Table of Contents
To fix this issue, you need to convert the dtyped array and scalar into compatible types. For example, if the array is dtyped as an int64, the scalar should also be an int64. If the scalar is of type bool, then you need to convert it to an int64. This can be done by using the built-in functions in Python, such as int() or float(). Once both the array and scalar are of the same type, then the ‘rand_’ operation should work.
One error you may encounter in Python is the following:
TypeError:Cannot perform 'rand_' with a dtyped [int64] array and scalar of type [bool]
This error usually occurs when you attempt to filter a pandas DataFrame using multiple conditions but fail to use parenthesis around each individual condition.
The following example shows how to fix this error in practice.
How to Reproduce the Error
Suppose we have the following pandas DataFrame:
import pandas as pd #create DataFrame df = pd.DataFrame({'team': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'], 'points': [18, 22, 19, 14, 14, 11, 20, 28], 'assists': [5, 7, 7, 9, 12, 9, 9, 4], 'rebounds': [11, 8, 10, 6, 6, 5, 9, 12]}) #view DataFrame print(df) team points assists rebounds 0 A 18 5 11 1 A 22 7 8 2 A 19 7 10 3 A 14 9 6 4 B 14 12 6 5 B 11 9 5 6 B 20 9 9 7 B 28 4 12
Now suppose we attempt to filter the DataFrame to only show rows where the team column is equal to ‘A’ and the points column is greater than 15:
#attempt to filter DataFrame
df.loc[df.team == 'A' & df.points > 15]
TypeError:Cannot perform 'rand_' with a dtyped [int64] array and scalar of type [bool]
We receive an error because we didn’t place parenthesis around each individual condition.
How to Fix the Error
To fix this error, we just need to make sure we place parenthesis around each individual condition when performing the filter:
#filter DataFrame
df.loc[(df.team == 'A') & (df.points > 15)]
team points assists rebounds
0 A 18 5 11
1 A 22 7 8
2 A 19 7 10
Notice that we’re able to successfully filter the DataFrame to only show the rows where team is equal to ‘A’ and where points is greater than 15.
Note that we also need to place parenthesis around each individual condition if we’re using an or “|” operator instead:
#filter rows where team is equal to 'A' or points is greater than 15
df.loc[(df.team == 'A') | (df.points > 15)]
team points assists rebounds
0 A 18 5 11
1 A 22 7 8
2 A 19 7 10
3 A 14 9 6
6 B 20 9 9
7 B 28 4 12
Notice that we avoid any errors once again.
The following tutorials explain how to fix other common errors in pandas: