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.astype() function create an Index with values cast to dtypes. The class of a new Index is determined by dtype. When conversion is impossible, a ValueError exception is raised.
Syntax : TimedeltaIndex.astype(dtype, copy=True)
Parameters :
dtype : numpy dtype or pandas type
copy : bool, default True
By default, astype always returns a newly allocated object. If copy is set to False and internal requirements on dtype are satisfied, the original data is used to create a new Index or the original Index is returned.Return : Index object
Example #1: Use TimedeltaIndex.astype() function to cast the values of the TimedeltaIndex object to ‘str’.
# importing pandas as pd import pandas as pd # Create the first TimedeltaIndex object tidx = pd.TimedeltaIndex(start = '1 days 02:00:12.001124', periods = 5, freq = 'N', name = 'Koala') # Print the TimedeltaIndex object print(tidx) |
Output :
Now we will use the TimedeltaIndex.astype() function to cast the value to string.
# cast the data values to string format. tidx.astype('str') |
Output :
As we can see in the output, the TimedeltaIndex.astype() function has cast the values of the tidx object to the desired format.
Example #2: Use TimedeltaIndex.astype() function to cast the values of the TimedeltaIndex object to ‘bool’.
# 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']) # Print the TimedeltaIndex object print(tidx) |
Output :
Now we will use the TimedeltaIndex.astype() function to cast the value to bool type.
# cast the data values to bool type. tidx.astype('bool') |
Output :
As we can see in the output, the TimedeltaIndex.astype() function has cast the values of the tidx object to the desired format.
