Forum Discussion
Python script changes data in date column.
The column is not even part of the python scriptThen how else does it participate in the output? Your python script is supposed to create a dataframe that is handed back to Power Query as a table.
Hey,
I have 17 columns. The script that I run only adds a new column at the end. The results in this column are based on the values in 3 of columns.
When I run the script, I get all the original dataframe back, with all 17 columns + 1 (the 1 computed by python). In these original 17 columns, only 1 of them (presented above) gets its values changed. The other 16 columns maintain their values.
Perhaps I did not do a good job clarifying in the first place.
Maybe you can show a sanitized version of the Power Query script.
Sure!
# 'dataset' holds the input data for this script
import pandas as pd
def calculate_Ordering(row):
curr_row = row['Chapter']
row_grp = row['Name']
row_main = row['Main']
prj = row['Project']
main_groups = dataset[(dataset['Main'] == True) &
(dataset['Name'] != row_grp) &
(dataset['Project'] == prj)]
rel_chpt = main_groups[main_groups['Chapter'] < curr_row]['Chapter'].max()
if row_main:
return curr_row
else:
if str(curr_row).startswith(str(rel_chpt)):
return rel_chpt
else:
return curr_row
dataset['Order'] = dataset.apply(calculate_Ordering, axis=1)
print(dataset)
The column affected is "Deadline", which only has date type data. It is not included in the script and is the only one affected. A possible work around would be to have it as text before running the Python script and then convert it back to date type, but this still does not explain why the data gets lost / modified in the first place.There is no point in the last print(dataset) command.
your dataset will completely replace any prior output, including that date column.
I'd need to see more of the Power Query script before and after the Python part to be able to assist more.