Row vs Column: What is Difference Between Rows and Columns

This article explains the fundamental differences between Row vs Column with examples, including advantages, limitations, etc:

In the day-to-day world of business, data analysis is a routine task, integral to the successful operation of any business. While the terms ‘Row’ and ‘Column’ are alien to none, these two terms are often used interchangeably and can cause grave confusion for many.

If you are new to the world of Microsoft Excel and struggling to understand the difference between these two terms, this article is a must-read for you.

In this article, we will familiarize readers with rows and columns. We will also analyze the main points of difference between rows and columns.

Rows and columns form an integral part of tables (spreadsheets) used to store data.

Row vs Column

Every worksheet has a collection of cells spread out in grid patterns and are called rows and columns, respectively. It is in these cells where data is stored. Using rows and columns is most commonly seen in tables as a part of spreadsheets like in Microsoft Excel.

Let’s get started.

We will begin by analyzing these two components, namely -rows and columns individually. The first section of this article will discuss what are rows and columns, followed by the differences between them.

What are Rows

When data or data series is placed horizontally on a table (spreadsheet), we call it a Row. This data can be words, numbers, or objects. Rows can be defined as a horizontal layout of data running from left to right. With rows, data is arranged in a straight line and lies next to each other. It runs horizontally in a table and is represented by a number.

A worksheet can have a maximum of 1048576 rows. This can be understood with the help of some real-life examples. Imagine a situation when we see a group of dwelling units built next to each other.

Refer to the diagram below:

What are Columns

Columns can be defined as the vertical arrangement of data and run from the top of the table to the bottom of the table. A worksheet can have up to 16384 columns.

Column vs Row Excel

The diagram below shows a representation of rows and columns on a Microsoft Excel Worksheet:

To navigate to a particular cell on a worksheet, the ideal way is to talk about the row number and column letter. In the image above, if we want to look for the weight of Y, you need to look at cell D4 (which is the 4^th row and column D). It is important to notice here that we always use the column first, which is followed by the row number.

Navigation

Here are some shortcuts that one can use to navigate between rows and columns on a spreadsheet:

• To move from the first to the last row: If you are a Windows user, you can use the Control key + the down navigation arrow (hold the Ctrl+ down arrow) to move to the last row.
• To move to the last column: Use Ctrl+ Right directional key (arrow) to move to the last column.

Examples

Let us understand the concept of rows and columns, taking a few examples from everyday life.

When talking of rows, we can take the example of a cinema hall where the arrangement of chairs is in a horizontal line. It is referred to as a ‘ROW’. The row number mentioned on the ticket tells us which horizontal line is the seat.

A great example to understand columns is a newspaper. Some articles in the newspaper are written from the top of the page to the bottom of the page. They are referred to as Columns.

Rows vs Columns: A Comparison

The key differences are explained in the below comparison table:

Advantages

Here are some benefits of using rows and columns or tables in workbooks:

• It allows data and data sets to be consistent and uniform.
• It is easier to update data over a period of time by simply adding or deleting rows and columns.
• Data can be presented and analyzed professionally.
• Tables created can be named and make it easy to refer to them.
• In MS-Excel, one can add filters to data to segregate data.
• The use of various formulas makes data comparison and analysis quick and easy.

Limitations

Usually, there is an upper limit to the total number of rows are columns that can appear on a spreadsheet. This number is set by default.

Below are the limitations of some popular programs:

#1) Limitation in Google Sheets

A Google sheet limits the maximum number of cells to 5 million either in a single worksheet or in multiple sheets. This translates to the fact that in case the upper limit of 5 million cells (either rows or columns) is reached, it will not allow any additional cells.

Google sheets which limit the total number of columns to 18,278, however, allow unlimited rows. There is also no limit specified for the number of tabs however, this is dependent on the 5 million cell limit.

The default number of cells in a new worksheet is 26000, i.e. 100 rows and 26 columns. If this limit for rows and columns is followed, we can have a maximum of 192 worksheets.

2) Limitations in MS Excel

In the case of MS Excel, the worksheets have a maximum of 16,384 columns and 1048576 rows. The last column is represented as XFD and indicates column number 16384.

As the total number of letters in the Alphabet is 26, and columns are represented by letters, after the 26^th column (Column Z), the next column number is continued with the start of the letters again.

Reference =>> Excel specifications and limits

#3) Limitation of rows and columns in the database

MySQL limits columns at 4096 per table however, the effective maximum can possibly be less for a given table and depends on multiple factors like restrictions imposed by storage engines or the maximum row size as the total length of columns cannot be greater than the row size.

For instance, InnoDB limits columns at 1017 columns per table. For rows size, InnoDB sets the row size as less than half a page for 4kB,8KB, 16KB, and 32KB page size settings. Therefore, in case the page size is default 16KB, the maximum row size is a little less than 8KB.

While talking about rows, the MySQL table has an upper limit of 65,535 bytes for row size irrespective of the fact that the storage engine may be capable of containing larger rows.

Reference =>> Limits on Table Column Count

Column vs Row Oriented Database

So far, we have discussed columns and rows for MS Excel. However, let us now understand rows and columns in database tables.

In the case of relational databases, the organization of data is done in two ways:

• Row oriented
• Column-oriented (This is also referred to as Columnar or C-store)

To explain the difference between these two terms, let us consider the table below:

Row-oriented databases: In these databases, data is organized by the record. In other words, it organizes all the data related to a record next to each other. This also means that rows follow each other in an immediate sequence.

This method of data storage has been popular for a long and hence is also called ‘traditional’. The row-oriented database provides the benefits of efficient reading and writing of rows. Even the columns in a single row are stored together on the same page (considering the size of the row is smaller than the size of the page).

This layout gives a boost to performance when a query is run for multiple columns of a single row. This is a very common scenario in Online Transactional Processing (OLTP) applications. To name a few examples of common row-oriented databases, PostgreSQL and MySQL top the chart.

Suggested Reading =>> Comparison between PostgreSQL vs MySQL

The data in the above table will be represented as below in a row-oriented database:

Column-oriented databases: In columnar-oriented databases, every row of a column is placed next to other rows in that same column. In other words, data from each column is stored together on a disk. Since the columns are stored together, only those blocks which contain the required data are read and unnecessary data is skipped.

This makes it quicker and faster to access data. Column-oriented databases are the preferred choice when dealing with a high volume of data. The most common usage of column-oriented databases is for Online Analytical Processing (OLAP) applications. Some common examples are Amazon Redshift and BigQuery.

The below image shows columnar storage of data:

Row-oriented vs Column-oriented- Making a Choice

We have now come to the last section of the article, where we discuss an important question that may have struck you a few times while reading about rows and columns. We have been talking about rows, columns, data, databases, etc. however, how do you decide if the data must be stored in rows or in columns?

In other words, should the database be row-oriented or column-oriented?

Here is how this dilemma can be answered. Unarguably, one common need for all databases is that they should be fast. It is imperative to select the most appropriate database so that the queries run will respond with speed.

With a simple decision of changing how data is stored in the memory, a few types of queries can run faster, thereby impacting the performance of databases. As discussed earlier, the basic architecture of storage of data is different for row and column-oriented databases.

As the names suggest, column-oriented databases work on columns and have vertical partitions, while row-oriented databases work on rows where the partitions are horizontal. This choice can have a great impact on the performance of the query.

A columnar store is a better choice when the data that needs to be accessed is mostly saved in columns and there is no need to run a query for each field in the rows. On the contrary, if, in each row, many columns are needed to find out the relevant rows, a row-store is a better choice.

Columnar stores offer the benefit of more efficient partial reads. This is because the volume of data loaded is low since it reads only the relevant data and not the entire record. Columnar stores are relatively more recent as compared to row stores, thereby giving the term ‘traditional’ to row stores.

Frequently Asked Questions

Q #1) How to find rows and columns in a table?

Answer: The best way to find rows and columns is to look at the manner of arrangement. A vertical arrangement is a column and a horizontal arrangement is a row.

Q #2) Do rows come first or columns?

Answer: As a practice, the first to be listed are the rows followed by columns. For example, the term 3×4 (used for a matrix) means 3 rows and 4 columns.

Q #3) Is there a difference between a cell and a column?

Answer: Yes, the point of intersection of a row and column is called a ‘cell’. Each cell is recognized by its name, which has the column (corresponding letter of column-like A, B, C, etc.) followed by the row number (1,2,3, etc.).

Q #4) How many rows and columns can MS Excel handle?

Answer: MS Excel can have up to a maximum of 1,048,576 rows and 16384 columns.

Conclusion

In this article, we have discussed the two fundamental components of any table, namely rows and columns. While dealing with saving data or analysis of data, it is important to clearly understand the difference between rows and columns, as it lays the very foundation of data analysis.

Also Read =>> Top MS Excel Interview Questions

For the benefit of our readers, we have explained the basic concept of row and column, followed by examples.