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 TimedeltaIndex.value_counts() function return an object containing counts of unique values. The resulting object will be in descending order so that the first element is the most frequently-occurring element. Excludes NA values by default.
Syntax : TimedeltaIndex.value_counts(normalize=False, sort=True, ascending=False, bins=None, dropna=True)
Parameters :
normalize : (boolean, default False) If True then the object returned will contain the relative frequencies of the unique values.
sort : (boolean, default True) Sort by values
ascending : (boolean, default False) Sort in ascending order
bins: (integer, optional) Rather than count values, group them into half-open bins, a convenience for pd.cut, only works with numeric data
dropna : (boolean, default True) Don’t include counts of NaN.Return : counts : Series
Example #1: Use TimedeltaIndex.value_counts() function to count the occurrence of each unique values in the given TimedeltaIndex object.
# importing pandas as pd import pandas as pd   # Create the TimedeltaIndex object tidx = pd.TimedeltaIndex(data =['06:05:01.000030', '+23:59:59.999999',                         '22 day 2 min 3us 10ns', '06:05:01.000030',                         '+12:19:59.999999'])   # Print the TimedeltaIndex object print(tidx) |
Output :
Now we will use the TimedeltaIndex.value_counts() function to find the count of occurrence of each unique values in the tidx object.
# count occurrences tidx.value_counts() |
Output :
As we can see in the output, the TimedeltaIndex.value_counts() function has returned an the count of all unique values in the given TimedeltaIndex object.
Â
Example #2: Use TimedeltaIndex.value_counts() function to count the occurrence of each unique values in the given TimedeltaIndex object.
# importing pandas as pd import pandas as pd   # Create the TimedeltaIndex object tidx = pd.TimedeltaIndex(data =['3 days 06:05:01.000030', '1 days 06:05:01.000030',                         '3 days 06:05:01.000030', '1 days 06:05:01.000030',                         '21 days 06:15:01.000030'])   # Print the TimedeltaIndex object print(tidx) |
Output :
Now we will use the TimedeltaIndex.value_counts() function to find the count of occurrence of each unique values in the tidx object.
# count occurrences tidx.value_counts() |
Output :
As we can see in the output, the TimedeltaIndex.value_counts() function has returned an the count of all unique values in the given TimedeltaIndex object.
