df.to_excel('Lesson3.xlsx', index=False) # Location of file Location = r'C:\Users\hdrojas\.xy\startups\Lesson3.xlsx' # Create ExcelFile object xlsx = ExcelFile(Location) # Parse a specific sheet df = xlsx.parse('sheet1',index_col='StatusDate') df.dtypes #list index df.index #convert to upper df.Names = df.Names.apply(lambda x: x.upper()) # Only grab where Status == 1 df = df[df['Status'] == 1] #- For all records in the State column where they are equal to NJ, replace them with NY. df.Names[df.Names == 'BOB'] = 'Chet' df.Names[df.Names == 'Chet'] = 'John' df.Names[df.Names == 'MARY'] = 'John' #agg by Names to get Sum Daily = df.reset_index().groupby(['Names']).sum() Daily.head() data = [1000,2000,3000] idx = date_range(start='12/31/2011', end='12/31/2013', freq='A')