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import requests | |
from bs4 import BeautifulSoup | |
requests.packages.urllib3.util.ssl_.DEFAULT_CIPHERS = 'ALL:@SECLEVEL=1' | |
payload = {'pagina': '1', 'data': '07/01/2019'} | |
url = 'https://antigo.agu.gov.br/agenda-autoridades/' | |
r = requests.post(url, data=payload, verify=False) |
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index | user_name | view_count | caption | comment_count | forward_count | kwai_id | like_count | timestamp | url | termo | |
---|---|---|---|---|---|---|---|---|---|---|---|
0 | D&W #Gospel 💜🙏💜 | 1590290 | #Damares #A_batalha_do_Arcanjo | 17623 | 116416 | dwgospel | 283278 | 1639007361892 | http://ak-eg-cdn.kwai.net/upic/2021/12/09/07/BMjAyMTEyMDkwNzQ2MTBfMTUwMDAwOTU4NDA3MDk5XzE1MDA2MDM3MDM1MzE3NF8yXzM=_b_B747796555f6034c2c6906c6af056f0ad.mp4?tag=1-1665436177-sr-0-1udswg86ug-7e3d736c366af8bc | damares | |
1 | D&W #Gospel 💜🙏💜 | 589784 | #Damares #Um_Novo_Vencedor | 11901 | 54064 | dwgospel | 124453 | 1636659853728 | http://ak-eg-cdn.kwai.net/upic/2021/11/12/03/BMjAyMTExMTIwMzM4MTZfMTUwMDAwOTU4NDA3MDk5XzE1MDA2MDMxMzYzNDEzOF8yXzM=_b_B2fafcb4a990c615112d5a666ec306c94.mp4?tag=1-1665436177-sr-0-jydcn38emw-e2a065a46554293e | damares | |
6 | #Denilson🏆JTV🏆 | 106764 | #kwaistatus #consolador #damares # | 635 | 8753 | D1968 | 28309 | 1649361552013 | http://ak-eg-cdn.kwai.net/upic/2022/04/08/03/BMjAyMjA0MDgwMzUzMzRfMTUwMDAwMDQ3MDI1MTg5XzE1MDA2MDY5NDA4NjU0NF8yXzM=_b_B5b5f5720007e4409b3d1a9506fb42ecb.mp4?tag=1-1665436177-sr-0-sm6xeqieh7-236669cbd70524fc | dam |
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#!/bin/bash | |
for file in * | |
do | |
if [ -d "$file" ] | |
then | |
cd "$file" | |
for f in * | |
do | |
mv "$f" "${file}_${f}" |
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# Baseado na função criada pela comunidade da Python Brasil, com pequenas mudanças | |
# Créditos: https://rgth.co/pt-br/blog/criando-a-foto-oficial-da-python-brasil-2020/ | |
from PIL import Image | |
from pathlib import Path | |
coluna = 12 | |
linha = 7 | |
quadrado = 200 |
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br_states = {"Acre": "AC", "Alagoas": "AL", "Amapá": "AP", "Amazonas": "AM", "Bahia": "BA", "Ceará": "CE", | |
"Distrito Federal": "DF", "Espírito Santo": "ES", "Goiás": "GO", "Maranhão": "MA", | |
"Mato Grosso": "MT","Mato Grosso do Sul": "MS","Minas Gerais":"MG", "Paraná": "PR", | |
"Paraíba": "PB", "Pará": "PA", "Pernambuco": "PE", "Piauí": "PI", "Rio Grande do Norte": "RN", | |
"Rio Grande do Sul": "RS", "Rio de Janeiro": "RJ", "Rondônia": "RO", "Roraima": "RR", | |
"São Paulo": "SP", "Santa Catarina": "SC", "Sergipe": "SE", "Tocantins": "TO" | |
} |
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# Confusion matrix order: | |
# Thus in binary classification, the order is: | |
# [true negatives, false negatives] | |
# [true positive, false negatives] | |
from sklearn.metrics import confusion_matrix | |
import pandas as pd | |
real = ["cat", "ant", "cat","ant","cat"] | |
prediction = ["ant", "ant", "cat","cat","ant"] |
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Serial #,County,Type,Class,Premises Name,DBA,Address,Address 2,City,State,Zip,Date Inactive,Latitude,Longitude,Accuracy Score,Accuracy Type,Number,Street,Unit Type,Unit Number,City,State,County,Zip,Country,Source | |
2210254,ALBA,TW,344,POUR DECISIONS INC,BEER BONES TAP ROOM,594 NEW LOUDON RD,,LATHAM,NY,12110,3/12/2019 15:49:39,42.751147,-73.760234,0.6,street_center,,New Loudon Rd,,,Latham,NY,Albany County,12110,US,TIGER/Line® dataset from the US Census Bureau | |
2212813,ALBA,WS,308,FIREBALL FARM & CIDERS LLC,TILTED SHED CIDERWORKS,7761 BELL RD,,WINDSOR,CA,95492,3/12/2019 14:05:19,38.539658,-122.810046,1,range_interpolation,7761,Bell Rd,,,Windsor,CA,Sonoma County,95492,US,TIGER/Line® dataset from the US Census Bureau | |
1307974,BRON,A,122,1 WESTFIELD MARKET & DELI CORP,,3202 AMPERE AVE,,BRONX,NY,10465,3/14/2019 11:14:09,40.84614,-73.82095,1,rooftop,3202,Ampere Ave,,,Bronx,NY,Bronx County,10465,US,City of New York | |
1307974,BRON,A,122,1 WESTFIELD MARKET & DELI CORP,,3202 AMPERE AVE,,BRONX,NY,10465,3/14/2019 09:18:32,40.84 |
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#!/bin/bash | |
consolidado="./consolidado.shp" | |
for i in $(find . -name '*.shp'); do | |
if [ ! -f "$consolidated_file" ]; then | |
# usa o primeiro arquivo para criar o arquivo final | |
ogr2ogr -f "ESRI Shapefile" $consolidated_file $i | |
else | |
# anexa os demais arquivos no consolidado | |
ogr2ogr -f "ESRI Shapefile" -update -append $consolidated_file $i | |
fi |
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#!/usr/bin/env python | |
# coding: utf-8 | |
# In[2]: | |
import pandas as pd | |
import nltk | |
import itertools | |
from nltk.corpus import stopwords | |
from gensim import corpora, models | |
from nltk.stem import PorterStemmer |
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# github.com/belisards/coronabr/ | |
library(tidyverse) | |
df <- read.csv("dados/corona_brasil.csv") %>% | |
mutate(date = as.Date(date)) | |
ivis <- df %>% select(-local,-deads,-index,-confirmado) %>% | |
filter(date < "2020-03-19") %>% arrange(date) |
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