[1055] Get the index of the “True” values in a Pandas Series
To get the index of the “True” values in a Pandas Series, you can use the index
attribute along with boolean indexing. Here’s a simple way to do it:
-
Import Pandas:
import pandas as pd -
Create your Series:
series = pd.Series([True, False, True, False, True]) -
Get the indices of “True” values:
true_indices = series[series].index -
Convert to a list (optional):
true_indices_list = list(true_indices)
Here’s the complete code snippet:
import pandas as pd # Create your Series series = pd.Series([True, False, True, False, True]) # Get the indices of "True" values true_indices = series[series].index # Convert to a list (optional) true_indices_list = list(true_indices) print(true_indices_list)
This will output:
[0, 2, 4]
This method uses boolean indexing to filter the Series for “True” values and then retrieves their indices.
Would you like more details or help with another aspect of Pandas?
Sure, let’s break down the script step by step:
Script:
true_indices = series[series].index
Explanation:
-
series[series]
:- This part uses boolean indexing. When you use a Series as an indexer for itself, it filters the Series based on the boolean values it contains.
- For example, if
series
is:
Then0 True 1 False 2 True 3 False 4 True dtype: bool series[series]
will return only the elements where the value isTrue
:0 True 2 True 4 True dtype: bool
-
.index
:- The
.index
attribute of a Series returns the index labels of the Series. - Applying
.index
to the filtered Series (series[series]
) will give you the indices of theTrue
values.
- The
Putting it all together:
series[series]
filters the Series to include only theTrue
values..index
extracts the indices of theseTrue
values.
So, if series
is:
0 True 1 False 2 True 3 False 4 True dtype: bool
Then true_indices
will be:
Int64Index([0, 2, 4], dtype='int64')
This means the indices of the True
values are 0, 2, and 4.
Does this help clarify things? Would you like to dive deeper into any part of the explanation?
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