- What is numpy?
- Numpy Arrays Vs Python Sequences
- Creating Numpy Arrays
- Array Attributes
- Changing Datatype
- Array Operations
- Array Functions
- Indexing and Slicing
- Iterating
- Reshaping
- Stacking
- Splitting
- speed, memory
- Advanced Indexing
- Broadcasting
- Broadcasting Rules
- Working with mathematical formulas
- Working with missing values
- Plotting Graphs
- np.sort
- np.append
- np.concatenate
- np.unique
- np.expand_dims
- np.where
- np.argmax
- np.cumsum
- np.percentile
- np.histogram
- np.corrcoef
- np.isin
- np.flip
- np.put
- np.delete
- np.union1d()
- np.intersect1d()
- np.setdiff1d()
- np.setxor1d()
- np.in1d()
- np.clip
import numpy as np
arr = np.array( , dtype=)
np.arange()
np.reshape()
np.ones()
np.zeros()
np.random.random()
np.linspace()
np.identity()
arr.ndim
arr.shape
arr.size
arr.itemsize
arr.dtype
arr.T
np.round()
np.floor()
np.ceil()
np.min()
np.max()
np.sum()
np.prod(,axis=0)
np.mean()
np.median()
np.std()
np.var(,axis=1)
np.sin()
np.dot()
np.exp()
arr.astype(np.int32)
np.transpose()
np.nditer()
np.ravel()
np.hstack()
np.vstack()
np.hsplit()
np.vsplit()
np.isnan()
np.sort( , axis=)
np.append( , axis=)
np.concatenate( ,axis=)
np.unique()
np.expand_dims( ,axis=)
np.where()
np.argmax( ,axis=)
np.argmin( ,axis=)
np.cumsum( ,axis=)
np.cumprod( ,axis=)
np.percentile( , )
np.histogram( ,bins=)
np.corrcoef()
np.isin( , )
np.flip( ,axis=)
np.put()
np.delete()
np.union1d()
np.intersect1d()
np.setdiff1d()
np.setxor1d()
np.in1d()
np.clip(a, a_min=, a_max=)