About the Portfolio Project: U.S. Medical Insurance Costs category

I started this yesterday and had a tough time getting going not working on the Codecademy website, I ended up using Jupyter notebook, please any feedback as to where I can work, I do have visual code installed but I have a hard time operating it.

GitHub ill also have to put more hours into…

Nevertheless I got it done I ended up using pandas to import the data, I also included the “import csv” function at the bottom: GitHub - dredomecode/medical_insurance_final_ish

Any feedback on the code is appreciated; I am severely new at coding and could use any inputs.
I am 58% through the data science foundation path.


This was my first project that I’ve done so far without having to look at any solutions. I am pretty proud of this milestone. Would appreciate any feedback.

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my code is here: GitHub - coachhuma/huma
please review if you would like.
Thank you :grinning:smiley:

Hi all,

I wonder what should I do to let the website know I’ve finished the project so that I can continue?

Thanks a lot!

Hello everyone,
the experience was fun, although was kind of tiring as I started working things on my own without any guidance and to check what I want to find and how is it going to be beneficial and what should I do
it took several hours at least and I wanted to make it as neat as possible but it is kind of messy. But for a first portfolio. It was a nice experience overall
This is the link to the code in my repository

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Hello there,

this exercise was challenging but also quite rewarding. Realised how much easier analysis during uni years could have been. The project had a span over couple of days and also included some significant trial and error. One challenge I encountered was trying to create a regional map of the US where the regions are heat mapped according to their average medical costs. I experimented with shp files. But did not manage to implement it, therefore I did not include it in my code example.
Feel free to have a look at my GitHub repository. , where I collect all my Codecademy Portfolio Projects.

Feedback is always welcome!

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Hi, I want your Feedback. Am I missing something? What needs improvement?

U.S. Medical Insurance GitHub Repository:

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I have uploaded my code using the link below.
Your feedback will be highly appreciated.
Thank you.

Above is the link to my notebook.
I enjoyed the exercise, I applied a linear regression, although I hope I did it the correct way.
This is a very clean dataset, many groups are evenly distributed.

I tried to write a brief summary for every result.
Please feel free to give feedback. :sunglasses:

I like how you annotated your results, you were very thorough.
I used the statistics package in python.
Feel free to look through my notebook.
Great job :grinning:

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I like your code, I would try and use a Jupyer notebook or you can use Jupyter lite.

It’s a much better environment for development.

I had trouble downloading jupyter on my work station.

I need more work. I am working with a person who have way more advanced knowledge than me. I’m just about to start Pandas to catch up. Maybe, redo all projects once I know more libraries.

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Hi, I created a dictionary and then appended it to a list. Hope this helps.
See here.

age_list = [] insurance_dict = {} numerical_id_list = [] insurance_list = [] with open("insurance.csv",newline = "") as insurance_data: reader = csv.DictReader(insurance_data) for row in reader: #print(row['age']) #numerical_ID = range(len( age = row['age'] # numerical_ID = len(row["age"]) sex = row['sex'] children = row['children'] BMI = row["bmi"] smoker = row["smoker"] region = row["region"] charges = row["charges"] #print(numerical_ID) #print(sex) #print(children) age_list.append(int(age)) numerical_ID_len = len(age_list) insurance_dict = {"age":int(age),"sex":sex, "children":int(children),"BMI": float(BMI),"smoker": smoker,"region": region,"charges": float(charges)} #insurance_dict[age] = {"age":int(age),"sex":sex, "children":int(children),"BMI": float(BMI),"smoker": smoker,"region": region,"charges": float(charges)} insurance_list.append(insurance_dict)

Hello World

Here is my solution to the US Medical Insurance Cost

Appreciate any feedback!

Hi all!

This is my solution. This took me a day, good recap exercise all everything we’ve learned on dictionary.
Please let me know if anybody have trouble seeing my file.

Hi @linhcly
I’ve checked the code and, despite being a beginner coder, it all looks correct.
It seems you solved the whole analysis with lists and haven’t used any dictionary, maybe you can add (just for a matter of practice) some further using them.

If possible have a look at my solution and tell me what you think.

Thanks in advance!

Hello there, this is my solution


Nice solution. Aftewards using pandas python will be much easy to analyse the data

I have completed my Portfolio Project: U.S. Medical Insurance Cost anybody would like to review and give feedback it would be highly appreciated.project link
Thank you

Hi everyone,

is there any kind of a real project ? I can only see the csv data set in the zip download. The other files are all empty…

Thank you