Title: Delete Observations With Missing Values
Slug: delete_observations_with_missing_values
Summary: How to delete observations with missing values.
Date: 2017-09-05 12:00
Category: Machine Learning
Tags: Preprocessing Structured Data
Authors: Chris Albon

Preliminaries



In [1]:

    
# Load libraries
import numpy as np
import pandas as pd

Create Feature Matrix



In [2]:

    
# Create feature matrix
X = np.array([[1.1, 11.1], 
              [2.2, 22.2], 
              [3.3, 33.3], 
              [4.4, 44.4], 
              [np.nan, 55]])

Delete Observations With Missing Values



In [3]:

    
# Remove observations with missing values
X[~np.isnan(X).any(axis=1)]









    Out[3]:





array([[  1.1,  11.1],
       [  2.2,  22.2],
       [  3.3,  33.3],
       [  4.4,  44.4]])