NLSA
4c62807fe9
build and deploy Speckle functions / publish-automate-function-version (push) Has been cancelled
87 lines
2.5 KiB
Python
87 lines
2.5 KiB
Python
def get_nested_attr(obj, attr_path, default=None):
|
|
"""
|
|
Safely get a nested attribute or dictionary key using a dot-separated path.
|
|
"""
|
|
try:
|
|
parts = attr_path.split('.')
|
|
for part in parts:
|
|
if isinstance(obj, dict):
|
|
obj = obj.get(part, default)
|
|
else:
|
|
obj = getattr(obj, part, default)
|
|
|
|
if obj is None:
|
|
return default
|
|
|
|
return obj
|
|
except AttributeError:
|
|
return default
|
|
|
|
|
|
def get_properties_for_object(obj, list_prop):
|
|
"""
|
|
Retrieve specified properties for a single object based on a list of property paths.
|
|
"""
|
|
result = {}
|
|
for prop in list_prop:
|
|
result[prop] = get_nested_attr(obj, prop)
|
|
|
|
return result
|
|
|
|
def get_properties_for_list(objects, list_prop):
|
|
"""
|
|
Retrieve specified properties for a list of objects.
|
|
"""
|
|
results = []
|
|
for obj in objects:
|
|
result = get_properties_for_object(obj, list_prop)
|
|
results.append(result)
|
|
|
|
return results
|
|
|
|
|
|
def create_pivot_with_total(df, category):
|
|
"""
|
|
Creates a pivot table for the given category, grouping by 'level' and summarizing 'area'.
|
|
Adds a total row at the bottom.
|
|
|
|
Parameters:
|
|
df (pd.DataFrame): The original DataFrame.
|
|
category (str): The category to filter ("Rooms" or "Areas").
|
|
|
|
Returns:
|
|
pd.DataFrame: The pivoted DataFrame with totals.
|
|
"""
|
|
# Filter based on category
|
|
df_filtered = df[df["category"] == category].reset_index(drop=True)
|
|
|
|
# Create the pivot table
|
|
df_pivot = df_filtered.pivot_table(index="level", columns="name", values="area", aggfunc="sum").reset_index()
|
|
|
|
# Fill NaN values with 0
|
|
df_pivot = df_pivot.fillna(0)
|
|
|
|
# Add a new row with the sum of all numeric columns
|
|
df_pivot.loc["Total"] = df_pivot.select_dtypes(include="number").sum()
|
|
df_pivot.loc["Total", "level"] = "Total" # Set label for the sum row
|
|
|
|
return df_pivot
|
|
|
|
def create_pivot_tables(filter_categories, df):
|
|
table_list = []
|
|
if len(filter_categories) == 2:
|
|
|
|
# Explicitly filter based on "Areas" and "Rooms"
|
|
df_rooms = create_pivot_with_total(df, "Rooms")
|
|
table_list.append(df_rooms)
|
|
|
|
df_areas = create_pivot_with_total(df, "Areas")
|
|
table_list.append(df_areas)
|
|
|
|
return table_list
|
|
else:
|
|
|
|
df_pivot_table = create_pivot_with_total(df, filter_categories[0])
|
|
table_list.append(df_pivot_table)
|
|
|
|
return table_list |