Managing an Incorrect Column

So, you received the result object. This means that the type of the column is non-numerical, but to calculate necessary values, the column need to be numerical. Let's change that.

Firstly, we need to replace - with .. To do so, you will apply the method .str.replace() to replace the character in the string in the dataset column. The syntax is
data['column_name'].str.replace('old_symbol','new_symbol')
In our case, old_symbol is -, and . is the new_symbol;
Then, convert the column to the float data type. To do so, use .astype() method. The syntax is data['column_name'].astype('type').
In our case, the type is 'float'.

Завдання

Your task is to:

Follow the algorithm above and firstly replace - with . in the column 'Fare'.
Convert the column 'Fare' to the 'float' data type.
Output the type of the column 'Fare'.

Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів

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Секція 5. Розділ 8

Managing an Incorrect Column

So, you received the result object. This means that the type of the column is non-numerical, but to calculate necessary values, the column need to be numerical. Let's change that.

Firstly, we need to replace - with .. To do so, you will apply the method .str.replace() to replace the character in the string in the dataset column. The syntax is
data['column_name'].str.replace('old_symbol','new_symbol')
In our case, old_symbol is -, and . is the new_symbol;
Then, convert the column to the float data type. To do so, use .astype() method. The syntax is data['column_name'].astype('type').
In our case, the type is 'float'.

Завдання

Your task is to:

Follow the algorithm above and firstly replace - with . in the column 'Fare'.
Convert the column 'Fare' to the 'float' data type.
Output the type of the column 'Fare'.

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 5. Розділ 8

Managing an Incorrect Column

So, you received the result object. This means that the type of the column is non-numerical, but to calculate necessary values, the column need to be numerical. Let's change that.

Firstly, we need to replace - with .. To do so, you will apply the method .str.replace() to replace the character in the string in the dataset column. The syntax is
data['column_name'].str.replace('old_symbol','new_symbol')
In our case, old_symbol is -, and . is the new_symbol;
Then, convert the column to the float data type. To do so, use .astype() method. The syntax is data['column_name'].astype('type').
In our case, the type is 'float'.

Завдання

Your task is to:

Follow the algorithm above and firstly replace - with . in the column 'Fare'.
Convert the column 'Fare' to the 'float' data type.
Output the type of the column 'Fare'.

Все було зрозуміло?

Дякуємо за ваш відгук!

So, you received the result object. This means that the type of the column is non-numerical, but to calculate necessary values, the column need to be numerical. Let's change that.

Firstly, we need to replace - with .. To do so, you will apply the method .str.replace() to replace the character in the string in the dataset column. The syntax is
data['column_name'].str.replace('old_symbol','new_symbol')
In our case, old_symbol is -, and . is the new_symbol;
Then, convert the column to the float data type. To do so, use .astype() method. The syntax is data['column_name'].astype('type').
In our case, the type is 'float'.

Завдання

Your task is to:

Follow the algorithm above and firstly replace - with . in the column 'Fare'.
Convert the column 'Fare' to the 'float' data type.
Output the type of the column 'Fare'.

Секція 5. Розділ 8