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Course Content

Analyzing and Visualizing Real-World Data

1. Preprocessing Data: Part I

Loading the DataData TypesAnalyzing Columns [1/4]Removing Characters: Method 1Removing Characters: Method 2Analyzing Columns [2/4]Replacing Characters

2. Preprocessing Data: Part II

Analyzing Columns [3/4]Removing and ReplacingAnalyzing Columns [4/4]Wrong Convertation?Proper ConvertingThat's All?

3. Analyzing Data

Superficial AnalysisThe Most Profitable StoreDate RangeHow Periodic the Data is?The Most Profitable PeriodsThe Best CombinationHolidays EffectWhat Holidays are we Considering?The Most Profitable Holiday

4. Visualizing Data

First Look at the DataComparing DynamicsFinding RelationDoes Temperature Affect?Or is it Holiday Effect?Comparing ShopsAdding Holidays to Comparison

Analyzing and Visualizing Real-World Data

Superficial AnalysisSuperficial Analysis

Welcome to the third section of the course! Here, you will use the pandas library to analyze data by answering specific questions.

Let's start with some basic information. We are going to analyze and visualize data on store sales. First, we need to determine how many stores we are working with. We can use the .describe() method of pandas to show the main descriptive statistics on numerical columns. Also, we can use the .unique() method of pandas to get only unique values of a certain column.

For the following question, feel free to edit the code above if necessary.

question-icon

What is the number of unique stores in the df dataframe?

Select the correct answer

Everything was clear?

Section 3. Chapter 1
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