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Contains Assignment 3 & 4 - pandas in python
PraneethaML/Coursera-Introduction-to-data-science-with-python
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This repository consists of Assignment 3 and 4 of the above mentioned course.
Assignment 3 deals with working on pandasa to analyse
- energy data from the file Energy Indicators.xls, which is a list of indicators of energy supply and renewable electricity production from the United Nations for the year 2013
- GDP data from the file world_bank.csv, which is a csv containing countries' GDP from 1960 to 2015 from World Bank.
- Sciamgo Journal and Country Rank data for Energy Engineering and Power Technology from the file scimagojr-3.xlsx, which ranks countries based on their journal contributions in the aforementioned area
Assignment 4 - Hypothesis:
University towns have their mean housing prices less effected by recessions. Run a t-test to compare the ratio of the mean price of houses in university towns the quarter before the recession starts compared to the recession bottom. (price_ratio=quarter_before_recession/recession_bottom)
The following data files are available for this assignment:
- From the Zillow research data site there is housing data for the United States. In particular the datafile for all homes at a city level, City_Zhvi_AllHomes.csv, has median home sale prices at a fine grained level.
- From the Wikipedia page on college towns is a list of university towns in the United States which has been copy and pasted into the file university_towns.txt.
- From Bureau of Economic Analysis, US Department of Commerce, the GDP over time of the United States in current dollars (use the chained value in 2009 dollars), in quarterly intervals, in the file gdplev.xls. For this assignment, only look at GDP data from the first quarter of 2000 onward.
- Jupyter Notebook 100.0%
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This repository includes course assignments of Introduction to Data Science in Python on coursera by university of michigan - tchagau/Introduction-to-Data-Science-in-Python
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