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tibble::tibble() | |
tribunais <- forosCNJ::da_tribunal |> | |
dplyr::filter(id_justica == 8) |> | |
dplyr::pull(sigla) |> | |
tolower() | |
endpoints <- glue::glue( | |
"https://api-publica.datajud.cnj.jus.br/api_publica_{tribunais}/_search" | |
) |
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# Endpoint for SOAP requests | |
endpoint_url <- 'https://www.cnj.jus.br/corregedoria/justica_aberta/ws.php' | |
# XML payload, replace the method name and parameters as per actual API | |
# This is a simplified example assuming a SOAP method called 'getServentiaJudicial' that accepts 'seq_orgao' as a parameter | |
xml_payload <- '<soapenv:Envelope xmlns:soapenv="http://schemas.xmlsoap.org/soap/envelope/" xmlns:cor="https://www.cnj.jus.br/corregedoria/justica_aberta/ws.php"> | |
<soapenv:Header/> | |
<soapenv:Body> | |
<cor:pesquisarServentiasJudiciais> | |
<!--Optional:--> |
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# reciclou mas deu um warning porque não é múltiplo | |
tibble::tibble(x = c('a', 'b', 'c')) |> | |
dplyr::filter(x == c('a', 'b')) | |
#> Warning: There was 1 warning in `dplyr::filter()`. | |
#> ℹ In argument: `x == c("a", "b")`. | |
#> Caused by warning in `x == c("a", "b")`: | |
#> ! comprimento do objeto maior não é múltiplo do comprimento do objeto menor | |
#> # A tibble: 2 × 1 | |
#> x | |
#> <chr> |
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# arrumação dos dados para pesquisa | |
moral_raw <- readxl::read_excel("moral.xlsx") | |
sexual_raw <- readxl::read_excel("sexual.xlsx") | |
moral <- moral_raw |> | |
janitor::clean_names() |> | |
dplyr::mutate( | |
no_processo_original = no_processo, | |
no_processo = abjutils::clean_cnj(no_processo) |
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pdf_full <- pdftools::pdf_text("pdf_full.pdf") | |
# 33-36, 38-39, 41-46, 48-49, 52-54, 56-61, 63-72, 74-77, 79-83, 85-91, 93-96, 98-100, 102-105 | |
paginas <- c( | |
33:36, 38:39, 41:46, 48:49, | |
52:54, 56:61, 63:72, 74:77, | |
79:83, 85:91, 93:96, 98:100, |
We can make this file beautiful and searchable if this error is corrected: It looks like row 2 should actually have 1 column, instead of 2. in line 1.
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Category: All categories | |
Month,deu ruim: (Brazil) | |
2004-01,0 | |
2004-02,0 | |
2004-03,0 | |
2004-04,0 | |
2004-05,0 | |
2004-06,0 | |
2004-07,0 |
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import pandas as pd | |
import numpy as np | |
import matplotlib.pyplot as plt | |
from sklearn.linear_model import LogisticRegression | |
# Seed for reproducibility | |
np.random.seed(42) | |
# Generate synthetic data | |
n = 500 # Number of samples |
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library(rugarch) | |
start_date <- '2018-01-01' | |
# esses são ativos de fundos imobiliários que eu ja tive | |
# e queria saber fiz um péssimo investimento | |
# ou apenas ruim. | |
ativos <- c( | |
"HGRE11.SA", | |
"BTLG11.SA", | |
"HGRU11.SA", |
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######################################## | |
# Time-varying parameter CAPM | |
######################################## | |
library(ggplot2) | |
library(BatchGetSymbols) | |
library(dplyr) | |
library(tidyr) | |
library(dlm) |
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ssp_criterios <- ssp_cortes %>% | |
mutate(corte = as.numeric(corte) / 10) %>% | |
gather(tipo_contagem, valor, maior, menor, total) %>% | |
unite(tipo_rubrica_contagem, tipo_rubrica, tipo_contagem, sep = "_") %>% | |
spread(tipo_rubrica_contagem, valor) %>% | |
mutate(soma = trafico_menor + | |
input$peso * porte_maior, | |
prop = trafico_menor / trafico_total + | |
input$peso * porte_maior / porte_total) %>% | |
group_by(droga_tipo) %>% |
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