When encountering the error “TypeError: cannot subtract datetimearray from ndarray,” it means you are trying to perform a subtraction operation between a numpy ndarray and a datetimearray, which is not allowed. To better understand this issue, let’s break it down with an example:
import numpy as np
import pandas as pd
# Create a numpy ndarray
arr = np.array([1, 2, 3, 4, 5])
# Create a pandas datetimearray
dates = pd.date_range('2022-01-01', periods=5)
# Attempt to subtract datetimearray from ndarray
result = arr - dates
In this example, we are trying to subtract the datetimearray “dates” from the ndarray “arr.” However, this operation will result in the “TypeError” mentioned above.
The reason for this error is that numpy ndarrays are designed for numerical operations and do not inherently support operations with datetime data types. In contrast, a datetimearray represents an array of datetime objects.
To perform element-wise subtraction between the ndarray and the datetimearray, you need to convert the datetimearray into a compatible numeric format, such as timestamps. One common way to achieve this is by using the “astype()” function in pandas.
# Convert datetimearray to timestamps (numeric format)
timestamps = dates.astype(np.int64) // 10**9
# Perform element-wise subtraction with the transformed datetimearray
result = arr - timestamps
By converting the datetimearray to timestamps, we obtain a numeric representation that can be directly subtracted from the ndarray. The “// 10**9” part is used to convert nanoseconds to seconds, which is the unit used by default for timestamps.
Now, the subtraction operation will work correctly without raising the TypeError. The resulting “result” will be a new ndarray containing the differences between the original ndarray and the timestamps representing the datetimearray.