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@why-not
why-not / gist:4582705
Last active October 2, 2025 03:23
Pandas recipe. I find pandas indexing counter intuitive, perhaps my intuitions were shaped by many years in the imperative world. I am collecting some recipes to do things quickly in pandas & to jog my memory.
"""making a dataframe"""
df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))
"""quick way to create an interesting data frame to try things out"""
df = pd.DataFrame(np.random.randn(5, 4), columns=['a', 'b', 'c', 'd'])
"""convert a dictionary into a DataFrame"""
"""make the keys into columns"""
df = pd.DataFrame(dic, index=[0])
@pkgw
pkgw / otpounce.py
Created August 26, 2012 04:01
Pounce on an OpenTable reservation
#! /usr/bin/env python
"""
Pounce on an open OpenTable reservation.
"""
import sys, os, time, re, mechanize, gtk, webkit, threading, random
rid = 1180 # OpenTable restaurant ID; 1180 = French Laundry
people_choices = [3, 3, 3, 4] # number of people to request for; cycles through choices
@jboner
jboner / latency.txt
Last active September 7, 2026 12:30
Latency Numbers Every Programmer Should Know
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