def opportunity_id(counter):
original = pd.read_csv("file.csv")
filter.full_correction(original)
set_output("opportunity_id.txt")
opportunity_id_stats(original)
reset_output()
def basic_analysis(df):
original = pd.read_csv("file.csv")
filter.full_correction(original)
basic_stats(df)
null_stats(df)
var_stats(df)
value_counts_stats(df)
return
def product_name(counter):
original = pd.read_csv("file.csv")
filter.full_correction(original)
set_up_stats(original)
set_output("product_name_stats.txt")
product_name_stats(original)
product_name_won(original, counter)
reset_output()
return
def trf(counter):
original = pd.read_csv("file.csv")
filter.full_correction(original)
set_up_stats(original)
set_output("trf_stats.txt")
trf_stats(original)
trf_won(original, counter)
trf_cut_won(original, counter)
reset_output()
def stage(counter):
original = pd.read_csv("file.csv")
filter.full_correction(original)
set_output("stage_stats.txt")
stage_stats(original)
stage_graph(original, counter)
original = original.loc[original["Stage"] == "Closed Won", :]
reset_output()
def burocratic_code(counter):
original = pd.read_csv("file.csv")
filter.full_correction(original)
original = original.drop_duplicates(subset="Opportunity_Name")
set_up_stats(original)
set_output("burocratic_code_stats.txt")
burocratic_code_stats(original)
burocratic_code_won(original, counter)
reset_output()
def opportunity_owner(counter):
original = pd.read_csv("file.csv")
filter.full_correction(original)
original = original.drop_duplicates(subset="Opportunity_Name")
set_up_stats(original)
set_output("opportunity_owner_stats.txt")
opportunity_owner_stats(original)
opportunity_owner_won(original, counter)
reset_output()
return
def product_type(counter):
original = pd.read_csv("file.csv")
filter.full_correction(original)
set_output("product_type_stats.txt")
product_type_basic_registers(original)
original = original.drop_duplicates(subset="Opportunity_Name")
product_type_basic_opportunities(original)
product_type_stats(original)
reset_output()
return
def billing_country(counter):
original = pd.read_csv("file.csv")
filter.full_correction(original)
original = original.drop_duplicates(subset="Opportunity_Name")
# Codigo extraído de Lean. Regenerado con unas modificaciones
facturacion_por_pais = original[['Billing_Country', 'ID']].groupby('Billing_Country').count().rename(columns={'ID': 'Total_Facturas'})\
.sort_values(by=['Total_Facturas'], ascending=False)
facturacion_por_pais = facturacion_por_pais.reset_index()
opportunity_owner_top5(facturacion_por_pais, counter)
return
def product_family(counter):
original = pd.read_csv("file.csv")
filter.full_correction(original)
#original = original.drop_duplicates(subset="Opportunity_Name")
set_up_stats(original)
set_output("product_family_stats.txt")
product_family_stats(original)
product_family_won(original, counter)
reset_output()
return
def negotiation_length(counter):
original = pd.read_csv("file.csv")
filter.full_correction(original)
original = original.loc[(original["Stage"] == "Closed Won") |
(original["Stage"] == "Closed Lost"), :]
original = original.drop_duplicates(subset="Opportunity_Name")
set_up_stats(original)
set_output("negotiation_length_stats.txt")
negotiation_length_stats(original)
negotiation_length_won(original, counter)
reset_output()
def brand():
original = pd.read_csv("file.csv")
filter.full_correction(original)
set_output("brand_stats.txt")
print_title("Estadísticas de la Marca")
brand_basic_prestats(original)
original = original.drop_duplicates(subset="Opportunity_Name")
brand_basic_stats(original)
brand_success(original)
brand_to_product_type_correlation(original)
product_type_to_brand_correlation(original)
reset_output()
return
def opportunity_created(counter):
original = pd.read_csv("file.csv")
filter.full_correction(original)
original = original.drop_duplicates(subset="Opportunity_Name")
set_up_stats(original)
set_output("opportunity_created_stats.txt")
opportunity_stats(original)
opportunity_year(original, counter)
opportunity_month(original, counter)
opportunity_day(original, counter)
opportunity_year_won(original, counter)
opportunity_month_won(original, counter)
opportunity_day_won(original, counter)
reset_output()
def total_taxable_amount(counter):
original = pd.read_csv("file.csv")
original = original[original["Total_Amount"].notna()]
filter.full_correction(original)
original = original.loc[(original["Stage"] == "Closed Won")
| (original["Stage"] == "Closed Lost")]
set_up_stats(original)
set_output("total_taxable_amount_stats.txt")
original = original.drop_duplicates(subset="Opportunity_Name")
tot_sum_compare(original)
tot_tax_basic_stats(original)
tot_tax_success(original, counter)
tot_cur_success(original, counter)
benford(original, counter)
reset_output()
return