Python | Pandas DatetimeIndex.inferred_freq

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas DatetimeIndex.inferred_freq attribute tries to return a string representing a frequency guess, generated by infer_freq. For those cases in which the function is not able to auto detect the frequency of the DatetimeIndex it returns None.

Syntax: DatetimeIndex.inferred_freq Return: freq

Example #1: Use DatetimeIndex.inferred_freq attribute to auto detect the frequency of the given DatetimeIndex object. Python3

# importing pandas as pd
import pandas as pd

# Create the DatetimeIndex
didx = pd.date_range("2008-12-30", periods = 5, freq ='Q')

# Print the DatetimeIndex
print(didx)

Output : Now we want the function to auto detect the frequency of the given DatetimeIndex object. Python3

# find the frequency of the object.
didx.inferred_freq

Output : As we can see in the output, the function has tried to auto detect the frequency of the given DatetimeIndex object and has returned a quarter type frequency starting from the month of December.   Example #2: Use DatetimeIndex.inferred_freq attribute to auto detect the frequency of the given DatetimeIndex object. Python3

# importing pandas as pd
import pandas as pd

# Create the DatetimeIndex
didx = pd.DatetimeIndex(start ='2000-01-31 06:30', freq ='BM', 
                           periods = 5, tz ='Asia/Calcutta')

# Print the DatetimeIndex
print(didx)

Output : Now we want the function to auto detect the frequency of the given DatetimeIndex object. Python3

# find the frequency of the object.
didx.inferred_freq

Output : As we can see in the output, the function has tried to auto detect the frequency of the given DatetimeIndex object and has returned 'BM' (Business Month end) frequency.