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

hi
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.

:slight_smile:

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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Hi,
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

https://github.com/SGB996/CodeCademy-Portfolio

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

Hello,
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