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Removing Characters: Method 2 | Preprocessing Data: Part I
Analyzing and Visualizing Real-World Data

Removing Characters: Method 2

As mentioned, there are two ways to remove a character from all column values. The second method uses a lambda function. How does it work? You define a lambda function that removes a certain character/characters from a function variable, and apply it to the selected column. Then you convert obtained values to the necessary type and save them.

Tarefa

  1. Define a lambda function with a single argument x that will look for and delete any of the characters '$°C%' from both the left and right sides (using the .strip() method). Assign the function to the rm variable.
  2. Apply the rm function to the 'Fuel_Price' column and then convert it to numerical type (float) using the .astype() method. Assign the obtained result to the same column.
  3. Perform the same actions described in the step 2 for the 'Unemployment' column.
  4. Perform the same actions described in the step 2 for the 'Temperature' column.
  5. Display the first row of the df dataframe and data types of the df dataframe.

Tudo estava claro?

Seção 1. Capítulo 5
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Conteúdo do Curso

Analyzing and Visualizing Real-World Data

Removing Characters: Method 2

As mentioned, there are two ways to remove a character from all column values. The second method uses a lambda function. How does it work? You define a lambda function that removes a certain character/characters from a function variable, and apply it to the selected column. Then you convert obtained values to the necessary type and save them.

Tarefa

  1. Define a lambda function with a single argument x that will look for and delete any of the characters '$°C%' from both the left and right sides (using the .strip() method). Assign the function to the rm variable.
  2. Apply the rm function to the 'Fuel_Price' column and then convert it to numerical type (float) using the .astype() method. Assign the obtained result to the same column.
  3. Perform the same actions described in the step 2 for the 'Unemployment' column.
  4. Perform the same actions described in the step 2 for the 'Temperature' column.
  5. Display the first row of the df dataframe and data types of the df dataframe.

Tudo estava claro?

Seção 1. Capítulo 5
toggle bottom row
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