE

Although Excel spreadsheets can contain formula and also support formatting, pandas only imports Excel spreadsheets as flat files, and it doesn’t support spreadsheet formatting.

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To import the Excel spreadsheet into a pandas DataFrame, first, we need to import the pandas package and then use the read_excel() method:

import pandas as pd
df = pd.read_excel('sales_data.xlsx')

display(df)

If you want to load only a limited number of rows into the DataFrame, you can specify the number of rows using the nrows argument:

df = pd.read_excel('sales_data.xlsx', nrows=5)
display(df)

Skipping a specific number of rows from the begining of a spreadsheet or skipping over a list of particular rows is available through the skiprows argument, as follows:

df = pd.read_excel('sales_data.xlsx', skiprows=range(5))
display(df)

The code above skips the first five rows and returns the rest of the data. Instead, the following code returns all the rows except for those with the mentioned indices:

df = pd.read_excel('sales_data.xlsx', skiprows=[1, 4,7,10])
display(df)

Another useful argument is usecols, which allows us to select spreadsheet columns with their letters, names, or positional numbers. Let’s see how it works:

df = pd.read_excel('sales_data.xlsx', usecols='A:C,G')
display(df)

In the code above, the string assigned to the usecols argument contains a range of columns with : plus column G separated by a comma. Also, we’re able to provide a list of column names and assign it to the usecols argument, as follows:

df = pd.read_excel('sales_data.xlsx', usecols=['OrderDate', 'Region', 'Rep', 'Total'])
display(df)

The usecols argument accepts a list of column numbers, too. The following code shows how we can pick up specific columns using their indices:

df = pd.read_excel('sales_data.xlsx', usecols=[0, 1, 2, 6])
display(df)

Working with Multiple Spreadsheets

Excel files or workbooks usually contain more than one spreadsheet. The pandas library allows us to load data from a specific sheet or combine multiple spreadsheets into a single DataFrame. In this section, we’ll explore how to use these valuable capabilities.

By default, the read_excel() method reads the first Excel sheet with the index 0. However, we can choose the other sheets by assigning a particular sheet name, sheet index, or even a list of sheet names or indices to the sheet_name argument. Let’s try it:

df = pd.read_excel('sales_data.xlsx', sheet_name='2021')
display(df)

The code above reads the second spreadsheet in the workbook, whose name is 2021. As mentioned before, we also can assign a sheet position number (zero-indexed) to the sheet_name argument. Let’s see how it works:

df = pd.read_excel('sales_data.xlsx', sheet_name=1)
display(df)

As you can see, both statements take in either the actual sheet name or sheet index to return the same result.

Sometimes, we want to import all the spreadsheets stored in an Excel file into pandas DataFrames simultaneously. The good news is that the read_excel() method provides this feature for us. In order to do this, we can assign a list of sheet names or their indices to the sheet_name argument. But there is a much easier way to do the same: to assign None to the sheet_name argument. Let’s try it:

all_sheets = pd.read_excel('sales_data.xlsx', sheet_name=None)

Before exploring the data stored in the all_sheets variable, let’s check its data type:

type(all_sheets)

dict

As you can see, the variable is a dictionary. Now, let’s reveal what is stored in this dictionary:

for key, value in all_sheets.items():
    print(key, type(value))

2020 <class 'pandas.core.frame.DataFrame'>
2021 <class 'pandas.core.frame.DataFrame'>

The code above shows that the dictionary’s keys are the Excel workbook sheet names, and its values are pandas DataFrames for each spreadsheet. To print out the content of the dictionary, we can use the following code:

for key, value in all_sheets.items():
    print(key)
    display(value)

2020

2021

Combining Multiple Excel Spreadsheets into a Single Pandas DataFrame

Having one DataFrame per sheet allows us to have different columns or content in different sheets.

But what if we prefer to store all the spreadsheets’ data in a single DataFrame? In this tutorial, the workbook spreadsheets have the same columns, so we can combine them with the concat() method of pandas.

If you run the code below, you’ll see that the two DataFrames stored in the dictionary are concatenated:

combined_df = pd.concat(all_sheets.values(), ignore_index=True)
display(combined_df)

Now the data stored in the combined_df DataFrame is ready for further processing or visualization. In the following piece of code, we’re going to create a simple bar chart that shows the total sales amount made by each representative. Let’s run it and see the output plot:

total_sales_amount = combined_df.groupby('Rep').Total.sum()
total_sales_amount.plot.bar(figsize=(10, 6))

Reading Excel Files Using xlrd

Although importing data into a pandas DataFrame is much more common, another helpful package for reading Excel files in Python is xlrd. In this section, we’re going to scratch the surface of how to read Excel spreadsheets using this package.

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NOTE

The xlrd package doesn’t support xlsx files due to a potential security vulnerability. So, we use the xls version of the sales data. You can download the xls version from the link below:
Sales Data Excel Workbook — xls ver.

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Let’s see how it works:

import xlrd
excel_workbook = xlrd.open_workbook('sales_data.xls')

Above, the first line imports the xlrd package, then the open_workbook method reads the sales_data.xls file.

We can also open an individual sheet containing the actual data. There are two ways to do so: opening a sheet by index or by name. Let’s open the first sheet by index and the second one by name:

excel_worksheet_2020 = excel_workbook.sheet_by_index(0)
excel_worksheet_2021 = excel_workbook.sheet_by_name('2021')

Now, let’s see how we can print a cell value. The xlrd package provides a method called cell_value() that takes in two arguments: the cell’s row index and column index. Let’s explore it:

print(excel_worksheet_2020.cell_value(1, 3))

Pencil

We can see that the cell_value function returned the value of the cell at row index 1 (the 2nd row) and column index 3 (the 4th column).

The xlrd package provides two helpful properties: nrows and ncols, returning the number of nonempty spreadsheet’s rows and columns respectively:

print('Columns#:', excel_worksheet_2020.ncols)
print('Rows#:', excel_worksheet_2020.nrows)

Columns#: 8
Rows#: 13

Knowing the number of nonempty rows and columns in a spreadsheet helps us with iterating over the data using nested for loops. This makes all the Excel sheet data accessible via the cell_value() method.

Conclusion

This tutorial discussed how to load Excel spreadsheets into pandas DataFrames, work with multiple Excel sheets, and combine them into a single pandas DataFrame. We also explored the main aspects of the xlrd package as one of the simplest tools for accessing the Excel spreadsheets data.

In this brief Python tutorial, we will learn how to read Excel (xlsx) files using Python. Specifically, we will read xlsx files in Python using the Python module openpyxl. First, we start by the simplest example of reading a xlsx file in Python. Second, we will learn how to read multiple Excel files using Python.

In previous posts, we have learned how to use Pandas read_excel method to import xlsx files with Python. As previously mentioned, however, we will use another package called openpyxl in this post. In the next paragraph, we will learn how to install openpyxl.

Openpyxl Syntax

Basically, here’s the simplest form of using openpyxl for reading a xlsx file in Python:

import openpyxl
from pathlib import Path

xlsx_file = Path('SimData', 'play_data.xlsx')
wb_obj = openpyxl.load_workbook(xlsx_file) 

# Read the active sheet:
sheet = wb_obj.activeCode language: Python (python)

It is, of course, also possible to learn how to read, write, and append to files in Python (e.g., text files). Make sure to check that post out, as well.

Prerequisites: Python and Openpyxl

Now, before we will learn what Openpyxl is, we need to make sure that we have both Python 3 and the module openpyxl installed. One easy way to install Python is to download a Python distribution such as Anaconda or ActivePython. Openpyxl, on the other hand, can, as with many Python packages, be installed using both pip and conda. Now, using pip we type the following in a command prompt or terminal window, pip install openpyxl and using conda we type this; conda install openpyxl. Note, sometimes when we are installing Python packages with pip, we may notice that we don’t have the latest version of pip. Luckily, it is quite easy to upgrade pip to the latest version using pip.

What is the use of Openpyxl in Python?

Openpyxl is a Python module that can read and write Excel (with extension xlsx/xlsm/xltx/xltm) files. Furthermore, this module enables a Python script to modify Excel files. For instance, if we want to go through thousands of rows but just read specific data points and make small changes to these points, we can do this based on some criteria with openpyxl.

How do I read an Excel (xlsx) File in Python?

Now, the general method for reading xlsx files in Python (with openpyxl) is to import openpyxl (import openpyxl) and then read the workbook: wb = openpyxl.load_workbook(PATH_TO_EXCEL_FILE). In this post, we will learn more about this, of course.

How to Read an Excel (xlsx) File in Python

Now, in this section, we will be reading an xlsx file in Python using openpyxl. In a previous section, we have already been familiarized with the general template (syntax) for reading an Excel file using openpyxl and we will now get into this module in more detail. Note we will also work with the Path method from the Pathlib module.

1. Import the Needed Modules

In the first step, to reading an xlsx file in Python, we need to import the modules we need. That is, we will import Path and openpyxl:

import openpyxl
from pathlib import PathCode language: Python (python)

2. Setting the Path to the Excel (xlsx) File

In the second step, we will create a variable using Path. Furthermore, this variable will point at the location and filename of the Excel file we want to import with Python:

# Setting the path to the xlsx file:
xlsx_file = Path('SimData', 'play_data.xlsx')</code></pre>Code language: Python (python)

Note, “SimData” is a subdirectory to that of the Python script (or notebook). That is, if we were to store the Excel file in a completely different directory, we need to put in the full path. For example, xlsx_file = Path(Path.home(), 'Documents', 'SimData', 'play_data.xlsx')if the data is stored in the Documents in our home directory.

3. Read the Excel File (Workbook)

In the third step, we are going to use Python to read the xlsx file. Now, we are using the load_workbook() method:

wb_obj = openpyxl.load_workbook(xlsx_file)Code language: Python (python)

4. Read the Active Sheet from the Excel file

Now, in the fourth step, we are going to read the active sheet using the active method:

sheet = wb_obj.activeCode language: Python (python)

Note, if we know the sheet name we can also use this to read the sheet we want: play_data = wb_obj['play_data']

5. Work or Manipulate the Excel Sheet

In the final and fifth steps, we can work or manipulate the Excel sheet we have imported with Python. For example, if we want to get the value from a specific cell, we can do as follows:

print(sheet["C2"].value)Code language: Python (python)

Another example of what we can do with the spreadsheet in Python is we can iterate through the rows and print them:

for row in sheet.iter_rows(max_row=6):
    for cell in row:
        print(cell.value, end=" ")
    print()Code language: Python (python)

Note that we used the max_row and set it to 6 to print the six first rows from the Excel file.

6. Bonus: Determining the Number of Rows and Columns in the Excel File

In the sixth, and bonus step, we are going to find out how many rows and columns we have in the example Excel file we have imported with Python:

print(sheet.max_row, sheet.max_column)Code language: Python (python)

Reading an Excel (xlsx) File to a Python Dictionary

Now, before we learn how to read multiple xlsx files, we will import data from Excel into a Python dictionary. It’s quite simple, but for the example below, we need to know the column names before we start. If we want to find out the column names, we can run the following code (or open the Excel file):

import openpyxl
from pathlib import Path

xlsx_file = Path('SimData', 'play_data.xlsx')
wb_obj = openpyxl.load_workbook(xlsx_file)
sheet = wb_obj.active

col_names = []
for column in sheet.iter_cols(1, sheet.max_column):
    col_names.append(column[0].value)
   
    
print(col_names)Code language: Python (python)

Creating a Dictionary from an Excel File

In this section, we will finally read the Excel file using Python and create a dictionary.

data = {}

for i, row in enumerate(sheet.iter_rows(values_only=True)):
    if i == 0:
        data[row[1]] = []
        data[row[2]] = []
        data[row[3]] = []
        data[row[4]] = []
        data[row[5]] = []
        data[row[6]] = []

    else:
        data['Subject ID'].append(row[1])
        data['First Name'].append(row[2])
        data['Day'].append(row[3])
        data['Age'].append(row[4])
        data['RT'].append(row[5])
        data['Gender'].append(row[6])Code language: Python (python)

Now, let’s walk through the code example above. First, we create a Python dictionary (data). Second, we loop through each row (using iter_rows), and we only go through the rows where there are values. Second, we have an if statement where we check if it’s the first row and add the keys to the dictionary. That is, we set the column names as keys. Third, we append the data to each key (column name) in the other statement.

How to Read Multiple Excel (xlsx) Files in Python

In this section, we will learn how to read multiple xlsx files in Python using openpyxl. Additionally to openpyxl and Path, we are also going to work with the os module.

1. Import the Modules

In the first step, we are going to import the modules Path, glob, and openpyxl:

import glob
import openpyxl
from pathlib import PathCode language: Python (python)

2. Read all xlsx Files in the Directory to a List

Second, we will read all the .xlsx files in a subdirectory into a list. Now, we use the glob module together with Path:

xlsx_files = [path for path in Path('XLSX_FILES').rglob('*.xlsx')]Code language: Python (python)

3. Create Workbook Objects (i.e., read the xlsx files)

Third, we can now read all the xlsx files using Python. Again, we will use the load_workbook method. However, this time we will loop through each file we found in the subdirectory,

wbs = [openpyxl.load_workbook(wb) for wb in xlsx_files]Code language: Python (python)

Now, in the code examples above, we are using Python list comprehension (twice, in both step 2 and 3). First, we create a list of all the xlsx files in the “XLSX_FILES” directory. Second, we loop through this list and create a list of workbooks. Of course, we could add this to the first line of code above.

4. Work with the Imported Excel Files

In the fourth step, we can now work with the imported excel files. For example, we can get the first file by adding “[0]” to the list. If we want to know the sheet names of this file we do like this:wbs[0].sheetnames . Many of the things we can do, and have done in the previous example on reading xlsx files in Python, can be done when we’ve read multiple Excel files.

Notice this is one great example of how to use this programming language. Other examples are, for instance, to use it for renaming files in Python.

Conclusion: Reading Excel (xlsx) Files in Python

In conclusion, Openpyxl is a powerful Python library that enables developers to read, write, and manipulate Excel files using Python. This tutorial covered how to read an Excel (xlsx) file in Python using Openpyxl. We started by importing the necessary modules, setting the path to the Excel file, and then reading the file and its active sheet. We then explored how to work with the sheet and even determine the number of rows and columns in the file.

Moreover, we also learned how to read an Excel file to a Python dictionary and create a dictionary from an Excel file. Finally, we learned how to read multiple Excel files in a directory by importing the required modules, reading all the xlsx files in the directory to a list, creating workbook objects, and working with the imported Excel files.

By mastering these techniques, you can easily read and manipulate Excel files using Python, which can be incredibly useful in various data processing applications. So go ahead, try it out, and unlock the full potential of Openpyxl in your Python projects!

It is, of course, possible to import data from various other file formats. For instance, read the post about parsing json files in Python to learn more about reading JSON files.