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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

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.

Tarefa

  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.

Tarefa

  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.

Tudo estava claro?

Seção 2. Capítulo 2
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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.

Tarefa

  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.

Tarefa

  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.

Tudo estava claro?

Seção 2. Capítulo 2
toggle bottom row

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.

Tarefa

  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.

Tarefa

  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.

Tudo estava claro?

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.

Tarefa

  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.

Seção 2. Capítulo 2
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