Various operations

Calculations help us transform the dataset for purposes of the intended analysis.

In this section, you’ll learn how to use Python to calculate key summary statistics and perform simple arithmetic operations on your dataset.

Sum, mean, and median

Excel

In Excel, you use functions like =SUM(), =AVERAGE(), and =MEDIAN() to summarize a column.

t0 Prompt

What is the total amount?

Show me the average transaction size

Calculate the median transaction value

Code

The python code looks as follows:

transactions["Amount"] = pd.to_numeric(transactions["Amount"])
total = transactions["Amount"].sum()
average = transactions["Amount"].mean()
median = transactions["Amount"].median()
print(total, average, median)

Min, max, and quartiles

Excel

In Excel, you use =MIN(), =MAX(), or =QUARTILE() to understand the spread of your data.

t0 Prompt

What is the smallest transaction?

Show the quartiles of the amount column

Give me the maximum value under Amount column

Code

The python code looks as follows:

transactions["Amount"] = pd.to_numeric(transactions["Amount"])
minimum = transactions["Amount"].min()
q1 = transactions["Amount"].quantile(0.25)
q2 = transactions["Amount"].median()
q3 = transactions["Amount"].quantile(0.75)
maximum = transactions["Amount"].max()
print(minimum, q1, q2, q3, maximum)

Multiply, divide, subtract, or add values

Excel

In Excel, you use formulas like =A1*0.1 or =A1-B1 to calculate taxes, net income, or margins.

t0 Prompt

Add 10% adjustment to all transactions

Divide amount by 1 million

Subtract 500,000 from each value under Amount column

Code

The python code looks as follows:

transactions["Amount"] = pd.to_numeric(transactions["Amount"])
transactions["With Tax"] = transactions["Amount"] * 1.10
transactions["Net"] = transactions["Amount"] - 500_000
transactions["Amount (in millions)"] = transactions["Amount"] / 1_000_000
transactions