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r/learnpython on Reddit: Beginner Python data analysis project - critique greatly welcome!
May 12, 2020 -
Hi everyone,
I just finished my first Python data analysis project, and being a total beginner, I could really use some other perspectives as to the quality of my final product. I plan on building a portfolio of similar projects and using it for applying to social science research assistant jobs where some programming and analysis ability is highly preferred. Since I am entirely self-taught, I need some concrete examples of what I can do to share with potential employers.
With that said, while I'm sure there are areas that could be improved, would my project be worth sharing with some edits? Or is it actually just a total flaming trash heap that should be scrapped entirely? Positive critique and helpful suggestions appreciated!
Project
Edit: Wow, I did not expect to wake up to so many comments and upvotes! I really needed this boost, to be honest. I'm so grateful for everyone's kindness and suggestions, and I'm definitely going to go back and try and tweak some things! I hope I can pay it forward one day, but for now, to fellow noobs who are trying to set up their first project - just go do it! I basically just forced myself to create something after learning the basics, and it really helps the learning process to break things down and figure out how they work outside of a guided tutorial. Keep coding!
Edit 2: I've uploaded a new version of the project since this was posted, taking into account some of the suggestions everyone has made. It's still not perfect, but I think it's time to move onto learning with new projects.
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As someone who just started learning python to do similar type of projects, I just wanted to say thanks for posting and I enjoyed reading this! How long did it take you to get to this point?! Great work.
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This looks really good! A few thoughts: When reading in csvs to pandas I find it useful to specify the encoding and the type (usually auto set to UTF-8 and object personally). Particularly when you're working with data which contains some text and some numeric columns, it's helpful to be explicit to avoid any unexpected behaviour. When naming variables be explicit with regards to the data type, e.g. instead of 'clergydata' I would call this 'df_clergydata'. When you end up with multiple different lists, dicts and dfs in your code it's very helpful to have all of this explicitly named (particularly when you come back to your code a month later). When creating column names in your df you created several which contain capital letters and spaces (e.g. clergydata['Age range']). It's better and easier to only use lower case letters in variable names/column names where possible and to use underscores instead of spaces. This lets you access the column using clergydata.age_range instead of clergydata['Age range'] in lots of situations when manipulating your df, which is often much quicker and easier. In cell 12 you manually specify the archdiocese abbreviation and name (e.g. LA, and Archdiocese of Los Angeles) for many different locations. It would be better to automate this somehow, to both improve clarity and also reduce the risk of error/inconsistency. I saw someone above suggested using a group by, which would work, or you could use a for loop to directly create your top19_cathpops and top19_dionames lists. If you're not clear how to do this let me know and I would be happy to clarify. Most importantly your code works and answers some interesting questions, but the above points will make things more explicit (which is always better) and make your life easier.
GitHub
github.com › topics › data-analysis-python
Data Analysis Python Projects
data-science exploratory-data-analysis ... data-analysis-python kaggle-used-cars-dataset ... A collection of data analysis and visualization projects designed to uncover insights from diverse datasets....
Data Analysis with Python Projects, Medical-Data-Visualiser
Well i am over 10 hours on this project and today i had a massive outbreak for not being able to procceed. Is it only me feeling that this is quite advanced with what we have been taught? I have done Python for everybody, Data analysis with Python videos and the numpy videos but here we are ... More on forum.freecodecamp.org
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December 30, 2024python - Suggest some beginner projects related to data analytics - Stack Overflow
To get started with these projects, you'll need to choose a dataset that aligns with your interests and goals. You can find datasets on platforms like Kaggle, GitHub, or data.gov. Python is a popular choice for data analysis, and libraries like Pandas, Matplotlib, Seaborn, and scikit-learn ... More on stackoverflow.com
Beginner Data Analyst Projects for Building an Impressive Portfolio?
Here is a pretty good playlist of end-to-end projects that you can look through. it covers everything from sql, python, power, and data studio: https://youtube.com/playlist?list=PLi5spBcf0UMXfbMt1X2bHQkk7mHXkTUhs&si=dUmZaMDaSJHAQRYF More on reddit.com
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May 5, 2024Data analysis project (beginner)
I am currently learning Data science and data analysis myself right now and i am also currently working on a project myself but i do have some advices to share that i was given by someone i know. They advised me to start by focusing on smaller goals that are the part of data analysis project. For example, make a project about data cleaning first by cleaning raw data from any public datasets available online or do a project about exploratory data analysis to explore the data and and also explore what questions to ask or maybe do a project about data visualization by visualizing already cleaned data from your own "data cleaning" project or by using already cleaned data from websites like Kaggle or UCI machine learning repository. The main idea is to get used to the tools and work environment before you jump into actual data analysis. These smaller projects will gain you experience and help you develop an understanding of how to work with data using your preferred tools and work environments. If you are confused about what project you should do then you can look for beginner friendly data analysis projects or you can find them here(Coursera link) I hope this helps More on reddit.com
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July 22, 2023What is data visualization?
Data visualization is the process of graphically representing data through visual means. Common forms of data visualization include the use of graphs, charts, and diagrams to visually represent otherwise abstract data sets. Today, data visualization is considered a key skill in the world of data analytics.
coursera.org
coursera.org › coursera articles › data › data analytics › 5 data analytics projects for beginners
5 Data Analytics Projects for Beginners | Coursera
What are some books on data analytics for beginners?
There are many great books for those just starting out in data analytics. The following three books, in particular, offer accessible introductions to key aspects of the field: Data Analytics Made Accessible by Dr. Anil Maheshwari, Numsense! Data Science for the Layman: No Math Added by Annalyn Ng and Kenneth Soo, and Python for Everybody: Exploring Data in Python 3 by Dr. Charles Russell Severance.
To supplement their reading, beginners may also consider taking the online Python for Everybody Specialization offered by the University of Michigan and taught by Dr. Severance himself.
coursera.org
coursera.org › coursera articles › data › data analytics › 5 data analytics projects for beginners
5 Data Analytics Projects for Beginners | Coursera
What skills do data analysts need?
Beginning data analysts should make sure they have a solid technical understanding of structured query language (SQL), Microsoft Excel, and either R or Python. Additionally, they should be able to think critically, present confidently, and know how to tell their data’s story visually. Read more about these and other key data analyst skills.
coursera.org
coursera.org › coursera articles › data › data analytics › 5 data analytics projects for beginners
5 Data Analytics Projects for Beginners | Coursera
Videos
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GeeksforGeeks
geeksforgeeks.org › data analysis › data-analyst-projects
30+ Top Data Analytics Projects in 2025 [With Source Codes] - GeeksforGeeks
February 13, 2026 - Web scraping projects teach you how to collect raw data from websites and transform it into useful insights through analysis. ... Choosing the right tools is essential for building efficient and scalable data analytics projects. Below are some of the most commonly used platforms in the industry. Microsoft Excel: Suitable for beginners and quick data exploration · Python (Pandas and NumPy): Ideal for data manipulation, analysis and automation
Kaggle
kaggle.com › general › 433860
Python-Powered Data Analysis Projects: Unveiling Insights ...
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DataCamp
datacamp.com › blog › data-analytics-projects-all-levels
30 Data Analytics Projects for All Levels (2026) | DataCamp
February 27, 2026 - You will practice graph construction from follower data, data cleaning with Pandas, centrality and community detection, ranking influential accounts, ego-net exploration, and creating readable network visualizations with clear takeaways. The World Population Analysis project is the best example of performing deep exploratory analysis. You will be exploring various columns, visualizing the least and most populated countries, and exploring population density and growth rate. Furthermore, you will display the country rank distribution and correlation map. ... Learn easy ways to plot data visualization in Python by completing Intermediate Data Visualization with Seaborn course.
freeCodeCamp.org
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Data Analysis with Python
Learn to Code — For Free
ProjectPro
projectpro.io › blog › 50+ python projects for data science in 2025
50+ Python Projects for Data Science in 2025
May 13, 2025 - This project is ideal for practicing data cleaning, feature engineering, and geospatial analysis. ... Study the Gross Domestic Product (GDP) trends of various countries over the past decades. This project involves analyzing economic indicators, visualizing growth patterns, and understanding global economic shifts. ... I am the Director of Data Analytics with over 10+ years of IT experience. I have a background in SQL, Python, and Big Data working with Accenture, IBM, and Infosys.
Coursera
coursera.org › coursera articles › data › data analytics › 5 data analytics projects for beginners
5 Data Analytics Projects for Beginners | Coursera
November 2, 2025 - Example sentiment analysis project: ... used Python to perform a sentiment analysis of product reviews using NLP. ... Learn how to use Google Cloud for sentiment analysis from Google itself in their short, interactive project, Entity and Sentiment Analysis with the Natural Language API. Humans are visual creatures, which makes data visualization ...
Amanxai
amanxai.com › home › all articles › 50 data analysis projects with python
50 Data Analysis Projects with Python | Aman Kharwal
December 27, 2024 - In this article, I'll take you through a list of 50 Data Analysis projects with Python you should try to master Data Analysis.
freeCodeCamp
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Data Analysis with Python Projects, Medical-Data-Visualiser - Python - The freeCodeCamp Forum
December 30, 2024 - Well i am over 10 hours on this project and today i had a massive outbreak for not being able to procceed. Is it only me feeling that this is quite advanced with what we have been taught? I have done Python for everybody, Data analysis with Python videos and the numpy videos but here we are ...
LinkedIn
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Aman Kharwal - 70+ Data Analysis Projects with Python
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365 Data Science
365datascience.com › blog › tutorials › python tutorials › 4 essential python projects for beginners (with code)
4 Essential Python Beginner Projects (with Code) – 365 Data Science
June 11, 2024 - Music Genre Classification Project with PCA and Logistic Regression (Intermediate, 3 hours) Machine Learning for User Classification Project (Intermediate, 10 hours) Encryption and Decryption in Python Project (Intermediate, 8 hours) Real Estate ...
Quora
quora.com › What-are-some-projects-or-platforms-for-Python-and-data-analysis-to-help-build-my-proficiency
What are some projects or platforms for Python and data analysis to help build my proficiency? - Quora
Answer: I may be completely wrong in my interpretation of your question, but I believe the response you want is a description of a practice project that would help you develop proficiency in data analysis using python. If so, good on you for this question. I never considered quora as a source of...
Great Learning
mygreatlearning.com › great learning › data science › python projects for data analysis
Python Projects for Data Analysis Free Course with Certificate | Great Learning
Data Cleaning Project Data cleaning is the process of identifying and correcting errors, inconsistencies, and inaccuracies in the data. This Python project involves cleaning the data and preparing it for analysis. In this project, you will work with messy data sets, identify missing values, handle outliers, and remove duplicates.
Dataquest
dataquest.io › blog › python-projects-for-beginners
88 Python Projects from Beginner to Advanced (2026)
2 days ago - Predicting the Weather Using Machine Learning (PREMIUM) — Step into the role of a data scientist to predict tomorrow's weather using historical data and machine learning, developing skills in data preparation, time series analysis, and model evaluation. Find out How Much Money You've Spent on Amazon — Dig into your own spending habits with this beginner-level tutorial! Analyze Your Personal Netflix Data — Another beginner-to-intermediate tutorial that gets you working with your own personal dataset. Analyze Survey Data — This walk-through will show you how to set up Python and how to filter survey data from any dataset (or just use the sample data linked in the article).
StrataScratch
stratascratch.com › blog › 11-data-analytics-projects-for-every-level
11 Data Analytics Projects for Every Level - StrataScratch
March 18, 2025 - Beginners can start with Excel, SQL, and Tableau or Power BI for basic analysis and visualization. For more advanced projects, use Python and libraries like pandas, NumPy, Matplotlib, and Seaborn.
GitHub
github.com › shsarv › Data-Analytics-Projects-in-python
GitHub - shsarv/Data-Analytics-Projects-in-python: A collection of data analysis and visualization projects designed to uncover insights from diverse datasets. These projects include analyses on COVID-19 trends, stock trading patterns, housing market prices, IoT data, and more, showcasing the power of data-driven storytelling. · GitHub
A collection of data analysis and visualization projects designed to uncover insights from diverse datasets. These projects include analyses on COVID-19 trends, stock trading patterns, housing market prices, IoT data, and more, showcasing the ...
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Medium
medium.com › @amit25173 › exploratory-data-analysis-projects-with-python-code-from-beginner-to-advanced-b5e1502859e6
Exploratory Data Analysis Projects with Python Code: From Beginner to Advanced | by Amit Yadav | Medium
April 18, 2025 - Sentiment Analysis on Social Media: Finally, we’ll explore sentiment analysis on social media data. You’ll clean and preprocess text data, visualize sentiment distributions, and correlate these sentiments with external events. Throughout these projects, we’ll be using tools and libraries such as pandas, matplotlib, seaborn, and plotly in Python, which are essential for any data scientist.
Springboard
springboard.com › blog › data analytics › data analyst projects: 21 ideas to grow your skills in 2025
Data Analyst Projects: 21 Ideas to Grow Your Skills in 2025
March 27, 2025 - Twitter Sentiment Analysis: Use the Twitter API to scrape tweets on a trending topic and classify them using TextBlob or NLTK. Google Reviews: Extract customer reviews with the Google My Business API and analyze them for sentiment with Python’s TextBlob library. Quora Question Matching: Work with duplicate question pair detection using this Kaggle dataset.