How to Use Excel's VAR Function in Pandas

The Excel VAR function calculates the variance of a supplied set of values. It's commonly used to measure the spread of a data set, which is helpful when analyzing financial returns data, scientific data, etc.

Implementing the Variance function in Pandas#

In Python's pandas library, the VAR function can be used in various ways, similar to Excel but with more flexibility. Here's how to achieve similar functionality:

Calcualte the variance of a single pandas DataFrame column#

To apply VAR to a single column in pandas, simply select the column and apply the built in `var` method. This is akin to writing the Excel formula, =VAR(A:A)

# Calculate the variance of column A
var_value = df['A'].var()

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Calculate the variance of multiple columns in a pandas DataFrame#

Just like in Excel how you can write the formula, =VAR(A:A, B:B), you can apply the `var` method to multiple columns in pandas.

To do so, use the following code:

# Calculate the variance of columns A and B
var_values = df[['Column1', 'Column2']].var()

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Common mistakes when using VAR in Python#

While using the VAR function in pandas, certain common pitfalls can lead to incorrect results or errors. Here are a few to be aware of:

Incorrect Data Type#

Calculating the variance on columns with non-numeric data will result in errors. It's crucial to ensure that the data types are consistent and appropriate for the `var` operation.

To do so, convert the data to a numeric format using pd.to_numeric() if necessary, and handle any non-numeric values beforehand.

# Convert Column1 to numeric
df['Column1'] = pd.to_numeric(df['Column1'], errors='coerce')

# Calculate the variance of Column1
var_value = df['Column1'].var()

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Understanding the Variance Formula in Excel#

Variance is a measure of how spread out a data set is. The variance is calculated as the average squared deviation of each number from its mean. The result is always positive, as the deviations are first squared.

=VAR(A1:A10)

VAR Excel Syntax

Examples