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Analyzing and Visualizing Real-World Data
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Course Content

Analyzing and Visualizing Real-World Data

Analyzing and Visualizing Real-World Data

1. Preprocessing Data: Part I
Loading the DataData TypesColumns OverviewRemoving Characters: Method 1Removing Characters: Method 2Checking ColumnsReplacing Characters
2. Preprocessing Data: Part II
Analyzing ColumnsRemoving and ReplacingProcessing DatesWrong 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

book
Removing and Replacing

As mentioned previously, there are two ways to perform removing or replacing operations. Since we used the .str accessor two chapters ago, let's use a lambda function this time.

Task
test

Swipe to begin your solution

  1. Define a lambda function with a single argument x that will:

    • Remove the '$' characters starting from the left (using the .lstrip() method);

    • Replace all blank spaces (' ') with empty strings ('') (using the .replace() method);

    • Assign the function to the rmv_rpl variable.

  2. Apply the rmv_rpl function to the 'Weekly_Sales' column using the .apply() method and convert it to the float data type.

Solution

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Section 2. Chapter 2
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book
Removing and Replacing

As mentioned previously, there are two ways to perform removing or replacing operations. Since we used the .str accessor two chapters ago, let's use a lambda function this time.

Task
test

Swipe to begin your solution

  1. Define a lambda function with a single argument x that will:

    • Remove the '$' characters starting from the left (using the .lstrip() method);

    • Replace all blank spaces (' ') with empty strings ('') (using the .replace() method);

    • Assign the function to the rmv_rpl variable.

  2. Apply the rmv_rpl function to the 'Weekly_Sales' column using the .apply() method and convert it to the float data type.

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 2. Chapter 2
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