Added an effect on mouse hover card.
Example here
Images without copyright.
Added an effect on mouse hover card.
Example here
Images without copyright.
# Scikit Learn Encoders | |
from sklearn.preprocessing import LabelEncoder | |
import pandas as pd | |
data_frame = pd.read_csv('data_file') | |
target_feature = 'Feature Label' | |
# use encoder to tranform |
Primeiro precisamos criar um virtualenv e ativa-la, para isolarmos as dependencias de python somente para esse projeto.
$ python3 -m venv $HOME/.venvs/metro_notify
$ source $HOME/.venvs/metro_notify/bin/activate
Depois é necessário instalarmos as bibliotecas necessárias para fazermos o webscrappin e o BOT no IFTTT: e Requests
if (window.navigator && window.navigator.msSaveOrOpenBlob) { | |
const data = "<base64 string/>" | |
const fileName = 'file.pdf' | |
const byteCharacters = atob(data) | |
let byteNumbers = new Array(byteCharacters.length) | |
for (var i = 0; i < byteCharacters.length; i++) { | |
byteNumbers[i] = byteCharacters.charCodeAt(i) | |
} |
class Aircraft: | |
def __init__(self, registration, model, num_rows, num_seats_per_row): | |
self._registration = registration | |
self._model = model | |
self._num_rows = num_rows | |
self._num_seats_per_row = num_seats_per_row | |
def registration(self): |
# LIST | |
numbers = [x * x for x in range(1, 6)] | |
# [1, 4, 9, 16, 25, 36] | |
# SET | |
numbers = {x * x for x in range(1, 6)} | |
# {1, 4, 36, 9, 16, 25} | |