Exploring DataFrames: Uncovering Insights from Top 30 US Fast Food Chains
Exploring DataFrames: Uncovering Insights from Top 30 US Fast Food Chains Data Science Project
Intro to Pandas for Data Analysis

Exploring DataFrames: Uncovering Insights from Top 30 US Fast Food Chains

In this project, we will delve into the basics of DataFrames by analyzing a dataset of the top 30 fast food chains in the United States. Your objective will be to understand the shape and structure of the data, utilizing various DataFrame operations to perform statistical analysis and gain insights into sales figures and locations.
Start this project
Exploring DataFrames: Uncovering Insights from Top 30 US Fast Food ChainsExploring DataFrames: Uncovering Insights from Top 30 US Fast Food Chains
Project Created by

Vidhi Shah

Project Activities

All our Data Science projects include bite-sized activities to test your knowledge and practice in an environment with constant feedback.

All our activities include solutions with explanations on how they work and why we chose them.

multiplechoice

What is the primary difference between the `df.info()` and `df.describe()` methods in pandas?

multiplechoice

What is the data type of the `Rank` column?

multiplechoice

Which of these columns contain numeric data?

multiplechoice

What is the shape of our DataFrame `df`?

codevalidated

Select the Sales Column.

Select the Sales (U.S., 2017) column and store it in a variable called sales.

codevalidated

Display Top Three Chains

Display the top 3 chains by rank.

Store your result in a variable called top_3_chains.

Your result should match the following output :

img6

input

Identify the 5th Ranking Fast Food Chain

Using .loc[] method find out the name of the fast food chain ranked 5th in the dataset.

input

How many chains have more than `'5000'` locations?

codevalidated

Analyse Sales Distribution Across Food Chains

Using the Sales (U.S., 2017) find out what is the median number of sales across all food chains?

Store your result in median_sales variable.

multiplechoice

If you want to select the third row from a DataFrame `df`, which of the following would be the correct way to do it?

Exploring DataFrames: Uncovering Insights from Top 30 US Fast Food ChainsExploring DataFrames: Uncovering Insights from Top 30 US Fast Food Chains
Project Created by

Vidhi Shah

This project is part of

Intro to Pandas for Data Analysis

Explore other projects