View wordcloud_gen_agenda.R
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suppressMessages(library(odbc)) | |
suppressMessages(library(DBI)) | |
suppressMessages(library(RPostgreSQL)) | |
suppressMessages(library(tidyverse)) | |
suppressMessages(library(tidytext)) | |
suppressMessages(library(wordcloud2)) | |
suppressMessages(library(lubridate)) | |
library(config) | |
library(ngram) |
View analise_gettr.R
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library(tidyverse) | |
library(lubridate) | |
library(clipr) | |
ptbr <- read.csv("dados_pt.csv", header = T) | |
ptbr$lang <- "português" | |
eng <- read.csv("dados_eng.csv", header = T) | |
eng$lang <- "inglês" |
View query.csv
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screen_name | semana | med | var_semana | |
---|---|---|---|---|
cirogomes | 2021-11-29 | 1289939.42857143 | 0.21663569941901 | |
cirogomes | 2021-12-06 | 1292566.57142857 | 0.203664048012886 | |
cirogomes | 2021-12-13 | 1295949 | 0.261683123035605 | |
cirogomes | 2021-12-20 | 1298984.42857143 | 0.23422438471179 | |
cirogomes | 2021-12-27 | 1301667.71428571 | 0.20656796611771 | |
cirogomes | 2022-01-03 | 1304274.71428571 | 0.200281528948465 | |
cirogomes | 2022-01-10 | 1307455.28571429 | 0.243857478316079 | |
cirogomes | 2022-01-17 | 1310957.42857143 | 0.26785947446224 | |
cirogomes | 2022-01-24 | 1316434.71428571 | 0.417808053481528 |
View blogs_atlas.R
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library(tidyverse) | |
library(newsatlasbr) | |
library(clipr) | |
atlas_signin(email = "dados@voltdata.info", password = "senhatokenaberto") | |
dados <- newsatlasbr::organizations_state(uf = "all") | |
desertos <- newsatlasbr::news_deserts() |
View emplacamentos.R
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library(tidyverse) | |
emplacamentos <- read_delim("https://docs.google.com/spreadsheets/d/e/2PACX-1vRY5Wc7j9qAEbStZioZBGEQB_o4S_eyJnVca8oP7gGTafvg8ZwDdZWYkzAx_455KOs3Q9uZQ9qSFIZ3/pub?gid=0&single=true&output=csv", delim = ",", locale = locale(grouping_mark = ".")) | |
emplacamentos$Ano <- as.Date(paste0(emplacamentos$Ano, "-01-01")) | |
marcas <- read_delim("https://docs.google.com/spreadsheets/d/e/2PACX-1vRY5Wc7j9qAEbStZioZBGEQB_o4S_eyJnVca8oP7gGTafvg8ZwDdZWYkzAx_455KOs3Q9uZQ9qSFIZ3/pub?gid=794101571&single=true&output=csv", delim = ",", locale = locale(grouping_mark = ".")) | |
marcas$Ano <- as.Date(paste0(marcas$Ano, "-01-01")) |
View atlas_connect.py
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# -*- coding: utf-8 | |
# Abraji (https://www.abraji.org.br) | |
# Reinaldo Chaves (reinaldo@abraji.org.br) | |
# Programa acessar a API do Atlas da Notícia (https://www.atlas.jor.br/) | |
# É necessário antes se cadastrar, veja como aqui: https://www.atlas.jor.br/plataforma/utilizarAPI/ | |
import requests | |
import pandas as pd | |
# Link da requisição principal |
View extrai_csvs.R
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library(glue) | |
library(stringr) | |
library(deflateBR) | |
library(lubridate) | |
# 2017 e 2018 usam .CSV com caixa alta | |
# 2019 e 2019 usam .csv com minúsculas | |
# Não há dados para março de 2019 | |
url <- "http://repositorio.dados.gov.br/segrt/QUARENTENA_{mes}{ano}.CSV" |
View bid-waze_analise.R
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library(tidyverse) | |
library(clipr) | |
# BRASIL - GERAL | |
# média de distanciamento social | |
bid %>% | |
filter(data> '2020-03-15' & region_type == "country" & dia_semana != "domingo") %>% | |
summarise(media = mean((ratio_20 - 1) * 100), mediana = median((ratio_20 - 1) * 100)) | |
# distanciamento social por dia da semana |
View analise_popularidade.R
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library(lubridate) | |
library(scales) | |
library(tidyverse) | |
# regulariza o formato da data do tweet, corrige para fuso certo | |
d$created_at <- as.POSIXct(strptime(d$created_at, "%Y-%m-%d %H:%M:%S")) | |
d$created_at <- d$created_at - hours(3) | |
d$dia <- as.POSIXct(strptime(d$created_at, "%Y-%m-%d")) | |
# cria coluna com minuto arredondado |
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