Develop Reference

Why "NameError: name 'product_id_list' is not defined"=

I write this and i don't know why product_id_list is not defined if i have defined it like 4 lines before.
Any suggestions? I thin identation is alright so I don't have any more ideas and I also searched around without luck.
Thank you!!
def make_dataSet_rowWise(reorder_product):
print('unique Product in dataset = ', len(reorder_product.product_id.unique()))
print('unique order_id in dataset = ', len(reorder_product.order_id.unique()))
product_id_list = reorder_product.product_id.unique().tolist()
product_id_list.append("order_id")
product_id_dict = {}
i = 0
for prod_id in product_id_list:
product_id_dict[prod_id] = i
i = i+1
product_id_df = pd.Dataframe(columns = product_id_list)
row_list_all = []
order_id_list = reorder_product.order_id.unique()
i = 1
for id in order_id_list:
#print(i)
i = i+1
np_zeros = np.zeros(shape = [len(product_id_list)-1])
ordered_product_list = reorder_product.loc[reorder_product.order_id == id]["product_id"].tolist()
for order_prod in ordered_product_list:
np_zeros[product_id_dict.get(order_prod)] = 1
row_list = np_zeros.tolist()
row_list.append(id)
row_list_all.append(row_list)
return (row_list_all, product_id_list)
df_row_wise = make_dataSet_rowWise(reorder_product_99Pct)
product_id_df = pd.DataFrame(df_row_wise[0], columns = df_row_wise[1])
product_id_df.head()
The error I have is this one:
NameError Traceback (most recent call last)
<ipython-input-343-07bcac1b3b48> in <module>
7 i = 0
8
----> 9 for prod_id in product_id_list:
10 product_id_dict[prod_id] = i
11 i = i+1
NameError: name 'product_id_list' is not defined

As already mentioned by the other answers, your indentation is wrong.
My recommendation is that you use a IDE like VSCode, there is also a free web version https://vscode.dev/
With such kind of IDE you can see that your indentation is wrong, check screenshot and line 27
There are also wrong indentations with the 3 for loops. The correct indentation should be as the following

I think your indentation may be wrong, the for-loops and return statement is out of the function (with your indentation) so I indented it so that it would still be part of the function...
def make_dataSet_rowWise(reorder_product):
print('unique Product in dataset = ', len(reorder_product.product_id.unique()))
print('unique order_id in dataset = ', len(reorder_product.order_id.unique()))
product_id_list = reorder_product.product_id.unique().tolist()
product_id_list.append("order_id")
product_id_dict = {}
i = 0
for prod_id in product_id_list:
product_id_dict[prod_id] = i
i = i+1
product_id_df = pd.Dataframe(columns = product_id_list)
row_list_all = []
order_id_list = reorder_product.order_id.unique()
i = 1
for id in order_id_list:
#print(i)
i = i+1
np_zeros = id.zeros(shape = [len(product_id_list)-1])
ordered_product_list = reorder_product.loc[reorder_product.order_id == id]["product_id"].tolist()
for order_prod in ordered_product_list:
np_zeros[product_id_dict.get(order_prod)] = 1
row_list = np_zeros.tolist()
row_list.append(id)
row_list_all.append(row_list)
return (row_list_all, product_id_list)

I'm new here, but i think you either need to define the variable out of the scope of
def make_dataSet_rowWise(reorder_product):
OR indent the for loops to be inside
make_dataSet_rowWise

How to create a function to tell whether a value is increasing or decreasing?

I want to create comments from a dataset that details the growth rate, market share, etc for various markets and products. The dataset is in the form of a pd.DataFrame(). I would like the comment to include keywords like increase/decrease based on the calculations, for example, if 2020 Jan has sale of 1000, and 2021 Jan has a sale of 1600, then it will necessary mean an increase of 60%.
I defined a function outside as such and I would like to seek if this method is too clumsy, if so, how should I improve on it.
GrowthIncDec = namedtuple('gr_tuple', ['annual_growth_rate', 'quarterly_growth_rate'])
def increase_decrease(annual_gr, quarter_gr):
if annual_gr > 0:
annual_growth_rate = 'increased'
elif annual_gr < 0:
annual_growth_rate = 'decreased'
else:
annual_growth_rate = 'stayed the same'
if quarter_gr > 0:
quarterly_growth_rate = 'increased'
elif quarter_gr < 0:
quarterly_growth_rate = 'decreased'
else:
quarterly_growth_rate = 'stayed the same'
gr_named_tuple = GrowthIncDec(annual_growth_rate=annual_growth_rate, quarterly_growth_rate=quarterly_growth_rate)
return gr_named_tuple
myfunc = increase_decrease(5, -1)
myfunc.annual_growth_rate
output: 'increased'
A snippet of my main code is as follows to illustrate the use of the above function:
def get_comments(grp, some_dict: Dict[str, List[str]]):
.......
try:
subdf = the dataframe
annual_gr = subdf['Annual_Growth'].values[0]
quarter_gr = subdf['Quarterly_Growth'].values[0]
inc_dec_named_tup = increase_decrease(annual_gr, quarter_gr)
inc_dec_annual_gr = inc_dec_named_tup.annual_growth_rate
inc_dec_quarterly_gr = inc_dec_named_tup.quarterly_growth_rate
comment = "The {} has {} by {:.1%} in {} {} compared to {} {}"\
.format(market, inc_dec_annual_gr, annual_gr, timeperiod, curr_date, timeperiod, prev_year)
comments_df = pd.DataFrame(columns=['Date','Comments'])
# comments_df['Date'] = [curr_date]
comments_df['Comments'] = [comment]
return comments_df
except (IndexError, KeyError) as e:
# this is for all those nan values which is empty
annual_gr = 0
quarter_gr = 0

Parsing Security Matrix Spreadsheet - NoneType is not Iterable

Trying to Nest no's and yes's with their respective applications and services.
That way when a request comes in for a specific zone to zone sequence, a check can be run against this logic to verify accepted requests.
I have tried calling Decision_List[Zone_Name][yes_no].update and i tried ,append when it was a list type and not a dict but there is no update method ?
Base_Sheet = range(5, sh.ncols)
Column_Rows = range(1, sh.nrows)
for colnum in Base_Sheet:
Zone_Name = sh.col_values(colnum)[0]
Zone_App_Header = {sh.col_values(4)[0]:{}}
Zone_Svc_Header = {sh.col_values(3)[0]:{}}
Zone_Proto_Header = {sh.col_values(2)[0]:{}}
Zone_DestPort_Header = {sh.col_values(1)[0]: {}}
Zone_SrcPort_Header = {sh.col_values(0)[0]: {}}
Decision_List = {Zone_Name:{}}
for rows in Column_Rows:
app_object = sh.col_values(4)[rows]
svc_object = sh.col_values(3)[rows]
proto_object = sh.col_values(3)[rows]
dst_object = sh.col_values(2)[rows]
src_object = sh.col_values(1)[rows]
yes_no = sh.col_values(colnum)[rows]
if yes_no not in Decision_List[Zone_Name]:
Decision_List[Zone_Name][yes_no] = [app_object]
else:
Decision_List[Zone_Name]=[yes_no].append(app_object)
I would like it present info as follows
Decision_List{Zone_Name:{yes:[ssh, ssl, soap], no:
[web-browsing,facebook]}}

I would still like to know why i couldnt call the append method on that specific yes_no key whos value was a list.
But in the mean time, i made a work around of sorts. I created a set as the key and gave the yes_no as the value. this will allow me to pair many no type values with the keys being a set of the application, port, service, etc.. and then i can search for yes values and create additional dicts out of them for logic.
Any better ideas out there i am all ears.
for rownum in range(0, sh.nrows):
#row_val is all the values in the row of cell.index[rownum] as determined by rownum
row_val = sh.row_values(rownum)
col_val = sh.col_values(rownum)
print rownum, col_val[0], col_val[1: CoR]
header.append({col_val[0]: col_val[1: CoR]})
print header[0]['Start Port']
dec_tree = {}
count = 1
Base_Sheet = range(5, sh.ncols)
Column_Rows = range(1, sh.nrows)
for colnum in Base_Sheet:
Zone_Name = sh.col_values(colnum)[0]
Zone_App_Header = {sh.col_values(4)[0]:{}}
Zone_Svc_Header = {sh.col_values(3)[0]:{}}
Zone_Proto_Header = {sh.col_values(2)[0]:{}}
Zone_DestPort_Header = {sh.col_values(1)[0]: {}}
Zone_SrcPort_Header = {sh.col_values(0)[0]: {}}
Decision_List = {Zone_Name:{}}
for rows in Column_Rows:
app_object = sh.col_values(4)[rows]
svc_object = sh.col_values(3)[rows]
proto_object = sh.col_values(3)[rows]
dst_object = sh.col_values(2)[rows]
src_object = sh.col_values(1)[rows]
yes_no = sh.col_values(colnum)[rows]
for rule_name in Decision_List.iterkeys():
Decision_List[Zone_Name][(app_object, svc_object, proto_object)]= yes_no
Thanks again.

I think still a better way is to use collections.defaultdict
In this manner it will ensure that i am able to append to the specific yes_no as i had originally intended.
for colnum in Base_Sheet:
Zone_Name = sh.col_values(colnum)[0]
Zone_App_Header = {sh.col_values(4)[0]:{}}
Zone_Svc_Header = {sh.col_values(3)[0]:{}}
Zone_Proto_Header = {sh.col_values(2)[0]:{}}
Zone_DestPort_Header = {sh.col_values(1)[0]: {}}
Zone_SrcPort_Header = {sh.col_values(0)[0]: {}}
Decision_List = {Zone_Name:defaultdict(list)}
for rows in Column_Rows:
app_object = sh.col_values(4)[rows]
svc_object = sh.col_values(3)[rows]
proto_object = sh.col_values(2)[rows]
dst_object = sh.col_values(1)[rows]
src_object = sh.col_values(0)[rows]
yes_no = sh.col_values(colnum)[rows]
if yes_no not in Decision_List[Zone_Name]:
Decision_List[Zone_Name][yes_no]= [app_object, svc_object, proto_object, dst_object, src_object]
else:
Decision_List[Zone_Name][yes_no].append([(app_object, svc_object, proto_object,dst_object, src_object)])
This allows me to then set the values as a set and append them as needed

Python , how to get value from a loop and assign to another loop?

I have two loops below the first one is the timand and the second one is shared. What i want to know how can i assign each result to shared["score"] ? cause what i had try below i assign shared["score"] = timang["score"] just return 1 1 1 .... And also how can we return multiple response in python for example
return Response(shared_data, tomon_dat, status=status.HTTP_200_OK) is this possible?
#result of timang
Result: 0
Result: 1
Result: 0
Result: 0
Result: 1
Result: 1
for timang in tomon_dat:
tm_ins = QuestionaireAnswerModel.objects.get(id=timang["id"])
timang["score"] = tm_ins.score
timang["id"] = tm_ins.id
datatest = timang["score"]
for shared in shared_data:
questionaire_ins = QuestionaireModel.objects.get(random_code=shared["random_code"])
shared["title"] = questionaire_ins.title
shared["sub_title"] = questionaire_ins.sub_title
shared["idddd"] = questionaire_ins.id
answer_ins = SharedQuestionaire.objects.get(id=shared["id"])
shared["is_answered"] = (QuestionaireAnswerModel.objects.filter(shared_questionaire=answer_ins).count()) > 0
shared["score"] = timang["score"]

python list of dictionaries only updating 1 attribute and skipping others

I have a list of lists containing company objects:
companies_list = [companies1, companies2]
I have the following function:
def get_fund_amount_by_year(companies_list):
companies_length = len(companies_list)
for idx, companies in enumerate(companies_list):
companies1 = companies.values_list('id', flat=True)
funding_rounds = FundingRound.objects.filter(company_id__in=companies1).order_by('announced_on')
amount_per_year_list = []
for fr in funding_rounds:
fr_year = fr.announced_on.year
fr_amount = fr.raised_amount_usd
if not any(d['year'] == fr_year for d in amount_per_year_list):
year_amount = {}
year_amount['year'] = fr_year
for companies_idx in range(companies_length):
year_amount['amount'+str(companies_idx)] = 0
if companies_idx == idx:
year_amount['amount'+str(companies_idx)] = fr_amount
amount_per_year_list.append(year_amount)
else:
for year_amount in amount_per_year_list:
if year_amount['year'] == fr_year:
year_amount['amount'+str(idx)] += fr_amount
return amount_per_year_list
The problem is the resulting list of dictionaries has only one amount attribute updated.
As you can see "amount0" contains all "0" amounts:
[{'amount1': 12100000L, 'amount0': 0, 'year': 1999}, {'amount1':
8900000L, 'amount0': 0, 'year': 2000}]
What am I doing wrong?

I put list of dictionaries being built in the loop and so when it iterated it overwrote the last input. I changed it to look like:
def get_fund_amount_by_year(companies_list):
companies_length = len(companies_list)
**amount_per_year_list = []**
for idx, companies in enumerate(companies_list):
companies1 = companies.values_list('id', flat=True)
funding_rounds = FundingRound.objects.filter(company_id__in=companies1).order_by('announced_on')