Python Scikit learn: Get the number of observations, missing values and nan values
Python Machine learning Iris Basic: Exercise-3 with Solution
Write a Python program to get the number of observations, missing values and nan values.
Sample Solution:
Python Code:
import pandas as pd
iris = pd.read_csv("iris.csv")
print(iris.info())
Samole Output:
<class 'pandas.core.frame.DataFrame'> RangeIndex: 150 entries, 0 to 149 Data columns (total 6 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 Id 150 non-null int64 1 SepalLengthCm 150 non-null float64 2 SepalWidthCm 150 non-null float64 3 PetalLengthCm 150 non-null float64 4 PetalWidthCm 150 non-null float64 5 Species 150 non-null object dtypes: float64(4), int64(1), object(1) memory usage: 7.2+ KB None
Python Code Editor:
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Previous: Write a Python program using Scikit-learn to print the keys, number of rows-columns, feature names and the description of the Iris data.
Next: Write a Python program to create a 2-D array with ones on the diagonal and zeros elsewhere. Now convert the NumPy array to a SciPy sparse matrix in CSR format.
What is the difficulty level of this exercise?
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