Preprocessing Data with NumPy
NumPy, ndarrays, Slicing, Random Generators, Importing and Saving Data, Statistics, Data Manipulation, Preprocessing
4.51 (292 reviews)
2,193
students
6.5 hours
content
Dec 2020
last update
$79.99
regular price
What you will learn
Arrays.
The definition of a package/library.
Installing and Upgrading a package.
Navigating the documentation.
A history of NumPy.
The relationship between arrays and vectors.
Arrays vs Lists.
Indexing.
Assigning values to arrays.
Elementwise properties and operations.
Datatypes supported by ndarrays.
Broadcasting and type casting.
Running a function or method over a given axis.
Slicing, Stepwise Slicing, Conditional Slicing
Dimensionality reduction in arrays.
Generating arrays full of identical values.
Generating non-random sequences of data.
Generating random data with Random Generators.
Generating random samples from a random probability distribution.
Importing and exporting data with and from NumPy.
NPY and NPZ files.
Maximums and Minimums.
Percentiles and Quantiles.
Mean and Variance.
Covariance and Correlation.
Calculating histograms.
Higher dimension histograms.
Finding and filling up missing values.
Substituting "filler" values.
Reshaping arrays.
Removing parts of arrays.
Removing parts of individual elements within arrays. (Stripping)
Sorting and Shuffling.
Argument Functions.
Stacking and Concatenating.
Finding the unique values within an array.
A comprehensive practical example of data cleaning and preprocessing.
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3697848
udemy ID
12/11/2020
course created date
12/18/2020
course indexed date
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