Analyzing and Visualizing Real-World Data

Analyzing and Visualizing Real-World Data

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1. Preprocessing Data: Part I

First, let's get acquainted with the data we will be working with. Throughout this section, we will perform the initial set of actions to prepare the data for further analysis.

Loading the Data

Columns Overview

Removing Characters: Method 1

Removing Characters: Method 2

Checking Columns

Replacing Characters

2. Preprocessing Data: Part II

In the second section, we will continue with the preparatory tasks started in the first section and ensure the data is ready for further exploration.

Analyzing Columns

Removing and Replacing

Processing Dates

Wrong Convertation?

Proper Converting

3. Analyzing Data

After preparing the data, we will move on to some exploratory analysis. Throughout this section, we will answer several questions and uncover interesting insights.

Superficial Analysis

The Most Profitable Store

How Periodic the Data is?

The Most Profitable Periods

The Best Combination

Holidays Effect

What Holidays are we Considering?

The Most Profitable Holiday

4. Visualizing Data

In the last section, we will use visualization tools to either confirm or reject the hypotheses we made in the previous section. We will also create visualizations of key indicators for the entire dataset.

First Look at the Data

Comparing Dynamics

Finding Relation

Does Temperature Affect?

Or is it Holiday Effect?

Comparing Shops

Adding Holidays to Comparison

Adding Holidays to Comparison

As we can see, there are different shops in the dataset, and their revenues vary significantly - we have shops with total revenue of about 50 million, and at the same time shops with total revenue of more than 250 million. Let's see whether earnings differ depending on whether it is a holiday week or not.

Task

You are going to work with nearly the same code as in the previous task. You just need to modify certain things:

Group the values of the df DataFrame by 'Store', and then 'Holiday_Flag' column (the order is important). Then, after selecting the 'Weekly_Sales' column, compute the mean values.
Within the .barplot() function, set the parameter, so that there will be separate bars for each of the unique values of the 'Holiday_Flag' column.

Everything was clear?

Section 4. Chapter 7

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Course Content

Analyzing and Visualizing Real-World Data

Analyzing and Visualizing Real-World Data

Adding Holidays to Comparison

As we can see, there are different shops in the dataset, and their revenues vary significantly - we have shops with total revenue of about 50 million, and at the same time shops with total revenue of more than 250 million. Let's see whether earnings differ depending on whether it is a holiday week or not.

Task

You are going to work with nearly the same code as in the previous task. You just need to modify certain things:

Group the values of the df DataFrame by 'Store', and then 'Holiday_Flag' column (the order is important). Then, after selecting the 'Weekly_Sales' column, compute the mean values.
Within the .barplot() function, set the parameter, so that there will be separate bars for each of the unique values of the 'Holiday_Flag' column.

Everything was clear?

Section 4. Chapter 7

toggle bottom row

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