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.dropna() function drop all the missing values from the given TimedeltaIndex object. The function return Index without NA/NaN values.
Syntax : TimedeltaIndex.dropna(how=’any’)
Parameters :
how : If the Index is a MultiIndex, drop the value when any or all levels are NaN.Return : valid : Index
Example #1: Use TimedeltaIndex.dropna() function to drop all missing values from the given TimedeltaIndex object.
# importing pandas as pd import pandas as pd # Create the TimedeltaIndex object tidx = pd.TimedeltaIndex(data =['06:05:01.000030', None, '22 day 2 min 3us 10ns', '+23:59:59.999999', None, '+12:19:59.999999']) # Print the TimedeltaIndex object print(tidx) |
Output :
Now we will use the TimedeltaIndex.dropna() function to drop all the missing values from the tidx object.
# drop all missing values tidx.dropna() |
Output :
As we can see in the output, the TimedeltaIndex.dropna() function has returned a new object which has all the missing values dropped.
Example #2: Use TimedeltaIndex.dropna() function to drop all missing values from the given TimedeltaIndex object.
# importing pandas as pd import pandas as pd # Create the TimedeltaIndex object tidx = pd.TimedeltaIndex(data =[None, '1 days 06:05:01.000030', None, '1 days 02:00:00', '21 days 06:15:01.000030']) # Print the TimedeltaIndex object print(tidx) |
Output :
Now we will use the TimedeltaIndex.dropna() function to drop all the missing values from the tidx object.
# drop all missing values tidx.dropna() |
Output :
As we can see in the output, the TimedeltaIndex.dropna() function has returned a new object which has all the missing values dropped.
