ValueError: Boolean array expected for the condition, not object

Question

I am trying to build a classifier with sklearn and get the following error in my console when I run my code.

ValueError: Boolean array expected for the condition, not object

I tried tweaking my data (filling in null values) as well as playing with reshaping properties (however to no avail).

Here is the relevant code

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.metrics import confusion_matrix
from sklearn.tree import DecisionTreeClassifier
from sklearn.externals import joblib

# Get the dataset
dataset = pd.read_csv('master_info_final_v12_conversion.csv')

# Split the dataset into features and labels
X = dataset[dataset[['Happy', 'Stress', 'Eyes']]]
y = dataset[dataset['phenotype']]

# Split the dataset into training and testing data
X_train, X_test, y_train, y_test = train_test_split(X, y)

# Build the classifier and make prediction
classifier = DecisionTreeClassifier()
classifier.fit(X_train, y_train)
prediction = classifier.predict(X_test)

# Print the confusion matrix
print(confusion_matrix(y_test, prediction))

# Save the model to disk
joblib.dump(classifier, 'classifier.joblib')

Here is a snapshot of my data:

name	rating	phenotype	Happy	Stress	Eyes
tommy	7.1	boy	56	23	19
jill	2.3	girl		74	57
carlos	4.4	neither	45

cottontail · Accepted Answer · 2024-01-20 18:22:18Z

This error most commonly occurs when you try to select columns using a dataframe. For example, in the OP, an entire dataframe (instead of a list/array of column names) is used to select columns, which is throwing this error.

X = dataset[dataset[['Happy', 'Stress', 'Eyes']]]  # <----- error
X = dataset[['Happy', 'Stress', 'Eyes']]           # <----- no error

Note that many pd.DataFrame methods such as select_dtypes(), filter(), query(), take() etc. return a dataframe, so use the result as is; don't use it to filter the dataframe again.

df.select_dtypes('int')       # <--- already dataframe
df[df.select_dtypes('int')]   # <--- ValueError: Boolean array expected

df.filter(['col1'])           # <--- already dataframe
df[df.filter(['col1'])]       # <--- ValueError: Boolean array expected

Another case is when you call where() without a boolean condition. For example,

df = pd.DataFrame({'col1': [1, 2, 3], 'col2': ['a', 'b', 'c']})
df.where(df['col2'])                               # <----- error
df.where(df['col2'] == 'a')                        # <----- no error

In fact, if we look at the source code, when you pass a dataframe to __getitem__ (i.e. []), as in the first case, where() is called, so both cases boil down to the same part of the code.

Collectives™ on Stack Overflow

ValueError: Boolean array expected for the condition, not object

1 Answer 1

Comments

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Linked

Related