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Numpy
Benefits of using NumPy
Creating NumPy ndarrays
Using Built-in Functions to Create ndarrays
Accessing, Deleting, and Inserting Elements Into ndarrays
Slicing ndarrays
Boolean Indexing, Set Operations, and Sorting
Arithmetic operations and Broadcasting
Glossary
Numpy Mini Project
Numpy Mini Project
pandas
Datasets
pandas basics
creating pandas series
Accessing and Deleting Elements in Pandas Series
Arithmetic Operations on Pandas Series
Creating Pandas DataFrames
Accessing Elements in Pandas DataFrames
Dealing with NaN
Loading Data into a pandas DataFrame
Glossary
Pandas Mini-Project
Matplotlib and Seaborn Part 1
DataSet
Lesson Overview
Bar Charts
Absolute vs Relative Frequency
Counting Missing Data
Pie Charts
Histograms
Figures, Axes, and Subplots
Choosing a Plot for Discrete Data
Descriptive Statistics, Outliers, and Axis Limits
Scales and Transformations
Glossary
Extra: Kernel Density Estimation
Practice
Matplotlib and Seaborn Part 2
Datasets
Scatterplots and Correlation
Overplotting, Transparency, and Jitter
Heat Maps
Violin Plots
Box Plots
Clustered Bar Charts
Faceting
Adapted Bar Charts
Line Plots
Lession Summary
Practice
Linear Algebra
Working with Equations
SkLearn
PreProcessing
Data Cleaning
Feature Selection
Transformations
Machine Learning
Intro
Data Visualizations
Data Wrangling
Linear Regression
Linear Regression & Inference 2
K-Nearest Neighbors
K-Nearest Neighbors 2
Bias report
Artificial intelligence
Intro
Neural Networks
Fine-Tuning Neural Networks
Convolutional Neural Networks
Deep Learning Project
Natural language processing
Natural language processing 2
Neural Network for NLP
Stable Diffusion
Jupyter Lite
Free Resources
Discussion Page
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Glossary
Glossary
Below is the summary of all the functions and methods that you learned in this lesson:
numpy.ndarray.dtype
Return the data-type of the elements of the array. Remember, arrays are homogeneous.
numpy.ndarray.ndim
Return the
number
of array-dimensions (rank), e.g., it will return 2 for a 4x3 array.
numpy.ndarray.shape
Return a tuple representing the array dimensions, e.g., it will return (rows,columns) for a rank 2 array.
numpy.ndarray.size
Return the number of elements present in the array.
numpy.save
Save an array to .npy (numpy) format.
numpy.load
Load array from the .npy files.
numpy.random.random
Return random floats values from the interval [0.0, 1.0), in a specified shape.
numpy.random.randint
Return random integers from the half-open interval [a, b), in a specified shape.
numpy.random.normal
Return random samples from a Gaussian (normal) distribution.
numpy.random.permutation
Return a randomly permuted sequence from the given list
numpy.reshape
numpy.ndarray.reshape
Returns an array containing the same elements with a new shape, without affecting the the original array.
Category: Array Creation
numpy.ones
Return a new array of given shape and type, filled with 1s.
numpy.zeros
Return a new array of given shape and type, filled with 0s.
numpy.full
Return a new array of given shape and type, filled with a specific value.
numpy.eye
Return a 2-D array with 1s on the diagonal and 0s elsewhere.
numpy.diag
Extract the diagonal elements.
numpy.unique
Return the sorted unique elements of an array.
numpy.array
Create an n-dimensional array.
numpy.arange
Return evenly spaced values within a given half-open interval [a, b).
numpy.linspace
Return evenly spaced numbers over a specified interval [a,b].
numpy.ndarray.copy
Returns a copy of the array.
Category: Operating with Elements and Indices
numpy.insert
Insert values along the given axis before the specified indices.
numpy.delete
Return a new array, after deleting sub-arrays along a specified axis.
numpy.append
Append values at the end of the specified array.
numpy.hstack
Return a stacked array formed by stacking the given arrays in sequence horizontally (column-wise).
numpy.vstack
Return a stacked array formed by stacking the given arrays, will be at least 2-D, in sequence vertically (row-wise).
numpy.sort
Return a sorted copy of an array.
numpy.ndarray.sort
Sort an array in-place.
Category: Set Operations
numpy.intersect1d
Find the intersection of two arrays.
numpy.setdiff1d
Find the set difference of two arrays.
numpy.union1d
Return the unique, sorted array of values that are in either of the two input arrays.
Category: Arithmetic and Statistical Operations
numpy.add
Element-wise add given arrays
numpy.subtract
Subtract arguments of given arrays, element-wise.
numpy.multiply
Multiply arguments of given arrays, element-wise.
numpy.divide
Returns a true division of the inputs, element-wise.
numpy.exp
Calculate the exponential of all elements in the input array.
numpy.power
First array elements raised to powers from second array, element-wise.
numpy.sqrt
Return the non-negative square-root of an array, element-wise.
numpy.ndarray.min
Return the minimum along the specified axis.
numpy.ndarray.max
Return the maximum along a given axis.
numpy.mean
numpy.ndarray.mean
Compute the arithmetic mean along the specified axis.
numpy.median
Compute the median along the specified axis.
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