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Data Manipulation using pandas
Data Manipulation using pandas
Challenge
You've solved the first problem with wrong column type. Let's solve the remaining one (with dots). Recall that there are 4 columns with wrong types left ('morgh', 'valueh', 'grosrth', 'omphtotinch'). These columns considered to have dots as indicators for 'Not applicable'. For instance, columns valueh and grosrth are mutually exclusive, since the first one indicates the price of dwelling (i.e., house is owned) and the second one indicates the monthly rent.
The most appropriate way to solve this problem is to replace dots by NA values. In that case, we would be able to manipulate column like a numerical one.
Swipe to show code editor
Perform a replacement of dot symbols . by NAs for 'morgh', 'valueh', 'grosrth', 'omphtotinch' columns. Follow the next steps:
- Import the
NumPylibrary withnpalias. - Apply the
.where()method to thedfdataframe. - Set the condition what values must remain unchanged. These must be non-dots values.
- Set the
otherparameter tonanvalue fromNumPy.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівДякуємо за ваш відгук!
Challenge
You've solved the first problem with wrong column type. Let's solve the remaining one (with dots). Recall that there are 4 columns with wrong types left ('morgh', 'valueh', 'grosrth', 'omphtotinch'). These columns considered to have dots as indicators for 'Not applicable'. For instance, columns valueh and grosrth are mutually exclusive, since the first one indicates the price of dwelling (i.e., house is owned) and the second one indicates the monthly rent.
The most appropriate way to solve this problem is to replace dots by NA values. In that case, we would be able to manipulate column like a numerical one.
Swipe to show code editor
Perform a replacement of dot symbols . by NAs for 'morgh', 'valueh', 'grosrth', 'omphtotinch' columns. Follow the next steps:
- Import the
NumPylibrary withnpalias. - Apply the
.where()method to thedfdataframe. - Set the condition what values must remain unchanged. These must be non-dots values.
- Set the
otherparameter tonanvalue fromNumPy.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівДякуємо за ваш відгук!
Challenge
You've solved the first problem with wrong column type. Let's solve the remaining one (with dots). Recall that there are 4 columns with wrong types left ('morgh', 'valueh', 'grosrth', 'omphtotinch'). These columns considered to have dots as indicators for 'Not applicable'. For instance, columns valueh and grosrth are mutually exclusive, since the first one indicates the price of dwelling (i.e., house is owned) and the second one indicates the monthly rent.
The most appropriate way to solve this problem is to replace dots by NA values. In that case, we would be able to manipulate column like a numerical one.
Swipe to show code editor
Perform a replacement of dot symbols . by NAs for 'morgh', 'valueh', 'grosrth', 'omphtotinch' columns. Follow the next steps:
- Import the
NumPylibrary withnpalias. - Apply the
.where()method to thedfdataframe. - Set the condition what values must remain unchanged. These must be non-dots values.
- Set the
otherparameter tonanvalue fromNumPy.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівДякуємо за ваш відгук!
You've solved the first problem with wrong column type. Let's solve the remaining one (with dots). Recall that there are 4 columns with wrong types left ('morgh', 'valueh', 'grosrth', 'omphtotinch'). These columns considered to have dots as indicators for 'Not applicable'. For instance, columns valueh and grosrth are mutually exclusive, since the first one indicates the price of dwelling (i.e., house is owned) and the second one indicates the monthly rent.
The most appropriate way to solve this problem is to replace dots by NA values. In that case, we would be able to manipulate column like a numerical one.
Swipe to show code editor
Perform a replacement of dot symbols . by NAs for 'morgh', 'valueh', 'grosrth', 'omphtotinch' columns. Follow the next steps:
- Import the
NumPylibrary withnpalias. - Apply the
.where()method to thedfdataframe. - Set the condition what values must remain unchanged. These must be non-dots values.
- Set the
otherparameter tonanvalue fromNumPy.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівПерейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів