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Please enable JavaScript in your browser settings or update your browser.Select Data Based on Condition | Dealing With Conditions
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Course Content

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

Select Data Based on ConditionSelect Data Based on Condition

To excel in programming, you always need to practice. So, in this task, you must also memorize functions from the previous chapter. If you aren't solid on the functions from the last chapter, look at the hints to revise them.

Task

  1. Extract all rows from the columns 'name' and 'hazardous' using the .loc[] function.
  2. Filter data; extract rows where 'hazardous' is True.
  3. Output the first five rows of the data_filtered dataset.

Everything was clear?

Section 2. Chapter 2
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course content

Course Content

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

Select Data Based on ConditionSelect Data Based on Condition

To excel in programming, you always need to practice. So, in this task, you must also memorize functions from the previous chapter. If you aren't solid on the functions from the last chapter, look at the hints to revise them.

Task

  1. Extract all rows from the columns 'name' and 'hazardous' using the .loc[] function.
  2. Filter data; extract rows where 'hazardous' is True.
  3. Output the first five rows of the data_filtered dataset.

Everything was clear?

Section 2. Chapter 2
toggle bottom row
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