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Advanced Techniques in pandas

Between FunctionBetween Function

Let's examine our dataset a little bit. We have numerical columns, for instance 'Engine_volume'. Imagine you want information about all cars with an 'Engine_volume' less than 3, but greater than 2. Using the .loc[]statement, we can easily do this.

However, knowing that Python provides a special function that can extract data between two values without using two conditions will be useful. This function is titled .between(left_bound, right_bound). You can apply it to numerical columns specifying the numbers' left and right bounds. Look at the example and learn how we can combine .between() and .loc[] statements.

The code below extracts data where 'Engine_volume' >= 2 and 'Engine_volume' <= 3, but what should we do to make one or even two boundaries exclusive? Let's find out using the same example. You can add an additional argument to the .between() function.

  • .between(2, 3, inclusive = 'right') - extracts data where 'Engine_volume' > 2 and 'Engine_volume' <= 3;
  • .between(2, 3, inclusive = 'left') - extracts data where 'Engine_volume' >= 2 and 'Engine_volume' < 3;
  • .between(2, 3, inclusive = 'both') - extracts data where 'Engine_volume' >= 2 and 'Engine_volume' <= 3. The result will be the same as without using inclusive = 'both';
  • .between(2, 3, inclusive = 'neither') - extracts data where 'Engine_volume' > 2 and 'Engine_volume' < 3.
question-icon

Your task here is to extract data corresponding to the comments.

# Extract data where values from the column 'Year' are greater than 2010 and less than 2015
data.loc[data['Year'].between(2010, 2015, inclusive = '')]

# Extract data where values from the column 'Year' are greater or equal than 2010 and less than 2015
data.loc[data['Year'].between(2010, 2015, inclusive = '')]

# Extract data where values from the column 'Year' are greater or equal than 2010 and less or equal than 2015
data.loc[data['Year'].between(2010, 2015, inclusive = '')]

# Extract data where values from the column 'Year' are greater than 2010 and less or equal than 2015
data.loc[data['Year'].between(2010, 2015, inclusive = '')]

Click or drag`n`drop items and fill in the blanks

¿Todo estuvo claro?

Sección 3. Capítulo 3
course content

Contenido del Curso

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

Between FunctionBetween Function

Let's examine our dataset a little bit. We have numerical columns, for instance 'Engine_volume'. Imagine you want information about all cars with an 'Engine_volume' less than 3, but greater than 2. Using the .loc[]statement, we can easily do this.

However, knowing that Python provides a special function that can extract data between two values without using two conditions will be useful. This function is titled .between(left_bound, right_bound). You can apply it to numerical columns specifying the numbers' left and right bounds. Look at the example and learn how we can combine .between() and .loc[] statements.

The code below extracts data where 'Engine_volume' >= 2 and 'Engine_volume' <= 3, but what should we do to make one or even two boundaries exclusive? Let's find out using the same example. You can add an additional argument to the .between() function.

  • .between(2, 3, inclusive = 'right') - extracts data where 'Engine_volume' > 2 and 'Engine_volume' <= 3;
  • .between(2, 3, inclusive = 'left') - extracts data where 'Engine_volume' >= 2 and 'Engine_volume' < 3;
  • .between(2, 3, inclusive = 'both') - extracts data where 'Engine_volume' >= 2 and 'Engine_volume' <= 3. The result will be the same as without using inclusive = 'both';
  • .between(2, 3, inclusive = 'neither') - extracts data where 'Engine_volume' > 2 and 'Engine_volume' < 3.
question-icon

Your task here is to extract data corresponding to the comments.

# Extract data where values from the column 'Year' are greater than 2010 and less than 2015
data.loc[data['Year'].between(2010, 2015, inclusive = '')]

# Extract data where values from the column 'Year' are greater or equal than 2010 and less than 2015
data.loc[data['Year'].between(2010, 2015, inclusive = '')]

# Extract data where values from the column 'Year' are greater or equal than 2010 and less or equal than 2015
data.loc[data['Year'].between(2010, 2015, inclusive = '')]

# Extract data where values from the column 'Year' are greater than 2010 and less or equal than 2015
data.loc[data['Year'].between(2010, 2015, inclusive = '')]

Click or drag`n`drop items and fill in the blanks

¿Todo estuvo claro?

Sección 3. Capítulo 3
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