#!/usr/bin/env python
# coding: utf-8
import os
import re
import requests
from datetime import datetime
from bs4 import BeautifulSoup
from logya.core import Logya
from logya.path import slugify, target_file
from logya.writer import encode_content, write
logya = Logya()
logya.init_env()
url = 'https://en.wikipedia.org/wiki/Bodyweight_exercise'
html = requests.get(url).text
soup = BeautifulSoup(html, 'lxml')
replacements = {
'bams': 'bam',
'bodybuilders': 'bodybuilder',
'boots': 'boot',
'chairs': 'chair',
'climbers': 'climber',
'crosses': 'cross',
'curls': 'curl',
'darlings': 'darling',
'dips': 'dip',
'dogs': 'dog',
import pandas as pd
from datetime import datetime
from logya.core import Logya
from logya.writer import write, encode_content
parser = argparse.ArgumentParser(
description='Create data map draft based on input CSV and arguments.')
parser.add_argument('input_file', help='Name of the input file.')
parser.add_argument('output_name',
help='Name part of the generated content and CSV files.')
args = parser.parse_args()
L = Logya()
L.init_env()
now = datetime.now()
# World Bank specific data loading and processing
df = pd.read_csv(args.input_file, skiprows=4).dropna(
axis='columns', how='all',
thresh=10).rename(columns={'Country Code': 'iso3'})
years = [str(year) for year in range(1960, now.year + 1) if str(year) in df]
columns = ['iso3'] + years
df_final = df[columns]
# Determine absolute min and max values for use in JS
abs_min = df.min(numeric_only=True).min()
if abs_min > 0 and abs_min < 1:
#!/usr/bin/env python
# coding: utf-8
import os
import re
import requests
from datetime import datetime
from bs4 import BeautifulSoup
from logya.core import Logya
from logya.path import slugify, target_file
from logya.writer import encode_content, write
logya = Logya()
logya.init_env()
url = 'https://en.wikipedia.org/wiki/Bodyweight_exercise'
html = requests.get(url).text
soup = BeautifulSoup(html, 'lxml')
replacements = {
'bams': 'bam',
'bodybuilders': 'bodybuilder',
'boots': 'boot',
'chairs': 'chair',
'climbers': 'climber',
'crosses': 'cross',
'curls': 'curl',
'darlings': 'darling',
'dips': 'dip',
'dogs': 'dog',
'extensions': 'extension',