• lib Load
• Data Structure:
  • DataFramework
    • DF Information:
• ndarray
  • Create
  • Operations
    • Vectorization
• Useful functions
• copy or in-place

lib Load

import numpy as np

Data Structure:

1. Series
2. DataFramework: A 2-D labeled data structure with columns of potentially different types.

DataFramework

DF Information:

df.index

df.columns

ndarray

1. n multi dimension array
2. A generic multidimensional container for homogeneous data, so it should be same type.
3. It will convert type into homogeneous type

Create

1.

data1 = [1,2,3,4] arr = np.array(data1) arr = np.array(data1, dtype=np.float64)

out: array([1,2,3,4])

1. Use zeros or ones

   np.zeros(10) np.ones(11)

2. Use arange

   np.arange(15)

3. Use eye/ identity to create a Square N x N identity matrix

Operations

Vectorization

arr * arr arr - arr

Useful functions

• dtype

  data.dtype

• ndim

  arr2.ndim

• shape

• asarray

copy or in-place

1. If you want a copy of a slice of an ndarray instead of view, you will need to explicitly copy the array. Use arr[5:8].copy()