Pandas and NumPy connection - Mini Project: Build & Apply

Pandas and NumPy connection

📖 Scenario: You work in a small store that tracks daily sales data. You want to analyze the sales numbers using Python. You will use pandas to organize the data and numpy to perform calculations.

🎯 Goal: Create a pandas DataFrame from a numpy array of sales data, then calculate the average sales using numpy.

📋 What You'll Learn

Create a numpy array with exact sales data

Create a pandas DataFrame from the numpy array

Calculate the average sales using numpy

Print the average sales value

💡 Why This Matters

🌍 Real World

Stores and businesses often collect sales data daily. Using pandas and numpy together helps organize and analyze this data quickly.

💼 Career

Data analysts and scientists use pandas and numpy to clean, organize, and analyze data efficiently in many industries.

1

Create a numpy array with sales data

Create a numpy array called sales_data with these exact values: 100, 150, 200, 130, 170.

Pandas

# Your code here

Need a hint?

Use np.array([...]) to create the array with the exact numbers.

2

Create a pandas DataFrame from the numpy array

Import pandas as pd and create a DataFrame called df from the sales_data numpy array. Name the column 'Sales'.

Pandas

import numpy as np

sales_data = np.array([100, 150, 200, 130, 170])
# Your code here

Need a hint?

Use pd.DataFrame() with columns=['Sales'] to name the column.

3

Calculate the average sales using numpy

Create a variable called average_sales and set it to the mean of the 'Sales' column in df using numpy.

Pandas

import numpy as np
import pandas as pd

sales_data = np.array([100, 150, 200, 130, 170])
df = pd.DataFrame(sales_data, columns=['Sales'])
# Your code here

Need a hint?

Use np.mean() on the DataFrame column df['Sales'].

4

Print the average sales

Write a print statement to display the value of average_sales.

Pandas

import numpy as np
import pandas as pd

sales_data = np.array([100, 150, 200, 130, 170])
df = pd.DataFrame(sales_data, columns=['Sales'])
average_sales = np.mean(df['Sales'])
# Your code here

Need a hint?

Use print(average_sales) to show the result.