• Duplicate:

Duplicate the data from the cell above.

Ctrl + D fills and overwrites a cell with the contents of the cell above it.

• Transpose:

This will transform items in rows to be shown in columns instead, or vice versa.

To transpose a column to a row:

1. Select the data in the column
2. Select the cell you want the row to start
3. Right-click, choose paste special, select Transpose

• Trim:

Trim helps to remove the extra spaces in data.

TRIM can be useful in removing irregular spacing from imported data.

=TRIM()

• Pivot tables:

A powerful tool for calculating, summarizing, and analyzing data, it allows you to compare or find patterns and trends in data.

To access this function, select "Insert" in the Menu bar and select "Pivot Table."

• Stock market data:

You can get stock data in Excel.

1. Enter a list of stock ticker symbols.
2. Then select the cells and go to the Data tab
3. Then click the Stocks button within the Data Types group.

Excel will attempt to match each cell value to a company stock and fill in the data.

• Upper, lower, proper case:

=UPPER, Converts text to all uppercase

=LOWER, Converts text string to lowercase

=PROPER, Converts text to proper case

Excel Shortcut List

UNPOPULAR OPINION: Excel is still relevant for data analysis.

I am often asked by junior data analysts, “What is the purpose of learning Excel if they already know Python?”.

The truth is, Excel/Google Sheets are still widely used across most organizations. And if you are working with other people, sooner or later you will be asked to do some quick analysis in Excel.

Yes, even if your organization has Tableau/PowerBI, someone will still download report as CSV and do his own analysis.

If you are just starting your data analytics journey, I always recommend Excel as the first tool to learn.

It will help you to understand how tabular data works.

LOOKUPS are like JOINS in SQL;
VSTACK is UNION in SQL;
and FILTER, SORT, GROUPBY are similar to Python functions.

By learning Excel, you are setting a foundation for other tools.

Excel might not be the trendiest and coolest tool in data analytics, but it is versatile, accessible, and universal.