Problem: would like to use pivot_table [1] to pivot and ignore irrelevant columns
in the DataFrame.
Given the DataFrame
df = pd.DataFrame(
{| <script lang="ts" generics="T"> | |
| // SVELTE | |
| import { tick, untrack } from 'svelte'; | |
| // TYPES | |
| import type { Snippet } from 'svelte'; | |
| // ═══════════════════════ | |
| // 1. PROPS | |
| // ═══════════════════════ |
| #!/usr/bin/python3 | |
| """ | |
| Copyright 2021 Mygod | |
| Licensed under the Apache License, Version 2.0 (the "License"); | |
| you may not use this file except in compliance with the License. | |
| You may obtain a copy of the License at | |
| http://www.apache.org/licenses/LICENSE-2.0 |
| import psycopg2 | |
| from contextlib import closing | |
| """ | |
| Demonstrate that contextmanagers for closing and committing don't play well together without autocommit | |
| Only the noclosing function can run without error | |
| """ |
I'm going to walk you through the steps for setting up a AWS Lambda to talk to the internet and a VPC. Let's dive in.
So it might be really unintuitive at first but lambda functions have three states.
| /* | |
| * derivative work of Matheus de Oliveira's json_manipulator.sql | |
| * https://gist.github.com/matheusoliveira/9488951 | |
| * | |
| * adapted to support postgresql 9.4 jsonb type | |
| * no warranties or guarantees of any kind are implied or offered | |
| * | |
| * license is as Matheus conferred it on 4/9/2015: | |
| * matheusoliveira commented on Apr 9 | |
| * @hannes-landeholm, I'd like to take credit if you share them |
If you were to give recommendations to your "little brother/sister" on things that they need to do to become a data scientist, what would those things be?
I think the "Data Science Venn Diagram" (http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram) is a great place to start. You need three things to be a good data scientist:
| import pandas as pd | |
| from matplotlib import pyplot as plt | |
| import matplotlib as mpl | |
| import seaborn as sns | |
| %matplotlib inline | |
| #Read in data & create total column | |
| stacked_bar_data = pd.read_csv("C:\stacked_bar.csv") | |
| stacked_bar_data["total"] = stacked_bar_data.Series1 + stacked_bar_data.Series2 |
Dionysis Zindros, National Technical University of Athens [email protected]
pseudonymous anonymous web-of-trust identity trust bitcoin namecoin proof-of-burn timelock decentralized anonymous marketplace openbazaar
Dionysis Zindros, National Technical University of Athens [email protected]
pseudonymous anonymous web-of-trust identity trust bitcoin namecoin proof-of-burn timelock decentralized anonymous marketplace openbazaar