Welcome to the thrilling world of speed dating analysis! Prepare to embark on an exciting journey through a dataset filled with romantic encounters. In this assignment, you'll have the opportunity to delve into the dataset, uncover captivating insights about participants' attributes, preferences, and dating experiences using Python and SQL. So, gather your tools of data analysis and let's embark on this thrilling dating adventure together, here is the dataset needed for this fun trip with all the included description of what each data cell mean: https://www.kaggle.com/datasets/whenamancodes/speed-dating
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The Great Exploration
- Embark on an exhilarating quest to explore the dataset! Uncover hidden gems, untangle missing pieces, and unravel enchanting patterns that weave participants' dating tales using SQL queries.
- Objective: Write SQL queries to retrieve relevant data from the database and explore the dataset.
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Love Stats Galore
- Become a statistical cupid! Calculate mesmerizing statistics like averages, ranges, and counts to understand the heart of the dataset. Discover the secrets of participants' ages, races, and their pursuit of attraction using SQL aggregate functions.
- Objective: Use SQL aggregate functions to calculate statistics such as average age, age range, and counts of participants based on their attributes.
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Visualize Your Dating Destiny
- Paint a vivid picture of dating adventures with captivating visualizations! Create delightful charts and plots that showcase participants' preferences, age dynamics, and the magic of shared interests using Python's data visualization libraries. Retrieve the necessary data using SQL queries.
- Objective: Create a bar plot to compare the distribution of ages for males and females in the dataset.
- Objective: Generate a scatter plot showing the correlation between a participant's attractiveness rating and their partner's attractiveness rating.
- Objective: Design a pie chart to visualize the distribution of races among the participants.
- Objective: Develop a line plot to show how the importance of shared interests changes with age.
- Objective: Construct a stacked bar plot to compare the preferences of participants for attractiveness, sincerity, intelligence, and humor.
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Hypothesis Heartthrobs
- Embrace your inner detective and test romantic hypotheses! Investigate whether participants who highly value attractiveness are more likely to find love, or if there's a connection between shared race and the importance of having the same religion. Unlock the secrets of successful matches through your analytical prowess using SQL queries and Python's statistical libraries.
- Objective: Test the hypothesis: Participants who rate attractiveness as highly important are more likely to get matches than those who rate it as less important.
- Objective: Investigate the hypothesis: There is a significant difference in the expected happiness level between participants who have previously met their partners and those who haven't.
- Objective: Perform a hypothesis test to determine if there is a relationship between the race of a participant and the importance they place on having the same religion.
- Objective: Analyze the hypothesis: The average ratings for intelligence given by participants and their partners are significantly different.
- Objective: Conduct a hypothesis test to examine whether there is a correlation between a participant's interest in museums and their interest in art.
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Share the Love
- Craft a charming story of your findings! Share your insights in a way that sparks curiosity and captures hearts. Use the power of clear explanations, enchanting visualizations, and SQL queries to transport your audience into the realm of speed dating magic.
- Love Potion Python: Embrace the enchanting powers of Python, the language of love, for all your data analysis tasks.
- Heartwarming SQL: Utilize SQL queries to retrieve and manipulate data from the database.
- Loveable Libraries: Harness the magic of libraries such as Pandas, Matplotlib, Seaborn, and SQLalchemy to create a delightful experience of data manipulation, visualization, and database interaction.
- Love Chronicles: Jupyter Notebook or Python scripts documenting your dating adventures, step by step!
- Love Notes: Documentation that reveals your fascinating findings and conclusions with a touch of whimsy.
- Enchanting Visualizations: Delightful charts and plots that bring the magic of speed dating to life.
- Follow your curious heart and embark on a fearless exploration of the dataset!
- Embrace the magic of SQL queries to retrieve and manipulate data from the database.
- Cast spells of visualizations to capture the essence of participants' experiences.
- Formulate enchanting hypotheses and test them to uncover the secrets of successful matches.
- Share your insights with love and charm, using clear explanations, captivating visualizations, and SQL queries.
Please submit your completed assignment by emailing the Jupyter Notebook, Python scripts, and documentation here. If the files are too large to upload, you can share them through a file-sharing service or repository (e.g., Google Drive, GitHub).