def tableau_data():
Workbook.caller()
save_path = str(dr_pivot_path())
save_path = save_path[:save_path.rindex('\\')]
ddr_data = dr.raw_pivot()
d = dr.tableau_campaign_data(ddr_data)
s = search.merge_data()
tableau = d.append(s)
tableau['Quarter'] = qquarter()
if Range('merged', 'A1').value is None:
chunk_df(tableau, 'merged', 'A1')
# If data is already present in the tab, the two data sets are merged together and then copied into the data tab.
else:
past_data = pd.read_excel(dr_pacing_path(), 'merged', index_col=None)
past_data = past_data[past_data['Campaign'] != 'Search']
appended_data = past_data.append(tableau)
Sheet('merged').clear()
chunk_df(appended_data, 'merged', 'A1')
#Range('Sheet3', 'AT1').value = pd.to_datetime(ddr_data['Date'].max()) + datetime.timedelta(days= 1)
wb = Workbook()
Sheet('Sheet1').name = 'DDR Data'
chunk_df(ddr_data, 'DDR Data', 'A1')
wb.save(save_path + '\\' + 'DR_Raw_Data.xlsx')
wb.close()
def output_pacing_data_for_forecasts():
wb = Workbook.caller()
dr_data = dr.raw_pivot()
#pace = dr.pacing()
#data_merged = data_transform.raw_pacing_and_dr(dr_data, pace)
dr_forecasting = data_transform.transform_dr(dr_data)
wb.set_current()
Sheet('raw_pacing_data').clear_contents()
Range('raw_pacing_data', 'A1', index=False).value = dr_forecasting
performance.publishers(dr_data)