python_course2's Introduction
Hey there!! Welcome to the next Pyhton course. NumPy Basics Operator Description np.array([1,2,3]) 1d array np.array([(1,2,3),(4,5,6)]) 2d array np.arange(start,stop,step) range array Placeholders Operator Description np.linspace(0,2,9) Add evenly spaced values btw interval to array of length np.zeros((1,2)) Create and array filled with zeros np.ones((1,2)) Creates an array filled with ones np.random.random((5,5)) Creates random array np.empty((2,2)) Creates an empty array Array Syntax Description array.shape Dimensions (Rows,Columns) len(array) Length of Array array.ndim Number of Array Dimensions array.dtype Data Type array.astype(type) Converts to Data Type type(array) Type of Array Copying/Sorting Operators Description np.copy(array) Creates copy of array other = array.copy() Creates deep copy of array array.sort() Sorts an array array.sort(axis=0) Sorts axis of array Array Manipulation Adding or Removing Elements Operator Description np.append(a,b) Append items to array np.insert(array, 1, 2, axis) Insert items into array at axis 0 or 1 np.resize((2,4)) Resize array to shape(2,4) np.delete(array,1,axis) Deletes items from array Combining Arrays Operator Description np.concatenate((a,b),axis=0) Concatenates 2 arrays, adds to end np.vstack((a,b)) Stack array row-wise np.hstack((a,b)) Stack array column wise Splitting Arrays Operator Description numpy.split() Split an array into multiple sub-arrays. np.array_split(array, 3) Split an array in sub-arrays of (nearly) identical size numpy.hsplit(array, 3) Split the array horizontally at 3rd index More Operator Description other = ndarray.flatten() Flattens a 2d array to 1d array = np.transpose(other) array.T Transpose array inverse = np.linalg.inv(matrix) Inverse of a given matrix Mathematics Operations Operator Description np.add(x,y) x + y Addition np.substract(x,y) x - y Subtraction np.divide(x,y) x / y Division np.multiply(x,y) x @ y Multiplication np.sqrt(x) Square Root np.sin(x) Element-wise sine np.cos(x) Element-wise cosine np.log(x) Element-wise natural log np.dot(x,y) Dot product np.roots([1,0,-4]) Roots of a given polynomial coefficients Comparison Operator Description == Equal != Not equal < Smaller than > Greater than <= Smaller than or equal >= Greater than or equal np.array_equal(x,y) Array-wise comparison Basic Statistics Operator Description np.mean(array) Mean np.median(array) Median array.corrcoef() Correlation Coefficient np.std(array) Standard Deviation More Operator Description array.sum() Array-wise sum array.min() Array-wise minimum value array.max(axis=0) Maximum value of specified axis array.cumsum(axis=0) Cumulative sum of specified axis Slicing and Subsetting Operator Description array[i] 1d array at index i array[i,j] 2d array at index[i][j] array[i<4] Boolean Indexing, see Tricks array[0:3] Select items of index 0, 1 and 2 array[0:2,1] Select items of rows 0 and 1 at column 1 array[:1] Select items of row 0 (equals array[0:1, :]) array[1:2, :] Select items of row 1 [comment]: <> ( array[1,...] array[ : :-1] Reverses array
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