def main(path, country, unknown):
print('Starting Pipeline...')
df_with_dates_raw = mac.acquire(path)
df_with_dates_clean = mwr.wrangle(df_with_dates_raw, country, unknown)
df_analyze = man.analyze(df_with_dates_clean)
mre.save_df(df_analyze, country, unknown)
print(f'The results of the country -{country}- are: ')
print(df_analyze)
print('Finished Pipeline')
def main(country=None):
start = time.time()
print(f'Starting pipeline for {country}')
df = m_acquisition.acquire()
print('This may take around 80 seconds..')
wrangling_ = m_wrangling.wrangle(df)
print('Wrangling done, lets save the table')
analysis_ = m_analysis.analyse(wrangling_, country)
print(analysis_)
print(f'Task {country} done')
end = time.time()
print(end - start, str("seconds"))
def main(arguments):
data = mac.acquire(arguments.path)
filtered = mwr.wrangle(data, arguments.unemployed)
results = man.analyze(filtered)
reporting = mre.reporting(results, arguments.country)
reporting.to_csv('./data/results/Results.csv')
print(reporting)
print(
'\n\n======================| Pipeline is complete. You may find the results in the folder ./data/results |==============================\n\n'
)
def main(country, job):
data = mac.acquire()
relevant_data = mwr.transform_data(data)
clean_data, countries_codes = mwr.country_name_import(relevant_data)
select_job, key_uuid = mwr.job_data(clean_data, job)
filtered_data = mwr.job_filtering(clean_data, select_job, key_uuid)
filtered_data = man.country_filtering(filtered_data, country,
countries_codes)
result = man.analyze(filtered_data, job, clean_data)
mre.visualizing_histogram(result['Age'], country, job)
mre.reporting(result)
print(
'======= Pipeline is complete. You may find the results in the folder ./data/results ======='
)
def main(args):
print('Starting pipeline and retrieving information...')
print('Getting information from database analysed...')
df_m1 = mac.acquire(args.path)
df_m2 = mwr.wrangling(df_m1)
if args.country is None:
print('retrieving information for all countries...')
df_m3 = man.analysis(df_m2, 'all')
else:
df_m3 = man.analysis(df_m2, args.country)
print(
'********************* Pipeline is complete, you can find the results in the data results folder *********************'
)
def main(arguments):
print('starting pipeline...')
prices_dfs = mac.acquire(arguments.path, arguments.key)
stocks = mwr.build_data(prices_dfs)
returns = man.compute_returns(stocks)
risk_ratios = man.compute_risk_ratio(returns)
top_return_risk_companies = risk_ratios.nlargest(10, 'Ratio')
returns_corr = man.compute_corr(
returns[top_return_risk_companies['Company'].to_list()])
mre.report(top_return_risk_companies, returns_corr)
print(
'========================= Pipeline is complete. You may find the results in the folder '
'./data/results =========================')
def main(args):
print('starting pipeline...')
print('Getting the data from database...')
raw_data = mac.acquire(args.path)
print('Data from database is there!...')
print('Dealing with data...')
data = mwr.wrangling(raw_data)
print('Data dealt!')
print('analysing the data...')
molins = man.analysis(data, args.country)
print(molins)
print('Data analysed!...')
# Data reporting
print('Lets create the report...')
mre.graph_reporting(molins)
mre.pdf_reporting()
mre.email_reporting(arguments.email)
print('Report created!')
print(
'========================= Pipeline is complete. You may find the results in the folder '
'./data/results =========================')
def main(arguments):
print('Starting pipeline...', end='')
time.sleep(1)
print('....', end='')
time.sleep(1)
print('....')
df_project = mac.acquire(arguments.path)
data_merged = mwr.wrangling(df_project)
data_merged.to_csv('./data/processed/data_merged_info.csv')
data_project_analysed = man.analyce_data(data_merged, arguments.country)
data_project_analysed.to_csv('./data/results/country_gender_analysed.csv')
print(data_project_analysed)
# Bonus 1:
print('Getting Opinions...')
data_opinions = man.judgement(df_project)
data_opinions.to_csv('./data/results/Bonus1-Data_Opinions.csv')
print(data_opinions)
print(
'========================= Pipeline is complete. You may find the results in the folder '
'./data/results =========================')
def main(scrape):
print('Starting Pipeline...')
mac.acquire(scrape)
mwr.wrangle(scrape)
print('Finished Pipeline')
def main(df_coste, df_indicadores):
# mra.raw_cesel()
mac.acquire(df_coste, df_indicadores)
# mphl.pivot()
mg.graphic()
def main(arguments):
rural = mac.acquire()
rural_processed = mwr.wrangling(rural)
rural_analysed = man.analyze(rural_processed, arguments.country)
return rural_analysed
def main(scrape, download, model):
print('Starting Pipeline...')
mac.acquire(scrape)
mwr.wrangle(scrape, download)
man.analyze(model)
print('Finished Pipeline')