sainathadapa

def glimpse(df, maxvals=10, maxlen=110):
    print('Shape: ', df.shape)
    
    def pad(y):
        max_len = max([len(x) for x in y])
        return [x.ljust(max_len) for x in y]
    
    # Column Name
    toprnt = pad(df.columns.tolist())
    

akesling

import os
import struct
import numpy as np

"""
MNist loading helper for Python 2.7.

For Python 3.x, see https://gist.github.com/akesling/42393ccb868125071fdea77d98a0d2f0

Loosely inspired by http://abel.ee.ucla.edu/cvxopt/_downloads/mnist.py

jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD