extract (leave only) all rows between two specific strings in a dataframe

[Digger]

I have table

How extract (leave only) all rows between two specific strings in a dataframe
total_sale_amount  and type

expected result

0.00

7037.65

Maybe using python?

Tryed this

import numpy as np

idx_start = dataset.index[dataset.Column1 == "total_sale_amount"]
idx_end = dataset.index[dataset.Column1 == "type"]
print(idx_start)

good = list(zip(list(idx_start), list(idx_end)))#required sequences

#unpack list of list
g2 = [list(range(x[0],x[1]+1)) for x in good]

#data.iloc[np.r_[[y for x in g2 for y in x]]]#If you want to return just the valid dataset

l =[y for x in g2 for y in x]

#'dataset'['mark'] = np.where((dataset.index.isin(l)),1,None)

But it return same result as dataset

[v-yangliu-msft · Accepted solution]

Hi  @Digger ,

Here are the steps you can follow：

1. Enter Power Query through Transform data, select Table-right click-Duplicate to form a new table Table_duplicate.

2. Select Table, Add Column – Index Column – From 1.

3. Select the new table Table_duplicate, Add Column – Index Column – From 0.

4. Select Home – Merge Queries - Merge Queries as New

5. Enter the Merge interface, select the same [Index], Join kind = Left Outer

Result：

6. Create calculated table.

final_table =
var _1=FILTER('Merge1','Merge1'[Column1]="total_sale_amount")
return
SELECTCOLUMNS(_1,"Column1",[Column_merge])

7. Result：

Best Regards,

Liu Yang

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly

[lbendlin]

this is easy to do via an index column. Please provide sample data in usable format (not as a picture).