CSDA 1100 Software Lab 2

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York University *

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CSDA1000

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Computer Science

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Feb 20, 2024

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2

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CSDA 1100 – Data Analytics for Business Software Lab 2 Accessing Data with Python Objectives 1. Access data from a variety of sources using Python libraries and store it for analysis. 2. Apply basic functionality of the Pandas library for data access and analysis 3. Access data from some common websites using Python to issue an API request 4. Inspect the data structure and format after it has been stored in Python Step 1 • A series of videos to learn Python coding skills are available at the following web site • https://www.freecodecamp.org/learn/data-analysis-with-python/#data-analysis-with- python-course • Depending on your background, you are encouraged to view these videos as required. This is optional for you within the objectives of this lab. • Specific videos will be referenced as resources for this labs and other weekly labs as required Step 2 - Optional • These videos are optional. You can proceed directly to Step 3 if you want to seen actual samples and carry out the lab • Review the following videos to gain background on using Python and its Pandas library • Pandas is a useful library for accessing, storing and manipulating data • These videos are optional. You can proceed directly to Step 3 if you want to seen actual samples and carry out the lab • Introduction to Pandas Dataframes • https://www.freecodecamp.org/learn/data-analysis-with-python/data-analysis-with- python-course/pandas-dataframes • Indexing and Conditional Selection • https://www.freecodecamp.org/learn/data-analysis-with-python/data-analysis-with- python-course/pandas-indexing-and-conditional-selection • Reading Data Introduction • https://www.freecodecamp.org/learn/data-analysis-with-python/data-analysis-with- python-course/reading-data-introduction • Reading Data csv and txt • https://www.freecodecamp.org/learn/data-analysis-with-python/data-analysis-with- python-course/reading-data-csv-and-txt
Step 3 Note a series of reference sheets for Pandas and Matplotlib are provided in the weekly zip file for your reference Review the weekly lab Jupyter notebook CSDA 1100 Lab 2 Notebook.ipynb There are 8 examples provided for access local csv files and web based data using a variety of methods. The purpose of this review is to become aware of some basic capabilities for accessing data for your analysis Step 4 To practice your coding skills, carry out the following lab activities. Use the weekly sample notebook as a reference and guide. 1. Create a new data frame that includes data for inflation (infl) and gdp (realgdp) for the years of 1972 to 1975 2. Access stock price data for Apple (AAPL) for 2015 to 2020 and plot the trading volume as a line graph 3. Access gdp data from either Quandl or the World Bank for France and from 2000 to 2021. Plot the data as a line graph 4. Access the address of the following Airport codes, YYC, YVR, SFO, YYZ, ORD, LAX, LGA and EWR 5. Determine the shape of your data frames for Q1, Q2 and Q3 6. Determine the total COVID 19 case count for Canada, France, Spain and Italy up to the current day you run your code.
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