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Analyzing and Visualizing Real-World Data
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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
Comparing Shops

As you can see, all of these points are related to the 'pre-Christmas' periods, as we noticed before. Now, let's use visualizing tools to compare the revenue for shops. We already know the top 5 selling stores, but are other shops significantly worse? We'll find out using a bar chart.

Uppgift

Swipe to start coding

  1. Prepare the data: group the values of the df DataFrame based on the 'Store' column, then select the 'Weekly_Sales' column, calculate sum values across groups, and reset the indexes. Save the result within the data variable.
  2. Initialize a bar plot. Use the 'Store' column values of data for the x-axis, 'Weekly_Sales' for the y-axis, and make bars 'blue'.
  3. Display the plot.

Lösning

Switch to desktopByt till skrivbordet för praktisk övningFortsätt där du är med ett av alternativen nedan
Var allt tydligt?

Hur kan vi förbättra det?

Tack för dina kommentarer!

Avsnitt 4. Kapitel 6
toggle bottom row

book
Comparing Shops

As you can see, all of these points are related to the 'pre-Christmas' periods, as we noticed before. Now, let's use visualizing tools to compare the revenue for shops. We already know the top 5 selling stores, but are other shops significantly worse? We'll find out using a bar chart.

Uppgift

Swipe to start coding

  1. Prepare the data: group the values of the df DataFrame based on the 'Store' column, then select the 'Weekly_Sales' column, calculate sum values across groups, and reset the indexes. Save the result within the data variable.
  2. Initialize a bar plot. Use the 'Store' column values of data for the x-axis, 'Weekly_Sales' for the y-axis, and make bars 'blue'.
  3. Display the plot.

Lösning

Switch to desktopByt till skrivbordet för praktisk övningFortsätt där du är med ett av alternativen nedan
Var allt tydligt?

Hur kan vi förbättra det?

Tack för dina kommentarer!

Avsnitt 4. Kapitel 6
Switch to desktopByt till skrivbordet för praktisk övningFortsätt där du är med ett av alternativen nedan
Vi beklagar att något gick fel. Vad hände?
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