João Cavalcante jvfe

## spec.json
{
  "config": {"view": {"continuousWidth": 400, "continuousHeight": 300}},
  "vconcat": [
    {
      "hconcat": [
        {
          "mark": {"type": "line", "point": true},
          "encoding": {
            "color": {
              "condition": {"value": "purple", "selection": "selector055"},

## spec2.json
{
  "config": {"view": {"continuousWidth": 400, "continuousHeight": 300}},
  "vconcat": [
    {
      "hconcat": [
        {
          "mark": "point",
          "encoding": {
            "color": {
              "condition": {"value": "purple", "selection": "selector079"},

## get_covid_data_jhu.py
import pandas as pd
import datetime

def get_covid_data_jhu(dt_ini, dt_fim, us_columns = True, country = None):

    date_range = pd.date_range(start = dt_ini, end = dt_fim).to_list()
    string_range = [str(d.date().strftime("%m-%d-%Y")) for d in date_range]

    full_data_list = []
    for dat in string_range:

## get_tibble_gene_summaries.R
get_summary <- function(geneids){
  summary_list <- entrez_summary("gene", id = geneids, ) %>%
    extract_from_esummary(elements = c("uid", "summary"), simplify = TRUE) %>%
    as_tibble() %>%
    unnest()

  gene_names <- summary_list %>%
    slice(1) %>%
    as.character()


## plot_network.py
from bokeh.io import show
from bokeh.models import Range1d, Plot, Circle, HoverTool, MultiLine
from bokeh.models.graphs import NodesAndLinkedEdges
from bokeh.plotting import from_networkx
import networkx as nx

def plot_network(network, tooltip, layout=nx.kamada_kawai_layout):
    """Makes a nice network plot with Bokeh

    Mostly stuff I pieced together from the bokeh tutorials.

## wikidata_utils.py
from collections import defaultdict
import pandas as pd
import requests


def perform_query(query):
    """Performs a SPARQL query to the wikidata endpoint

    Args:
        query: A string containing a functional sparql query

## docx2pdf.sh
#!/bin/bash

libreoffice --headless --convert-to pdf:writer_pdf_Export "$1" --outdir .

## wikidata_shex_checker.py
from pyshex.shex_evaluator import ShExEvaluator
from pyshex.user_agent import SlurpyGraphWithAgent
from pyshex.utils.sparql_query import SPARQLQuery
import pandas as pd


def test_query_against_shex(schema, sparql):
    """Checks the items resulting from a Wikidata query against a shex schema

    Using PyShEx, we can check the validity of multiple items against a predefined

## mkignore
#!/bin/bash

curl https://www.toptal.com/developers/gitignore/api/python,r,linux,visualstudiocode >> .gitignore

## diamond.m8
read1	WP_005581541.1	98.2	40	1	0	129	299	1	57	7.7e-22	113.6
read2	WP_005575885.1	100.0	60	0	0	181	2	1	60	2.2e-24	122.1
read3	WP_005580014.1	100.0	50	0	0	2	151	385	434	3.6e-19	104.8
read4	WP_005576929.1	100.0	98	0	0	296	3	308	405	6.7e-42	180.3
read5	ELY74166.1	98.0	100	2	0	300	1	80	179	7.9e-43	183.3
read5	WP_015233403.1	98.0	100	2	0	300	1	98	197	7.9e-43	183.3
read6	WP_005578121.1	100.0	52	0	0	1	156	124	175	1.6e-22	115.9
read7	WP_005576999.1	92.0	100	8	0	1	300	14	113	1.1e-47	199.5
read8	WP_005579760.1	98.0	100	2	0	2	301	214	313	1.8e-42	182.2
read8	AFZ74922.1	98.0	100	2	0	2	301	188	287	1.8e-42	182.2
	{
	"config": {"view": {"continuousWidth": 400, "continuousHeight": 300}},
	"vconcat": [
	{
	"hconcat": [
	{
	"mark": {"type": "line", "point": true},
	"encoding": {
	"color": {
	"condition": {"value": "purple", "selection": "selector055"},
	import pandas as pd
	import datetime

	def get_covid_data_jhu(dt_ini, dt_fim, us_columns = True, country = None):

	date_range = pd.date_range(start = dt_ini, end = dt_fim).to_list()
	string_range = [str(d.date().strftime("%m-%d-%Y")) for d in date_range]

	full_data_list = []
	for dat in string_range:
	get_summary <- function(geneids){
	summary_list <- entrez_summary("gene", id = geneids, ) %>%
	extract_from_esummary(elements = c("uid", "summary"), simplify = TRUE) %>%
	as_tibble() %>%
	unnest()

	gene_names <- summary_list %>%
	slice(1) %>%
	as.character()
	from bokeh.io import show
	from bokeh.models import Range1d, Plot, Circle, HoverTool, MultiLine
	from bokeh.models.graphs import NodesAndLinkedEdges
	from bokeh.plotting import from_networkx
	import networkx as nx

	def plot_network(network, tooltip, layout=nx.kamada_kawai_layout):
	"""Makes a nice network plot with Bokeh

	Mostly stuff I pieced together from the bokeh tutorials.
	from collections import defaultdict
	import pandas as pd
	import requests


	def perform_query(query):
	"""Performs a SPARQL query to the wikidata endpoint

	Args:
	query: A string containing a functional sparql query
	#!/bin/bash

	libreoffice --headless --convert-to pdf:writer_pdf_Export "$1" --outdir .
	from pyshex.shex_evaluator import ShExEvaluator
	from pyshex.user_agent import SlurpyGraphWithAgent
	from pyshex.utils.sparql_query import SPARQLQuery
	import pandas as pd


	def test_query_against_shex(schema, sparql):
	"""Checks the items resulting from a Wikidata query against a shex schema

	Using PyShEx, we can check the validity of multiple items against a predefined
	#!/bin/bash

	curl https://www.toptal.com/developers/gitignore/api/python,r,linux,visualstudiocode >> .gitignore
	read1 WP_005581541.1 98.2 40 1 0 129 299 1 57 7.7e-22 113.6
	read2 WP_005575885.1 100.0 60 0 0 181 2 1 60 2.2e-24 122.1
	read3 WP_005580014.1 100.0 50 0 0 2 151 385 434 3.6e-19 104.8
	read4 WP_005576929.1 100.0 98 0 0 296 3 308 405 6.7e-42 180.3
	read5 ELY74166.1 98.0 100 2 0 300 1 80 179 7.9e-43 183.3
	read5 WP_015233403.1 98.0 100 2 0 300 1 98 197 7.9e-43 183.3
	read6 WP_005578121.1 100.0 52 0 0 1 156 124 175 1.6e-22 115.9
	read7 WP_005576999.1 92.0 100 8 0 1 300 14 113 1.1e-47 199.5
	read8 WP_005579760.1 98.0 100 2 0 2 301 214 313 1.8e-42 182.2
	read8 AFZ74922.1 98.0 100 2 0 2 301 188 287 1.8e-42 182.2