- For (target customers)
- Who must (solve a specific problem)
- Our product is a new (new product category)
- That provides (key breakthrough benefit vs. current way of doing things – which solves dilemma)
- Unlike (competitor in new category)
- We have (whole product most relevant for you)
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| <?php | |
| /** | |
| * Convert a comma separated file into an associated array. | |
| * The first row should contain the array keys. | |
| * | |
| * Example: | |
| * | |
| * @param string $filename Path to the CSV file | |
| * @param string $delimiter The separator used in the file | |
| * @return array |
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| i | |
| me | |
| my | |
| myself | |
| we | |
| our | |
| ours | |
| ourselves | |
| you | |
| your |
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| #!/usr/bin/env python | |
| """ | |
| ===================================== | |
| PEP 20 (The Zen of Python) by example | |
| ===================================== | |
| Usage: %prog | |
| :Author: Hunter Blanks, hblanks@artifex.org / hblanks@monetate.com |
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| def get_fib(n, start): | |
| '''(int, int) -> int | |
| Returns the nth Fibonacci number where start defines whether the squence | |
| starts at 0 or 1 and n is a whole number greater than or equal to 1 | |
| >>>get_fib(1,0) | |
| 0 | |
| >>>get_fib(1,1) | |
| 1 |
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| import random | |
| ################################################################################ | |
| def main(): | |
| table = Table(['Matthew', 'Mark', 'Luke', 'John']) | |
| table.deal_cards() | |
| table.play_all() | |
| def print_underline(string, line): |
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| # --------------------------------------------------------------------------- | |
| # | |
| # Description: This file holds all my BASH configurations and aliases | |
| # | |
| # Sections: | |
| # 1. Environment Configuration | |
| # 2. Make Terminal Better (remapping defaults and adding functionality) | |
| # 3. File and Folder Management | |
| # 4. Searching | |
| # 5. Process Management |
A personal diary of DataFrame munging over the years.
Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)
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| """ | |
| Generate PDF reports from data included in several Pandas DataFrames | |
| From pbpython.com | |
| """ | |
| from __future__ import print_function | |
| import pandas as pd | |
| import numpy as np | |
| import argparse | |
| from jinja2 import Environment, FileSystemLoader | |
| from weasyprint import HTML |
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| // returns an array of localStorage items in key/value pairs based on a query parameter | |
| // returns all localStorage items if query isn't specified | |
| // query can be a string or a RegExp object | |
| function findLocalItems (query) { | |
| var i, results = []; | |
| for (i in localStorage) { | |
| if (localStorage.hasOwnProperty(i)) { | |
| if (i.match(query) || (!query && typeof i === 'string')) { | |
| value = JSON.parse(localStorage.getItem(i)); |
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