It’s time to give your spreadsheet muscles a boost.
Excel Is Useful For Data Analysts
Many Data scientists and data analysts will often tell you to learn Python or R to break into the industry. But Microsoft Excel, the well-known spreadsheet application, is still popular – and can sometimes be better than programming languages for analysing data. A good Excel spreadsheet should take complex, raw data and convert it into a readable document that anybody in an organisation can understand. In this article, we will look at five essential Excel functions that all data analysts should know.
COUNTBLANK
Raw data can be messy, and sometimes it can include missing values, especially when this data is collected in the real world. In Python, we can use a method such as isna() to detect missing values. However, this is also possible with Excel using the COUNTBLANK function.
COUNTBLANK will count the number of blank cells in a given range.

The formula for this Excel function is:
=COUNTBLANK(range)
SUMIFS
One of the best-known and most basic Excel functions is the SUM function. Sometimes we may want to use SUM, but also exclude cells from our summation using a criterion. This is where SUMIFS comes in.
SUMIFS allows us to sum values in a given range, but only sums the values that match given criteria. As many criteria can be given to this function as desired.

The formula for this Excel function is:
=SUMIFS(sum_range, criteria_range1, criteria1, …)
RANK
The RANK function can be used to return the rank of a numerical value when compared to a list of other numerical values. Ranking can be very important in Data Analysis to know where a particular value would fall in an ordered array. There also exists a similar function known as PERCENTRANK which returns the ranking as a percentage of the dataset’s range.
It is important to note that if a value cannot be found in the given list or array, Excel will return a #N/A error. This is not true for PERCENTRANK.

The formula for this Excel function is:
=RANK(number, list)
VLOOKUP
VLOOKUP is one of the most important functions for any data analyst to know. It can be used to retrieve, or look up, data in a table that is organised vertically. This is incredibly useful as it can be used to automatically find data in another spreadsheet, as long as each row has an ID.
The ID column for the table must be the first column. The third parameter in the VLOOKUP function can then be used to refer to the column containing the data that you want to retrieve. It is important to note that this parameter is 1-based in Excel. This means that a value of 2 will get the 2nd column, and value of 3 will get the third column, and so on. This is different to list indexing in Python, which is 0-based.
The other two parameters in the VLOOKUP function refer to the lookup value (or the ID of the row you are retrieving) and the range of the table itself.

The formula for this Excel function is:
=VLOOKUP(lookup_value, table_array, col_index_number)
IFERROR
If you are presenting your Excel spreadsheets to other people in your business, then it can be useful to have default values in cells when errors occur in your functions. This can be particularly useful when other users do not understand the meaning of errors, or the value of the cell would be known if an error occurred in calculations (such as defaulting to 0).
The IFERROR function can do exactly that. This function simply takes two parameters, the first is the function, and the second is the default value if the function throws an error. If the function does not throw an error, then the value will be outputted as normal.

The formula for this Excel function is:
=IFERROR(value, value_if_error)
And there you have it! These are five essential functions that data scientists and data analysts should know for Microsoft Excel. Although you will need to know these five, remember that there are many more Excel functions to use – and there is usually one to get your job done.
VLOOKUP is one of the most notorious functions, asked about in job descriptions and interviews. Functions such as SUMIFS are incredibly common, and you can find them in almost all useful spreadsheets. In fact, all of the functions in this article are common in data analysis. Are there any other Excel functions that you believe are essential for data analysis? Share them below.