Data Analysis Using Python - University of Pennsylvania

Data Analysis Using Python - a course by the University of Pennsylvania

My dairy about the journey of studies:

Instructor: Brandon Krakowsky
Coursera Course - Data Analysis Using Python
Part of Introduction to Programming with Python and Java Specialization

Data Analysis Using Python - Part 1 of "Introduction to Programming with Python and Java Specialization"

Module 1: Loading, Querying, Filtering Data using the csv Module

Module 1 - (3) Importing and reading a file using the csv module

Loading Data:

Download and install Anaconda (Python 3 + Jupyter Notebook all at once)

Quiz 1:

Quiz 2:
The correct answer is:

✅ filtered_flights = [row for row in flights if row["Departure"] == "Philadelphia" and row["Destination"] == "Los Angeles" and float(row["Price"]) < 1200]
Run Module 1 - Lab 1 - Work with ufo sightings data (hints: better to create your own github account and "fork" the whole project space (as in your own account space) to run.

Quiz 3: Loading, Inspecting, & Querying Data

(*Step) Clean Data & Deal With Missing Data

Try Github: Data Analysis, Joining & Filtering Data(.ipynb)

df[-1:]['name'] is the same as that at line #47 above.
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Module 2: Querying data using boolean indexing

Computations - Sum( ) and mean( ): Hyperink

Other Methods - Video Hyperlink

Module 2 - Code Along Exercise : Add rating column - Video Hyperlink

Quiz 4 - Joining & Filtering Data

Module 3: Summarizing & Visualizing Data - NumPy Library

Type Errors:
There are four options, and three of them can run /wo errors:
.....

(You can also download the files from the Github and run in VS Code under Code Space, or in your local machine)

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