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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

Loading the DataLoading the Data

Welcome to the course! Here, you will work with the sales data from 45 stores of a retail chain. Let's begin by loading and previewing the data.

Remember to load the CSV file, use the .read_csv() method from the pandas library.

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

1. How many rows does the `df` dataset have?
2. How many columns does the `df` dataset have?

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How many rows does the df dataset have?

Select the correct answer

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How many columns does the df dataset have?

Select the correct answer

Everything was clear?

Section 1. Chapter 1
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