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Advanced Techniques in pandas
course content

Course Content

Advanced Techniques in pandas

Advanced Techniques in pandas

1. Getting Familiar With Indexing and Selecting Data
Outputting Columns by TitleOutputting Rows by IndexSelecting Specific Rows and ColumnsLearning More About IndexationGetting Familiar With lambda FunctionsExpanding Functionality of the .iloc[] Attribute
2. Dealing With Conditions
Setting ConditionSelecting Data Based on ConditionDealing With Several ConditionsMaking Your Code BeautifulConditions Quiz
3. Extracting Data
Is Data in ...?Combining Your KnowledgeBetween MethodExtracting Specific DataFinding the Smallest Values of a ColumnFinding the Largest Values of a ColumnFinding the Correlation
4. Aggregating Data
Getting Familiar With the .groupby() MethodGrouping by Several ColumnsComplicated GroupingAdvanced GroupingDealing With Pivot TablesCreating a Pivot Table
5. Preprocessing Data
Checking for Missing ValuesCalculating the Number of Missing ValuesWhat Will We Do With the NaN Values?How to Delete Only NaN Values?Filling In the Missing ValuesManaging Categorical VariablesChecking the Column TypeManaging an Incorrect ColumnRenaming the Column

bookManaging 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 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;
  2. 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'.

Task

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'.

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Section 5. Chapter 8
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bookManaging 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 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;
  2. 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'.

Task

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'.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 5. Chapter 8
toggle bottom row

bookManaging 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 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;
  2. 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'.

Task

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'.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

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 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;
  2. 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'.

Task

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'.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 5. Chapter 8
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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