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Advanced Techniques in pandas

Manage an Incorrect ColumnManage 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.

  1. Firstly, we need to replace - with .. To do so, you will apply the function .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;
  2. Then, convert the column to the float data type. To do so, use .astype() function. The syntax is data['column_name'].astype('type').
    In our case, the type is 'float'.

Завдання

Your task is to:

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

Все було зрозуміло?

Секція 5. Розділ 8
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Зміст курсу

Advanced Techniques in pandas

1. Get Familiar With Indexing and Selecting Data

Output Columns by TitleOutput Rows by IndexSelect Specific Rows and ColumnsLearn More About IndexationGet Familiar With lambda FunctionsExpand Functionality of the .iloc[] Function

2. Dealing With Conditions

Set ConditionSelect Data Based on ConditionDealing With Several ConditionsMake Your Code BeautifulConditions Quiz

3. Extract Data

Is Data in ...?Combine Your KnowledgeBetween FunctionExtract Specific DataFind the Smallest Values of a ColumnFind the Largest Values of a ColumnFind the Correlation

4. Aggregating Data

Get Familiar With the .groupby() MethodGroup by Several ColumnsComplicated GroupingGroupDealing With Pivot TablesCreate a Pivot Table

5. Preprocessing Data

Check for Missing ValuesCalculate the Number of Missing ValuesWhat Will We Do With the NaN Values?How to Delete Only NaN Values?Fill In the Missing ValuesManage Categorical VariablesCheck the Column TypeManage an Incorrect ColumnRename the Column

Advanced Techniques in pandas

Manage an Incorrect ColumnManage 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.

  1. Firstly, we need to replace - with .. To do so, you will apply the function .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;
  2. Then, convert the column to the float data type. To do so, use .astype() function. The syntax is data['column_name'].astype('type').
    In our case, the type is 'float'.

Завдання

Your task is to:

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

Все було зрозуміло?

Секція 5. Розділ 8
toggle bottom row
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