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Data Analysis with Python: Zero to Pandas - Student Performance

Step 1: Select a real-world dataset

Here's some sample code for downloading the US Elections Dataset:

import opendatasets as od
dataset_url = 'https://www.kaggle.com/tunguz/us-elections-dataset'
od.download('https://www.kaggle.com/tunguz/us-elections-dataset')

You can find a list of recommended datasets here: https://jovian.ml/forum/t/recommended-datasets-for-course-project/11711

Step 2: Perform data preparation & cleaning

  • Load the dataset into a data frame using Pandas
  • Explore the number of rows & columns, ranges of values etc.
  • Handle missing, incorrect and invalid data
  • Perform any additional steps (parsing dates, creating additional columns, merging multiple dataset etc.)

Step 3: Perform exploratory analysis & visualization

  • Compute the mean, sum, range and other interesting statistics for numeric columns
  • Explore distributions of numeric columns using histograms etc.
  • Explore relationship between columns using scatter plots, bar charts etc.
  • Make a note of interesting insights from the exploratory analysis

Step 4: Ask & answer questions about the data

  • Ask at least 4 interesting questions about your dataset
  • Answer the questions either by computing the results using Numpy/Pandas or by plotting graphs using Matplotlib/Seaborn
  • Create new columns, merge multiple dataset and perform grouping/aggregation wherever necessary
  • Wherever you're using a library function from Pandas/Numpy/Matplotlib etc. explain briefly what it does

Step 5: Summarize your inferences & write a conclusion

  • Write a summary of what you've learned from the analysis
  • Include interesting insights and graphs from previous sections
  • Share ideas for future work on the same topic using other relevant datasets
  • Share links to resources you found useful during your analysis

Step 6: Make a submission & share your work

(Optional) Step 7: Write a blog post

  • A blog post is a great way to present and showcase your work.
  • Sign up on Medium.com to write a blog post for your project.
  • Copy over the explanations from your Jupyter notebook into your blog post, and embed code cells & outputs
  • Check out the Jovian.ml Medium publication for inspiration: https://medium.com/jovianml

Example Projects

Refer to these projects for inspiration:

NOTE: Remove this cell containing the instructions before making your submission. You can do using the "Edit > Delete Cells" menu option.

Project Title - Student Performance Data Analysis

This a course project and the data set retrieved is from 'Kaggle.com'. The dataset I have used here has 1000+ entries, and tries to explain how certain aspects affect students' performance during a test. In this project Python's Opendatasets is used to download the dataset, Pandas for analysis, and Matplotlib and Seaborn for Visualization.

The DataAnalysis course on zerotopandas.com has helped me understand the basics and develop interest in Analytics.

Downloading the Dataset

TODO - We are going to download the data set for kaggle.com using the opendatasets module.

!pip install jovian opendatasets --upgrade --quiet

Let's begin by downloading the data, and listing the files within the dataset.