Retrieving the Frequency Name from a Pandas CustomBusinessHour Offset Object

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πŸ’‘ Problem Formulation: Pandas is a powerful Python library used for data manipulation and analysis. One particular feature it provides is the ability to work with time series data and custom business hours. Sometimes, we need to understand the frequency with which a given CustomBusinessHour offset is applied. This article explores different methods to retrieve the frequency name from a CustomBusinessHour offset object in Python’s Pandas. For instance, if you create a CustomBusinessHour object with a frequency of ‘4H’ (four hours), the goal is to return the string "4H".

Method 1: Accessing the rule_code Property

This method focuses on accessing the rule_code property of the CustomBusinessHour object. The rule_code is a built-in property that succinctly indicates the frequency rule of the offset object. This property makes it straightforward to identify the applied frequency without any additional steps.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.freqstr)

Output:

'4H'

In this example, after creating a CustomBusinessHour object, we simply print the freqstr attribute. The result is the frequency of the CustomBusinessHour as a string, which is '4H'.

Method 3: Converting to a String

Converting the CustomBusinessHour object instance to a string may also reveal the frequency information. This indirect method leverages Python’s string representation mechanism.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.rule_code)

Output:

'4H'

This code snippet creates a CustomBusinessHour object with a frequency of four hours and prints the rule applied by accessing the rule_code attribute. The output is the string '4H', exactly what we are seeking.

Method 2: Using the freqstr Attribute

The freqstr attribute is an alternative way to access the frequency string of a Pandas offset object. This attribute holds the frequency information as a string and provides a simple and direct way to obtain the frequency.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.freqstr)

Output:

'4H'

In this example, after creating a CustomBusinessHour object, we simply print the freqstr attribute. The result is the frequency of the CustomBusinessHour as a string, which is '4H'.

Method 3: Converting to a String

Converting the CustomBusinessHour object instance to a string may also reveal the frequency information. This indirect method leverages Python’s string representation mechanism.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.rule_code)

Output:

'4H'

This code snippet creates a CustomBusinessHour object with a frequency of four hours and prints the rule applied by accessing the rule_code attribute. The output is the string '4H', exactly what we are seeking.

Method 2: Using the freqstr Attribute

The freqstr attribute is an alternative way to access the frequency string of a Pandas offset object. This attribute holds the frequency information as a string and provides a simple and direct way to obtain the frequency.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.freqstr)

Output:

'4H'

In this example, after creating a CustomBusinessHour object, we simply print the freqstr attribute. The result is the frequency of the CustomBusinessHour as a string, which is '4H'.

Method 3: Converting to a String

Converting the CustomBusinessHour object instance to a string may also reveal the frequency information. This indirect method leverages Python’s string representation mechanism.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.rule_code)

Output:

'4H'

This code snippet creates a CustomBusinessHour object with a frequency of four hours and prints the rule applied by accessing the rule_code attribute. The output is the string '4H', exactly what we are seeking.

Method 2: Using the freqstr Attribute

The freqstr attribute is an alternative way to access the frequency string of a Pandas offset object. This attribute holds the frequency information as a string and provides a simple and direct way to obtain the frequency.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.freqstr)

Output:

'4H'

In this example, after creating a CustomBusinessHour object, we simply print the freqstr attribute. The result is the frequency of the CustomBusinessHour as a string, which is '4H'.

Method 3: Converting to a String

Converting the CustomBusinessHour object instance to a string may also reveal the frequency information. This indirect method leverages Python’s string representation mechanism.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.freqstr)

Output:

'4H'

In this example, after creating a CustomBusinessHour object, we simply print the freqstr attribute. The result is the frequency of the CustomBusinessHour as a string, which is '4H'.

Method 3: Converting to a String

Converting the CustomBusinessHour object instance to a string may also reveal the frequency information. This indirect method leverages Python’s string representation mechanism.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.rule_code)

Output:

'4H'

This code snippet creates a CustomBusinessHour object with a frequency of four hours and prints the rule applied by accessing the rule_code attribute. The output is the string '4H', exactly what we are seeking.

Method 2: Using the freqstr Attribute

The freqstr attribute is an alternative way to access the frequency string of a Pandas offset object. This attribute holds the frequency information as a string and provides a simple and direct way to obtain the frequency.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.freqstr)

Output:

'4H'

In this example, after creating a CustomBusinessHour object, we simply print the freqstr attribute. The result is the frequency of the CustomBusinessHour as a string, which is '4H'.

Method 3: Converting to a String

Converting the CustomBusinessHour object instance to a string may also reveal the frequency information. This indirect method leverages Python’s string representation mechanism.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.freqstr)

Output:

'4H'

In this example, after creating a CustomBusinessHour object, we simply print the freqstr attribute. The result is the frequency of the CustomBusinessHour as a string, which is '4H'.

Method 3: Converting to a String

Converting the CustomBusinessHour object instance to a string may also reveal the frequency information. This indirect method leverages Python’s string representation mechanism.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.rule_code)

Output:

'4H'

This code snippet creates a CustomBusinessHour object with a frequency of four hours and prints the rule applied by accessing the rule_code attribute. The output is the string '4H', exactly what we are seeking.

Method 2: Using the freqstr Attribute

The freqstr attribute is an alternative way to access the frequency string of a Pandas offset object. This attribute holds the frequency information as a string and provides a simple and direct way to obtain the frequency.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.freqstr)

Output:

'4H'

In this example, after creating a CustomBusinessHour object, we simply print the freqstr attribute. The result is the frequency of the CustomBusinessHour as a string, which is '4H'.

Method 3: Converting to a String

Converting the CustomBusinessHour object instance to a string may also reveal the frequency information. This indirect method leverages Python’s string representation mechanism.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.freqstr)

Output:

'4H'

In this example, after creating a CustomBusinessHour object, we simply print the freqstr attribute. The result is the frequency of the CustomBusinessHour as a string, which is '4H'.

Method 3: Converting to a String

Converting the CustomBusinessHour object instance to a string may also reveal the frequency information. This indirect method leverages Python’s string representation mechanism.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.rule_code)

Output:

'4H'

This code snippet creates a CustomBusinessHour object with a frequency of four hours and prints the rule applied by accessing the rule_code attribute. The output is the string '4H', exactly what we are seeking.

Method 2: Using the freqstr Attribute

The freqstr attribute is an alternative way to access the frequency string of a Pandas offset object. This attribute holds the frequency information as a string and provides a simple and direct way to obtain the frequency.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.freqstr)

Output:

'4H'

In this example, after creating a CustomBusinessHour object, we simply print the freqstr attribute. The result is the frequency of the CustomBusinessHour as a string, which is '4H'.

Method 3: Converting to a String

Converting the CustomBusinessHour object instance to a string may also reveal the frequency information. This indirect method leverages Python’s string representation mechanism.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.freqstr)

Output:

'4H'

In this example, after creating a CustomBusinessHour object, we simply print the freqstr attribute. The result is the frequency of the CustomBusinessHour as a string, which is '4H'.

Method 3: Converting to a String

Converting the CustomBusinessHour object instance to a string may also reveal the frequency information. This indirect method leverages Python’s string representation mechanism.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.
from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.rule_code)

Output:

'4H'

This code snippet creates a CustomBusinessHour object with a frequency of four hours and prints the rule applied by accessing the rule_code attribute. The output is the string '4H', exactly what we are seeking.

Method 2: Using the freqstr Attribute

The freqstr attribute is an alternative way to access the frequency string of a Pandas offset object. This attribute holds the frequency information as a string and provides a simple and direct way to obtain the frequency.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(cbh.freqstr)

Output:

'4H'

In this example, after creating a CustomBusinessHour object, we simply print the freqstr attribute. The result is the frequency of the CustomBusinessHour as a string, which is '4H'.

Method 3: Converting to a String

Converting the CustomBusinessHour object instance to a string may also reveal the frequency information. This indirect method leverages Python’s string representation mechanism.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print(str(cbh))

Output:

''

This code demonstrates obtaining the frequency by converting the CustomBusinessHour object to a string. While the output contains the frequency information (04:00), it is embedded within a longer string and thus requires parsing to isolate the ‘4H’ value.

Method 4: Defining a Custom Function

A custom function can be created to extract the frequency from a CustomBusinessHour object. This function can use the rule_code property and format it according to specific requirements.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

def get_freq_name(cbh_obj):
    return cbh_obj.rule_code

cbh = CustomBusinessHour(n=4)
print(get_freq_name(cbh))

Output:

'4H'

This code snippet presents a custom function, get_freq_name(), that simply returns the rule_code of a CustomBusinessHour object. The function is then used to print out the frequency ‘4H’. It essentially encapsulates the logic and can have additional features or checks added as necessary.

Bonus One-Liner Method 5: Using a Lambda Function

For those who prefer a concise approach, a lambda function inline with the print statement can achieve the same result. It’s brief and doesn’t require a separate function definition.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

cbh = CustomBusinessHour(n=4)
print((lambda x: x.rule_code)(cbh))

Output:

'4H'

The lambda function demonstrated here is an anonymous, in-place function that returns the rule_code of the input CustomBusinessHour object. The output remains ‘4H’ as expected.

Summary/Discussion

  • Method 1: Accessing rule_code. Straightforward. Cannot be customized.
  • Method 2: Using freqstr. Direct. Relies on internal string representation.
  • Method 3: Converting to a String. Provides full object information. Requires parsing for specific frequency details.
  • Method 4: Defining a Custom Function. Enables extensibility. Adds more code.
  • Bonus Method 5: Lambda Function. Compact. Less readable for beginners.