pivot-table

问题 I am new to VBA and I am having some trouble with some code on how to uncheck or deselect all items in a pivot table except a specific one. I am creating a button to automatically filter data that will only reveal data in January ("20190131") or in February ("20190228") and so on etc. I still dont have data for October ("20191031"), November and December, which causes error "Unable to set the Visible property of the PivotItem" because there is still no existing data of those dates. I just

问题 I have a dataframe that looks like this: df = pd.DataFrame({'publisher': ['facebook', 'facebook', 'facebook', 'google', 'google', 'google'], 'month_leadgen': ['2019-01', '2019-02', '2019-03', '2019-01', '2019-02', '2019-03'], 'month_payment': ['2019-01', '2019-02', '2019-03', '2019-01', '2019-02', '2019-03'], 'revenue': [60, 150, 450, 85, 250, 150]}) I then created a pivot table: df = df.pivot_table(index=['publisher', 'month_leadgen'], columns='month_payment', values='revenue').reset_index()

问题 I have a dataframe that looks like this: df = pd.DataFrame({'publisher': ['facebook', 'facebook', 'facebook', 'google', 'google', 'google'], 'month_leadgen': ['2019-01', '2019-02', '2019-03', '2019-01', '2019-02', '2019-03'], 'month_payment': ['2019-01', '2019-02', '2019-03', '2019-01', '2019-02', '2019-03'], 'revenue': [60, 150, 450, 85, 250, 150]}) I then created a pivot table: df = df.pivot_table(index=['publisher', 'month_leadgen'], columns='month_payment', values='revenue').reset_index()

问题 I have pCach as PivotCache when I just do ThisWorkbook.PivotCaches.Create(SourceType:=xlDatabase, SourceData:=pTRng).CreatePivotTable(TableDestination:= _ wOPT.Cells(3, 1), TableName:="PivotTable2") It works as expected and inserts pivotcache on the destination cell But when I try this it gives me type mismatch error? Set pCach = ThisWorkbook.PivotCaches.Create(SourceType:=xlDatabase, SourceData:=pTRng).CreatePivotTable(TableDestination:= _ wOPT.Cells(3, 1), TableName:="PivotTable2") 回答1: Try

问题 I have a dataframe that looks like this: data.head() Out[2]: Area Area Id Variable Name Variable Id Year \ 0 Argentina 9 Conservation agriculture area 4454 1982 1 Argentina 9 Conservation agriculture area 4454 1987 2 Argentina 9 Conservation agriculture area 4454 1992 3 Argentina 9 Conservation agriculture area 4454 1997 4 Argentina 9 Conservation agriculture area 4454 2002 Value Symbol Md 0 2.0 1 6.0 2 500.0 That I would like to pivot so that Variable Name is the columns, Area and Year are

问题 I have written some code to compute a weighted average using pivot tables in pandas. However, I am not sure how to add the actual column which performs the weighted averaging (Add a new column where each row contains value of 'cumulative'/'COUNT'). The data looks like so: VALUE COUNT GRID agb 1 43 1476 1051 2 212 1476 2983 5 7 1477 890 4 1361 1477 2310 Here is my code: # Read input data lup_df = pandas.DataFrame.from_csv(o_dir+LUP+'.csv',index_col=False) # Insert a new column with area *

问题 Closed . This question needs details or clarity. It is not currently accepting answers. Want to improve this question? Add details and clarify the problem by editing this post. Closed 3 months ago . Improve this question I have a table where if a row is missing it means the value for that row is zero. so for 2020-10-12 label L2 has all 0 values for all display url. 2020-10-12 label L3 has all 0 values for all display url except d2. How can I fill this missing data in the pivot table? I want

问题 Closed . This question needs details or clarity. It is not currently accepting answers. Want to improve this question? Add details and clarify the problem by editing this post. Closed 3 months ago . Improve this question I have a table where if a row is missing it means the value for that row is zero. so for 2020-10-12 label L2 has all 0 values for all display url. 2020-10-12 label L3 has all 0 values for all display url except d2. How can I fill this missing data in the pivot table? I want

问题 I am trying to create a pivot table that joins multiple (more than 8) data frames into one. The tables have multiple columns, but I'll keep it simple here: Table1 week project 42 ABC 42 FGA 42 ZTR 44 HTZ 44 UZR 44 LOP 46 POL 46 ZTT 46 ART 46 ART ... In some weeks there may be not any occurrence of any project. Table 2, 3, 4 and so on will certainly have a different number of weekly occurrences. The only common column accross all tables it the week column. Some tables have more some less

问题 Hello Data Scientist and Pandas Experts, I need some help as I can’t get my data organized properly. Here is my data frame: df_dict = [ {'Date': Timestamp('2014-01-03 00:00:00'), 'Store': 'store1', 'employee': 'emp1', 'duties': 'opening'}, \ {'Date': Timestamp('2014-01-03 00:00:00'), 'Store': 'store1', 'employee': 'emp2', 'duties': 'deli'}, \ {'Date': Timestamp('2014-01-03 00:00:00'), 'Store': 'store1', 'employee': 'emp3', 'duties': 'cashier'},\ {'Date': Timestamp('2014-01-03 00:00:00'),